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By operation of the Public Governance, Performance and Accountability (Establishing the Australian Digital best online singulair Health Agency) Rule 2016, on 1 July 2016, all the assets and liabilities of singulair leukotriene NEHTA will vest in the Australian Digital Health Agency. In this website, on and from 1 July 2016, all references to "National E-Health Transition Authority" or "NEHTA" will be deemed to be references to the Australian Digital Health Agency best online singulair. PCEHR means the My Health Record, formerly the "Personally Controlled Electronic Health Record", within the meaning of the My Health Records Act 2012 (Cth), formerly called the Personally Controlled Electronic Health Records Act 2012 (Cth). Website Accessibility Copyright ©2015-2020 Australian Digital Health best online singulair AgencyWhat’s happened?.

We have received reports of fraudulent telephone calls from an individual or organisation claiming to be a representative of the Australian Digital Health Agency. It has been reported that the caller says they are calling from the “digital health agency” to enrol people to get a “health record”.What do I need best online singulair to do?. If you receive a call from someone offering to enrol you for a “health record”, do not provide any personal information, hang up the call and report it to scamwatch.gov.au.The Australian Digital Health Agency will not telephone you with an offer to enrol you for a My Health Record. For more information on how to register for a My Health Record, visit myhealthrecord.gov.au.If you best online singulair have shared your Medicare number with an unknown caller, report this to Services Australia who will place your details on a watch list to monitor for any compromise or misuse of your Medicare record.

Email [email protected] or best online singulair phone 1800 941 126. How could this affect me?. The caller is requesting personal information which could be used to steal your identity or best online singulair commit financial fraud. Reports indicate that the caller is requesting the following personal information:• Medicare number• Date of birth• Email address• Mobile telephone number• Credit card detailsIdentity theft (also known as identity fraud) occurs when one person uses another individual’s personal information without their consent, usually for personal gain or to conduct further crimes.Where can I get more information?.

If you have shared personal information and believe you may be at risk, you can contact IDCARE, a not for profit organisation that provides assistance and support to victims of identity theft and other cybercrime. Visit idcare.org or telephone 1800 595 160.The Office of the Australian Information Commissioner provides information about identity fraud including what to do if your identity has been stolen.For additional information about scams, visit scamwatch.gov.au – you can also subscribe to a free alert service to receive updates about the latest scams.The Australian Cyber Security Centre also provides advice for individuals, a free alert service to help you understand the latest online threats and the ability to report online crimes via the ReportCyber page..

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1) by can you take singulair and allegra at the same time receiving how long does it take for singulair to start working Medicaid. Medicaid recipients, including those who meet a spenddown, are "deemed" into LIS (automatically enrolled by SSA) and don't have to file a separate application for Extra Help. See more below about how receiving Medicaid just for one month can qualify you for Full Extra Help for up to 18 months.

2) by enrolling can you take singulair and allegra at the same time in a Medicare Savings Program. The Medicare Savings Program includes the Qualified Medicare Beneficiary (QMB) program, which covers beneficiaries up to 100% FPL. Specified Low-Income Medicare Beneficiary (SLIMB), for those between 100-120%.

And the Qualified Individual (QI-1) program, for can you take singulair and allegra at the same time individuals between 120-135% FPL. There are no resource tests in New York's Medicare Savings Program.) The New York State Department of Health posts the Medicare Savings Program income guidelines on their website. Just like Medicaid, Medicare Savings Program recipients are deemed into LIS and don't need to apply through SSA.

For more information see this can you take singulair and allegra at the same time article. 3) by applying for Extra Help through the Social Security Administration. The Extra Help income limits are 150% FPL and there is an asset test.

SSA lists the income and resource limits for Extra Help on their website, where you can also file an application online and get more information about the program can you take singulair and allegra at the same time. You can also find out information about Extra Help in many different languages. See Medicare Rights Center chart on Extra Help Income and Asset Limits - updated annually You can apply for Extra Help and MSP at the same time through SSA.

SSA will forward your Extra Help can you take singulair and allegra at the same time application data to the New York State Department of Health, who will use that data to assess your eligibility for MSP. Individuals who apply for LIS through SSA and those who are deemed into LIS should receive written confirmation of their Extra Help status through SSA. Of course, individuals who apply for LIS through SSA and are found ineligible are also entitled to a written notice and have appeal rights.

Benefits of Extra Help 1) Assistance with Part D cost-sharing The Extra Help program provides a subsidy which covers most (but not all) of beneficiary’s cost sharing obligations can you take singulair and allegra at the same time. Extra Help beneficiaries do not have to worry about hitting the “donut hole” – the LIS subsidy continues to cover them through the donut hole and into catastrophic coverage. Full Extra Help.

LIS beneficiaries with incomes up to 135% FPL are generally eligible for can you take singulair and allegra at the same time "full" Extra Help -- meaning they pay no Part D deductible, no charge for monthly premiums up to the benchmark amount, and fixed, relatively low co-pays (between $1.30 and $8.95 for 2020 depending on the person's income level and the tier category of the drug. Medicaid beneficiaries in nursing homes, waiver programs, or managed long term care have $0 co-pays). Full Extra Help beneficiaries who hit the catastrophic coverage limit have $0 co-pays.

See current co-pay levels here can you take singulair and allegra at the same time. Partial Extra Help. Beneficiaries between 135%-150% FPL receive "partial" Extra Help, which limits the Part D deductible to $89 (2020 figure - click here for updated chart).

Sets sliding scale can you take singulair and allegra at the same time fees for monthly premiums. And limits co-pays to 15%, until the beneficiary reaches the catastrophic coverage limit, at which point co-pays are limited to a $8.95 maximum (2020 or see current amount here) or 5% of the drug cost, whichever is greater. 2) Facilitated enrollment into a Part D visit this site plan Extra Help recipients who aren’t already enrolled in a Part D plan and don’t want to choose one on their own will be automatically enrolled into a benchmark plan by CMS.

This facilitated enrollment ensures that Extra Help recipients can you take singulair and allegra at the same time have Part D coverage. However, the downside to facilitated enrollment is that the plan may not be the best “fit” for the beneficiary, if it doesn’t cover all his/her drugs, assesses a higher tier level for covered drugs than other comparable plans, and/or requires the beneficiary to go through administrative hoops like prior authorization, quantity limits and/or step therapy. Fortunately, Extra Help recipients can always enroll in a new plan … see #3 below.

3) Continuous special enrollment period Extra can you take singulair and allegra at the same time Help recipients have a continuous special enrollment period, meaning that they can switch plans at any time. They are not “locked into” the annual open enrollment period (October 15-December 7). NOTE.

This can you take singulair and allegra at the same time changed in 2019. Starting in 2019, those with Extra Help will no longer have a continuous enrollment period. Instead, Extra Help recipients will be eligible to enroll no more than once per quarter for each of the first three quarters of the year.

4) No late enrollment penalty Non LIS beneficiaries generally face a premium penalty (higher monthly premium) if they delayed their enrollment into Part D, meaning that they didn’t enroll when they were initially eligible and didn’t have “creditable coverage.” Extra Help recipients do can you take singulair and allegra at the same time not have to worry about this problem – the late enrollment penalty provision does not apply to LIS beneficiaries. 1) For “deemed” beneficiaries (Medicaid/Medicare Savings Program recipients). Extra Help status lasts at least until the end of the current calendar year, even if the individual loses their Medicaid or Medicare Savings Program coverage during that year.

Individuals who receive Medicaid or a Medicare Savings Program any can you take singulair and allegra at the same time month between July and December keep their LIS status for the remainder of that calendar year and the following year. Getting Medicaid coverage for even just a short period of time (ie, meeting a spenddown for just one month) can help ensure that the individual obtains Extra Help coverage for at least 6 months, and possibly as long as 18 months. TIP.

People with a high spend-down who want to receive Medicaid for just one month in order to get Extra Help for 6-18 months can use past can you take singulair and allegra at the same time medical bills to meet their spend-down for that one month. There are different rules for using past paid medical bills verses past unpaid medical bills. For information see Spend down training materials.

Individuals who are losing their deemed status at the end of a calendar year because they are no longer receiving Medicaid or the Medicare Savings Program should be notified in advance by SSA, and given an opportunity to file can you take singulair and allegra at the same time an Extra Help application through SSA. 2) For “non-deemed” beneficiaries (those who filed their LIS applications through SSA) Non-deemed beneficiaries retain their LIS status until/unless SSA does a redetermination and finds the individual ineligible for Extra Help. There are no reporting requirements per se in the Extra Help program, but beneficiaries must respond to SSA’s redetermination request.

What to do if the Part D plan doesn't know that someone has Extra Help Sometimes there are lengthy delays between the date that someone is approved for Medicaid or a Medicare Savings Program and when that information is formally conveyed to the Part D plan by CMS. As a practical matter, this often results in beneficiaries being charged co-pays, premiums and/or deductibles that they can't afford and shouldn't have to pay. To protect LIS beneficiaries, CMS has a "Best Available Evidence" policy which requires plans to accept alternative forms of proof of someone's LIS status and adjust the person's cost-sharing obligation accordingly.

LIS beneficiaries who are being charged improperly should be sure to contact their plan and provide proof of their LIS status. If the plan still won't recognize their LIS status, the person or their advocate should file a complaint with the CMS regional office. The federal regulations governing the Low Income Subsidy program can be found at 42 CFR Subpart P (sections 423.771 through 423.800).

Also, CMS provides detailed guidance on the LIS provisions in chapter 13 of its Medicare Prescription Drug Benefit Manual.

LIS is also known as best online singulair "Extra Help." The who makes singulair Social Security Administration administers LIS -- you don't apply through your Part D plan. See Medicare Rights Center chart on Extra Help Income and Asset Limits (listed amounts already deduct the $20/month income disregard)(they update it annually) Enrolling in Extra Help There are three basic ways to get into the LIS program. 1) by receiving Medicaid. Medicaid recipients, including those who meet a spenddown, are "deemed" into LIS (automatically enrolled by SSA) and don't have to file a separate application best online singulair for Extra Help. See more below about how receiving Medicaid just for one month can qualify you for Full Extra Help for up to 18 months.

2) by enrolling in a Medicare Savings Program. The Medicare best online singulair Savings Program includes the Qualified Medicare Beneficiary (QMB) program, which covers beneficiaries up to 100% FPL. Specified Low-Income Medicare Beneficiary (SLIMB), for those between 100-120%. And the Qualified Individual (QI-1) program, for individuals between 120-135% FPL. There are no resource tests in New York's Medicare Savings Program.) The best online singulair New York State Department of Health posts the Medicare Savings Program income guidelines on their website.

Just like Medicaid, Medicare Savings Program recipients are deemed into LIS and don't need to apply through SSA. For more information see this article. 3) by best online singulair applying for Extra Help through the Social Security Administration. The Extra Help income limits are 150% FPL and there is an asset test. SSA lists the income and resource limits for Extra Help on their website, where you can also file an application online and get more information about the program.

You can also find out information about Extra Help in many different best online singulair languages. See Medicare Rights Center chart on Extra Help Income and Asset Limits - updated annually You can apply for Extra Help and MSP at the same time through SSA. SSA will forward your Extra Help application data to the New York State Department of Health, who will use that data to assess your eligibility for MSP. Individuals who apply for LIS best online singulair through SSA and those who are deemed into LIS should receive written confirmation of their Extra Help status through SSA. Of course, individuals who apply for LIS through SSA and are found ineligible are also entitled to a written notice and have appeal rights.

Benefits of Extra Help 1) Assistance with Part D cost-sharing The Extra Help program provides a subsidy which covers most (but not all) of beneficiary’s cost sharing obligations. Extra Help beneficiaries do not have to worry about hitting the “donut hole” – the LIS subsidy continues best online singulair to cover them through the donut hole and into catastrophic coverage. Full Extra Help. LIS beneficiaries with incomes up to 135% FPL are generally eligible for "full" Extra Help -- meaning they pay no Part D deductible, no charge for monthly premiums up to the benchmark amount, and fixed, relatively low co-pays (between $1.30 and $8.95 for 2020 depending on the person's income level and the tier category of the drug. Medicaid beneficiaries in nursing homes, waiver programs, or best online singulair managed long term care have $0 co-pays).

Full Extra Help beneficiaries who hit the catastrophic coverage limit have $0 co-pays. See current co-pay levels here. Partial best online singulair Extra Help. Beneficiaries between 135%-150% FPL receive "partial" Extra Help, which limits the Part D deductible to $89 (2020 figure - click here for updated chart). Sets sliding scale fees for monthly premiums.

And limits co-pays to 15%, until the beneficiary reaches the catastrophic coverage limit, at which point co-pays are limited to a $8.95 maximum (2020 or see current amount here) or 5% of the drug cost, whichever is best online singulair greater. 2) Facilitated enrollment into a Part D plan Extra Help recipients who aren’t already enrolled in a Part D plan and don’t want to choose one on their own will be automatically enrolled into a benchmark plan by CMS. This facilitated enrollment ensures that Extra Help recipients have Part D coverage. However, the downside to facilitated enrollment is that the plan may not be the best “fit” for the beneficiary, if it doesn’t cover all his/her drugs, assesses a higher tier level for covered drugs than other comparable plans, and/or requires the beneficiary to go through administrative best online singulair hoops like prior authorization, quantity limits and/or step therapy. Fortunately, Extra Help recipients can always enroll in a new plan … see #3 below.

3) Continuous special enrollment period Extra Help recipients have a continuous special enrollment period, meaning that they can switch plans at any time. They are not “locked best online singulair into” the annual open enrollment period (October 15-December 7). NOTE. This changed in 2019. Starting in 2019, those with Extra Help will no longer best online singulair have a continuous enrollment period.

Instead, Extra Help recipients will be eligible to enroll no more than once per quarter for each of the first three quarters of the year. 4) No late enrollment penalty Non LIS beneficiaries generally face a premium penalty (higher monthly premium) if they delayed their enrollment into Part D, meaning that they didn’t enroll when they were initially eligible and didn’t have “creditable coverage.” Extra Help recipients do not have to worry about this problem – the late enrollment penalty provision does not apply to LIS beneficiaries. 1) For “deemed” beneficiaries (Medicaid/Medicare Savings best online singulair Program recipients). Extra Help status lasts at least until the end of the current calendar year, even if the individual loses their Medicaid or Medicare Savings Program coverage during that year. Individuals who receive Medicaid or a Medicare Savings Program any month between July and December keep their LIS status for the remainder of that calendar year and the following year.

Getting Medicaid coverage for even just a short period of best online singulair time (ie, meeting a spenddown for just one month) can help ensure that the individual obtains Extra Help coverage for at least 6 months, and possibly as long as 18 months. TIP. People with a high spend-down who want to receive Medicaid for just one month in order to get Extra Help for 6-18 months can use past medical bills to meet their spend-down for that one month. There are best online singulair different rules for using past paid medical bills verses past unpaid medical bills. For information see Spend down training materials.

Individuals who are losing their deemed status at the end of a calendar year because they are no longer receiving Medicaid or the Medicare Savings Program should be notified in advance by SSA, and given an opportunity to file an Extra Help application through SSA. 2) For “non-deemed” beneficiaries (those who filed their LIS applications through SSA) Non-deemed beneficiaries retain their LIS status until/unless SSA does a redetermination and finds the individual ineligible best online singulair for Extra Help. There are no reporting requirements per se in the Extra Help program, but beneficiaries must respond to SSA’s redetermination request. What to do if the Part D plan doesn't know that someone has Extra Help Sometimes there are lengthy delays between the date that someone is approved for Medicaid or a Medicare Savings Program and when that information is formally conveyed to the Part D plan by CMS. As a practical matter, this often results in beneficiaries being charged co-pays, premiums and/or deductibles that they can't best online singulair afford and shouldn't have to pay.

To protect LIS beneficiaries, CMS has a "Best Available Evidence" policy which requires plans to accept alternative forms of proof of someone's LIS status and adjust the person's cost-sharing obligation accordingly. LIS beneficiaries who are being charged improperly should be sure to contact their plan and provide proof of their LIS status. If the plan still won't recognize their LIS status, the person or their advocate should file a complaint with the CMS regional office.

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How to cite this article:Singh O singulair drug class P. Aftermath of celebrity suicide – Media coverage and role of psychiatrists. Indian J Psychiatry 2020;62:337-8Celebrity suicide is one of the highly publicized singulair drug class events in our country.

Indians got a glimpse of this following an unfortunate incident where a popular Hindi film actor died of suicide. As expected, the media went into a frenzy as newspapers, news channels, and social media were full of stories providing minute details of singulair drug class the suicidal act. Some even going as far as highlighting the color of the cloth used in the suicide as well as showing the lifeless body of the actor.

All kinds of personal details were dug up, and speculations and hypotheses became the order of the day in the next few days that followed. In the singulair drug class process, reputations of many people associated with the actor were besmirched and their private and personal details were freely and blatantly broadcast and discussed on electronic, print, and social media. We understand that media houses have their own need and duty to report and sensationalize news for increasing their visibility (aka TRP), but such reporting has huge impacts on the mental health of the vulnerable population.The impact of this was soon realized when many incidents of copycat suicide were reported from all over the country within a few days of the incident.

Psychiatrists suddenly started getting distress calls from their patients singulair drug class in despair with increased suicidal ideation. This has become a major area of concern for the psychiatry community.The Indian Psychiatric Society has been consistently trying to engage with media to promote ethical reporting of suicide. Section 24 (1) of Mental Health Care Act, 2017, forbids publication of photograph of mentally ill person without his consent.[1] The Press singulair drug class Council of India has adopted the guidelines of World Health Organization report on Preventing Suicide.

A resource for media professionals, which came out with an advisory to be followed by media in reporting cases of suicide. It includes points forbidding them from putting stories in prominent positions and unduly repeating them, explicitly describing the method used, providing details about the site/location, using sensational headlines, or using photographs and video footage of the incident.[2] Unfortunately, the advisory seems to have little effect in the aftermath of celebrity suicides. Channels were full of speculations about the person's mental condition and singulair drug class illness and also his relationships and finances.

Many fictional accounts of his symptoms and illness were touted, which is not only against the ethics but is also contrary to MHCA, 2017.[1]It went to the extent that the name of his psychiatrist was mentioned and quotes were attributed to him without taking any account from him. The Indian Psychiatric Society has written to the Press Council of India underlining this concern and asking for measures to ensure ethics in reporting suicide.While there is a need for engagement with media to make them aware singulair drug class of the grave impact of negative suicide reporting on the lives of many vulnerable persons, there is even a more urgent need for training of psychiatrists regarding the proper way of interaction with media. This has been amply brought out in the aftermath of this incident.

Many psychiatrists and mental health professionals were called by singulair drug class media houses to comment on the episode. Many psychiatrists were quoted, or “misquoted,” or “quoted out of context,” commenting on the life of a person whom they had never examined and had no “professional authority” to do so. There were even stories with byline of a psychiatrist where the content provided was not only unscientific but also way beyond the expertise of a psychiatrist.

These types of viewpoints perpetuate stigma, myths, and “misleading concepts” about psychiatry and singulair drug class are detrimental to the image of psychiatry in addition to doing harm and injustice to our patients. Hence, the need to formulate a guideline for interaction of psychiatrists with the media is imperative.In the infamous Goldwater episode, 12,356 psychiatrists were asked to cast opinion about the fitness of Barry Goldwater for presidential candidature. Out of 2417 respondents, 1189 psychiatrists reported him to be mentally unfit while none had actually examined him.[3] This led to the formulation of “The Goldwater Rule” by the American Psychiatric Association in 1973,[4] but we have witnessed the same phenomenon at the time of presidential singulair drug class candidature of Donald Trump.Psychiatrists should be encouraged to interact with media to provide scientific information about mental illnesses and reduction of stigma, but “statements to the media” can be a double-edged sword, and we should know about the rules of engagements and boundaries of interactions.

Methods and principles of interaction with media should form a part of our training curriculum. Many professional societies have guidelines and resource books for interacting with media, and psychiatrists should singulair drug class familiarize themselves with these documents. The Press Council guideline is likely to prompt reporters to seek psychiatrists for their expert opinion.

It is useful for them to have a template ready with suicide rates, emphasizing multicausality of suicide, role of mental disorders, as well as help available.[5]It is about time that the Indian Psychiatric Society formulated its own guidelines laying down the broad principles and boundaries governing the interaction of Indian psychiatrists with the media. Till then, it is desirable to be guided singulair drug class by the following broad principles:It should be assumed that no statement goes “off the record” as the media person is most likely recording the interview, and we should also record any such conversation from our endIt should be clarified in which capacity comments are being made – professional, personal, or as a representative of an organizationOne should not comment on any person whom he has not examinedPsychiatrists should take any such opportunity to educate the public about mental health issuesThe comments should be justified and limited by the boundaries of scientific knowledge available at the moment. References Correspondence Address:Dr.

O P SinghAA 304, Ashabari Apartments, O/31, singulair drug class Baishnabghata, Patuli Township, Kolkata - 700 094, West Bengal IndiaSource of Support. None, Conflict of Interest. NoneDOI.

10.4103/psychiatry.IndianJPsychiatry_816_20Abstract Electroconvulsive therapy (ECT) is an effective modality of treatment for a variety of psychiatric disorders. However, it has always been accused of being a coercive, unethical, and dangerous modality of treatment. The dangerousness of ECT has been mainly attributed to its claimed ability to cause brain damage.

This narrative review aims to provide an update of the evidence with regard to whether the practice of ECT is associated with damage to the brain. An accepted definition of brain damage remains elusive. There are also ethical and technical problems in designing studies that look at this question specifically.

Thus, even though there are newer technological tools and innovations, any review attempting to answer this question would have to take recourse to indirect methods. These include structural, functional, and metabolic neuroimaging. Body fluid biochemical marker studies.

And follow-up studies of cognitive impairment and incidence of dementia in people who have received ECT among others. The review of literature and present evidence suggests that ECT has a demonstrable impact on the structure and function of the brain. However, there is a lack of evidence at present to suggest that ECT causes brain damage.Keywords.

Adverse effect, brain damage, electroconvulsive therapyHow to cite this article:Jolly AJ, Singh SM. Does electroconvulsive therapy cause brain damage. An update.

Indian J Psychiatry 2020;62:339-53 Introduction Electroconvulsive therapy (ECT) as a modality of treatment for psychiatric disorders has existed at least since 1938.[1] ECT is an effective modality of treatment for various psychiatric disorders. However, from the very beginning, the practice of ECT has also faced resistance from various groups who claim that it is coercive and harmful.[2] While the ethical aspects of the practice of ECT have been dealt with elsewhere, the question of harmfulness or brain damage consequent upon the passage of electric current needs to be examined afresh in light of technological advances and new knowledge.[3]The question whether ECT causes brain damage was reviewed in a holistic fashion by Devanand et al. In the mid-1990s.[4],[5] The authors had attempted to answer this question by reviewing the effect of ECT on the brain in various areas – cognitive side effects, structural neuroimaging studies, neuropathologic studies of patients who had received ECT, autopsy studies of epileptic patients, and finally animal ECS studies.

The authors had concluded that ECT does not produce brain damage.This narrative review aims to update the evidence with regard to whether ECT causes brain damage by reviewing relevant literature from 1994 to the present time. Framing the Question The Oxford Dictionary defines damage as physical harm that impairs the value, usefulness, or normal function of something.[6] Among medical dictionaries, the Peter Collins Dictionary defines damage as harm done to things (noun) or to harm something (verb).[7] Brain damage is defined by the British Medical Association Medical Dictionary as degeneration or death of nerve cells and tracts within the brain that may be localized to a particular area of the brain or diffuse.[8] Going by such a definition, brain damage in the context of ECT should refer to death or degeneration of brain tissue, which results in the impairment of functioning of the brain. The importance of precisely defining brain damage shall become evident subsequently in this review.There are now many more tools available to investigate the structure and function of brain in health and illness.

However, there are obvious ethical issues in designing human studies that are designed to answer this specific question. Therefore, one must necessarily take recourse to indirect evidences available through studies that have been designed to answer other research questions. These studies have employed the following methods:Structural neuroimaging studiesFunctional neuroimaging studiesMetabolic neuroimaging studiesBody fluid biochemical marker studiesCognitive impairment studies.While the early studies tended to focus more on establishing the safety of ECT and finding out whether ECT causes gross microscopic brain damage, the later studies especially since the advent of advanced neuroimaging techniques have been focusing more on a mechanistic understanding of ECT.

Hence, the primary objective of the later neuroimaging studies has been to look for structural and functional brain changes which might explain how ECT acts rather than evidence of gross structural damage per se. However, put together, all these studies would enable us to answer our titular question to some satisfaction. [Table 1] and [Table 2] provide an overview of the evidence base in this area.

Structural and Functional Neuroimaging Studies Devanand et al. Reviewed 16 structural neuroimaging studies on the effect of ECT on the brain.[4] Of these, two were pneumoencephalography studies, nine were computed tomography (CT) scan studies, and five were magnetic resonance imaging (MRI) studies. However, most of these studies were retrospective in design, with neuroimaging being done in patients who had received ECT in the past.

In the absence of baseline neuroimaging, it would be very difficult to attribute any structural brain changes to ECT. In addition, pneumoencephalography, CT scan, and even early 0.3 T MRI provided images with much lower spatial resolution than what is available today. The authors concluded that there was no evidence to show that ECT caused any structural damage to the brain.[4] Since then, at least twenty more MRI-based structural neuroimaging studies have studied the effect of ECT on the brain.

The earliest MRI studies in the early 1990s focused on detecting structural damage following ECT. All of these studies were prospective in design, with the first MRI scan done at baseline and a second MRI scan performed post ECT.[9],[11],[12],[13],[41] While most of the studies imaged the patient once around 24 h after receiving ECT, some studies performed multiple post ECT neuroimaging in the first 24 h after ECT to better capture the acute changes. A single study by Coffey et al.

Followed up the patients for a duration of 6 months and repeated neuroimaging again at 6 months in order to capture any long-term changes following ECT.[10]The most important conclusion which emerged from this early series of studies was that there was no evidence of cortical atrophy, change in ventricle size, or increase in white matter hyperintensities.[4] The next major conclusion was that there appeared to be an increase in the T1 and T2 relaxation time immediately following ECT, which returned to normal within 24 h. This supported the theory that immediately following ECT, there appears to be a temporary breakdown of the blood–brain barrier, leading to water influx into the brain tissue.[11] The last significant observation by Coffey et al. In 1991 was that there was no significant temporal changes in the total volumes of the frontal lobes, temporal lobes, or amygdala–hippocampal complex.[10] This was, however, something which would later be refuted by high-resolution MRI studies.

Nonetheless, one inescapable conclusion of these early studies was that there was no evidence of any gross structural brain changes following administration of ECT. Much later in 2007, Szabo et al. Used diffusion-weighted MRI to image patients in the immediate post ECT period and failed to observe any obvious brain tissue changes following ECT.[17]The next major breakthrough came in 2010 when Nordanskog et al.

Demonstrated that there was a significant increase in the volume of the hippocampus bilaterally following a course of ECT in a cohort of patients with depressive illness.[18] This contradicted the earlier observations by Coffey et al. That there was no volume increase in any part of the brain following ECT.[10] This was quite an exciting finding and was followed by several similar studies. However, the perspective of these studies was quite different from the early studies.

In contrast to the early studies looking for the evidence of ECT-related brain damage, the newer studies were focused more on elucidating the mechanism of action of ECT. Further on in 2014, Nordanskog et al. In a follow-up study showed that though there was a significant increase in the volume of the hippocampus 1 week after a course of ECT, the hippocampal volume returned to the baseline after 6 months.[19] Two other studies in 2013 showed that in addition to the hippocampus, the amygdala also showed significant volume increase following ECT.[20],[21] A series of structural neuroimaging studies after that have expanded on these findings and as of now, gray matter volume increase following ECT has been demonstrated in the hippocampus, amygdala, anterior temporal pole, subgenual cortex,[21] right caudate nucleus, and the whole of the medial temporal lobe (MTL) consisting of the hippocampus, amygdala, insula, and the posterosuperior temporal cortex,[24] para hippocampi, right subgenual anterior cingulate gyrus, and right anterior cingulate gyrus,[25] left cerebellar area VIIa crus I,[29] putamen, caudate nucleus, and nucleus acumbens [31] and clusters of increased cortical thickness involving the temporal pole, middle and superior temporal cortex, insula, and inferior temporal cortex.[27] However, the most consistently reported and replicated finding has been the bilateral increase in the volume of the hippocampus and amygdala.

In light of these findings, it has been tentatively suggested that ECT acts by inducing neuronal regeneration in the hippocampus – amygdala complex.[42],[43] However, there are certain inconsistencies to this hypothesis. Till date, only one study – Nordanskog et al., 2014 – has followed study patients for a long term – 6 months in their case. And significantly, the authors found out that after increasing immediately following ECT, the hippocampal volume returns back to baseline by 6 months.[19] This, however, was not associated with the relapse of depressive symptoms.

Another area of significant confusion has been the correlation of hippocampal volume increase with improvement of depressive symptoms. Though almost all studies demonstrate a significant increase in hippocampal volume following ECT, a majority of studies failed to demonstrate a correlation between symptom improvement and hippocampal volume increase.[19],[20],[22],[24],[28] However, a significant minority of volumetric studies have demonstrated correlation between increase in hippocampal and/or amygdala volume and improvement of symptoms.[21],[25],[30]Another set of studies have used diffusion tensor imaging, functional MRI (fMRI), anatomical connectome, and structural network analysis to study the effect of ECT on the brain. The first of these studies by Abbott et al.

In 2014 demonstrated that on fMRI, the connectivity between right and left hippocampus was significantly reduced in patients with severe depression. It was also shown that the connectivity was normalized following ECT, and symptom improvement was correlated with an increase in connectivity.[22] In a first of its kind DTI study, Lyden et al. In 2014 demonstrated that fractional anisotropy which is a measure of white matter tract or fiber density is increased post ECT in patients with severe depression in the anterior cingulum, forceps minor, and the dorsal aspect of the left superior longitudinal fasciculus.

The authors suggested that ECT acts to normalize major depressive disorder-related abnormalities in the structural connectivity of the dorsal fronto-limbic pathways.[23] Another DTI study in 2015 constructed large-scale anatomical networks of the human brain – connectomes, based on white matter fiber tractography. The authors found significant reorganization in the anatomical connections involving the limbic structure, temporal lobe, and frontal lobe. It was also found that connection changes between amygdala and para hippocampus correlated with reduction in depressive symptoms.[26] In 2016, Wolf et al.

Used a source-based morphometry approach to study the structural networks in patients with depression and schizophrenia and the effect of ECT on the same. It was found that the medial prefrontal cortex/anterior cingulate cortex (ACC/MPFC) network, MTL network, bilateral thalamus, and left cerebellar regions/precuneus exhibited significant difference between healthy controls and the patient population. It was also demonstrated that administration of ECT leads to significant increase in the network strength of the ACC/MPFC network and the MTL network though the increase in network strength and symptom amelioration were not correlated.[32]Building on these studies, a recently published meta-analysis has attempted a quantitative synthesis of brain volume changes – focusing on hippocampal volume increase following ECT in patients with major depressive disorder and bipolar disorder.

The authors initially selected 32 original articles from which six articles met the criteria for quantitative synthesis. The results showed significant increase in the volume of the right and left hippocampus following ECT. For the rest of the brain regions, the heterogeneity in protocols and imaging techniques did not permit a quantitative analysis, and the authors have resorted to a narrative review similar to the present one with similar conclusions.[44] Focusing exclusively on hippocampal volume change in ECT, Oltedal et al.

In 2018 conducted a mega-analysis of 281 patients with major depressive disorder treated with ECT enrolled at ten different global sites of the Global ECT-MRI Research Collaboration.[45] Similar to previous studies, there was a significant increase in hippocampal volume bilaterally with a dose–response relationship with the number of ECTs administered. Furthermore, bilateral (B/L) ECT was associated with an equal increase in volume in both right and left hippocampus, whereas right unilateral ECT was associated with greater volume increase in the right hippocampus. Finally, contrary to expectation, clinical improvement was found to be negatively correlated with hippocampal volume.Thus, a review of the current evidence amply demonstrates that from looking for ECT-related brain damage – and finding none, we have now moved ahead to looking for a mechanistic understanding of the effect of ECT.

In this regard, it has been found that ECT does induce structural changes in the brain – a fact which has been seized upon by some to claim that ECT causes brain damage.[46] Such statements should, however, be weighed against the definition of damage as understood by the scientific medical community and patient population. Neuroanatomical changes associated with effective ECT can be better described as ECT-induced brain neuroplasticity or ECT-induced brain neuromodulation rather than ECT-induced brain damage. Metabolic Neuroimaging Studies.

Magnetic Resonance Spectroscopic Imaging Magnetic resonance spectroscopic imaging (MRSI) uses a phase-encoding procedure to map the spatial distribution of magnetic resonance (MR) signals of different molecules. The crucial difference, however, is that while MRI maps the MR signals of water molecules, MRSI maps the MR signals generated by different metabolites – such as N-acetyl aspartate (NAA) and choline-containing compounds. However, the concentration of these metabolites is at least 10,000 times lower than water molecules and hence the signal strength generated would also be correspondingly lower.

However, MRSI offers us the unique advantage of studying in vivo the change in the concentration of brain metabolites, which has been of great significance in fields such as psychiatry, neurology, and basic neuroscience research.[47]MRSI studies on ECT in patients with depression have focused largely on four metabolites in the human brain – NAA, choline-containing compounds (Cho) which include majorly cell membrane compounds such as glycerophosphocholine, phosphocholine and a miniscule contribution from acetylcholine, creatinine (Cr) and glutamine and glutamate together (Glx). NAA is located exclusively in the neurons, and is suggested to be a marker of neuronal viability and functionality.[48] Choline-containing compounds (Cho) mainly include the membrane compounds, and an increase in Cho would be suggestive of increased membrane turnover. Cr serves as a marker of cellular energy metabolism, and its levels are usually expected to remain stable.

The regions which have been most widely studied in MRSI studies include the bilateral hippocampus and amygdala, dorsolateral prefrontal cortex (DLPFC), and ACC.Till date, five MRSI studies have measured NAA concentration in the hippocampus before and after ECT. Of these, three studies showed that there is no significant change in the NAA concentration in the hippocampus following ECT.[33],[38],[49] On the other hand, two recent studies have demonstrated a statistically significant reduction in NAA concentration in the hippocampus following ECT.[39],[40] The implications of these results are of significant interest to us in answering our titular question. A normal level of NAA following ECT could signify that there is no significant neuronal death or damage following ECT, while a reduction would signal the opposite.

However, a direct comparison between these studies is complicated chiefly due to the different ECT protocols, which has been used in these studies. It must, however, be acknowledged that the three older studies used 1.5 T MRI, whereas the two newer studies used a higher 3 T MRI which offers betters signal-to-noise ratio and hence lesser risk of errors in the measurement of metabolite concentrations. The authors of a study by Njau et al.[39] argue that a change in NAA levels might reflect reversible changes in neural metabolism rather than a permanent change in the number or density of neurons and also that reduced NAA might point to a change in the ratio of mature to immature neurons, which, in fact, might reflect enhanced adult neurogenesis.

Thus, the authors warn that to conclude whether a reduction in NAA concentration is beneficial or harmful would take a simultaneous measurement of cognitive functioning, which was lacking in their study. In 2017, Cano et al. Also demonstrated a significant reduction in NAA/Cr ratio in the hippocampus post ECT.

More significantly, the authors also showed a significant increase in Glx levels in the hippocampus following ECT, which was also associated with an increase in hippocampal volume.[40] To explain these three findings, the authors proposed that ECT produces a neuroinflammatory response in the hippocampus – likely mediated by Glx, which has been known to cause inflammation at higher concentrations, thereby accounting for the increase in hippocampal volume with a reduction in NAA concentration. The cause for the volume increase remains unclear – with the authors speculating that it might be due to neuronal swelling or due to angiogenesis. However, the same study and multiple other past studies [21],[25],[30] have demonstrated that hippocampal volume increase was correlated with clinical improvement following ECT.

Thus, we are led to the hypothesis that the same mechanism which drives clinical improvement with ECT is also responsible for the cognitive impairment following ECT. Whether this is a purely neuroinflammatory response or a neuroplastic response or a neuroinflammatory response leading to some form of neuroplasticity is a critical question, which remains to be answered.[40]Studies which have analyzed NAA concentration change in other brain areas have also produced conflicting results. The ACC is another area which has been studied in some detail utilizing the MRSI technique.

In 2003, Pfleiderer et al. Demonstrated that there was no significant change in the NAA and Cho levels in the ACC following ECT. This would seem to suggest that there was no neurogenesis or membrane turnover in the ACC post ECT.[36] However, this finding was contested by Merkl et al.

In 2011, who demonstrated that NAA levels were significantly reduced in the left ACC in patients with depression and that these levels were significantly elevated following ECT.[37] This again is contested by Njau et al. Who showed that NAA levels are significantly reduced following ECT in the left dorsal ACC.[39] A direct comparison of these three studies is complicated by the different ECT and imaging parameters used and hence, no firm conclusion can be made on this point at this stage. In addition to this, one study had demonstrated increased NAA levels in the amygdala following administration of ECT,[34] with a trend level increase in Cho levels, which again is suggestive of neurogenesis and/or neuroplasticity.

A review of studies on the DLPFC reveals a similarly confusing picture with one study, each showing no change, reduction, and elevation of concentration of NAA following ECT.[35],[37],[39] Here, again, a direct comparison of the three studies is made difficult by the heterogeneous imaging and ECT protocols followed by them.A total of five studies have analyzed the concentration of choline-containing compounds (Cho) in patients undergoing ECT. Conceptually, an increase in Cho signals is indicative of increased membrane turnover, which is postulated to be associated with synaptogenesis, neurogenesis, and maturation of neurons.[31] Of these, two studies measured Cho concentration in the B/L hippocampus, with contrasting results. Ende et al.

In 2000 demonstrated a significant elevation in Cho levels in B/L hippocampus after ECT, while Jorgensen et al. In 2015 failed to replicate the same finding.[33],[38] Cho levels have also been studied in the amygdala, ACC, and the DLPFC. However, none of these studies showed a significant increase or decrease in Cho levels before and after ECT in the respective brain regions studied.

In addition, no significant difference was seen in the pre-ECT Cho levels of patients compared to healthy controls.[34],[36],[37]In review, we must admit that MRSI studies are still at a preliminary stage with significant heterogeneity in ECT protocols, patient population, and regions of the brain studied. At this stage, it is difficult to draw any firm conclusions except to acknowledge the fact that the more recent studies – Njau et al., 2017, Cano, 2017, and Jorgensen et al., 2015 – have shown decrease in NAA concentration and no increase in Cho levels [38],[39],[40] – as opposed to the earlier studies by Ende et al.[33] The view offered by the more recent studies is one of a neuroinflammatory models of action of ECT, probably driving neuroplasticity in the hippocampus. This would offer a mechanistic understanding of both clinical response and the phenomenon of cognitive impairment associated with ECT.

However, this conclusion is based on conjecture, and more work needs to be done in this area. Body Fluid Biochemical Marker Studies Another line of evidence for analyzing the effect of ECT on the human brain is the study of concentration of neurotrophins in the plasma or serum. Neurotrophins are small protein molecules which mediate neuronal survival and development.

The most prominent among these is brain-derived neurotrophic factor (BDNF) which plays an important role in neuronal survival, plasticity, and migration.[50] A neurotrophic theory of mood disorders was suggested which hypothesized that depressive disorders are associated with a decreased expression of BDNF in the limbic structures, resulting in the atrophy of these structures.[51] It was also postulated that antidepressant treatment has a neurotrophic effect which reverses the neuronal cell loss, thereby producing a therapeutic effect. It has been well established that BDNF is decreased in mood disorders.[52] It has also been shown that clinical improvement of depression is associated with increase in BDNF levels.[53] Thus, serum BDNF levels have been tentatively proposed as a biomarker for treatment response in depression. Recent meta-analytic evidence has shown that ECT is associated with significant increase in serum BDNF levels in patients with major depressive disorder.[54] Considering that BDNF is a potent stimulator of neurogenesis, the elevation of serum BDNF levels following ECT lends further credence to the theory that ECT leads to neurogenesis in the hippocampus and other limbic structures, which, in turn, mediates the therapeutic action of ECT.

Cognitive Impairment Studies Cognitive impairment has always been the single-most important side effect associated with ECT.[55] Concerns regarding long-term cognitive impairment surfaced soon after the introduction of ECT and since then has grown to become one of the most controversial aspects of ECT.[56] Anti-ECT groups have frequently pointed out to cognitive impairment following ECT as evidence of ECT causing brain damage.[56] A meta-analysis by Semkovska and McLoughlin in 2010 is one of the most detailed studies which had attempted to settle this long-standing debate.[57] The authors reviewed 84 studies (2981 participants), which had used a combined total of 22 standardized neuropsychological tests assessing various cognitive functions before and after ECT in patients diagnosed with major depressive disorder. The different cognitive domains reviewed included processing speed, attention/working memory, verbal episodic memory, visual episodic memory, spatial problem-solving, executive functioning, and intellectual ability. The authors concluded that administration of ECT for depression is associated with significant cognitive impairment in the first few days after ECT administration.

However, it was also seen that impairment in cognitive functioning resolved within a span of 2 weeks and thereafter, a majority of cognitive domains even showed mild improvement compared to the baseline performance. It was also demonstrated that not a single cognitive domain showed persistence of impairment beyond 15 days after ECT.Memory impairment following ECT can be analyzed broadly under two conceptual schemes – one that classifies memory impairment as objective memory impairment and subjective memory impairment and the other that classifies it as impairment in anterograde memory versus impairment in retrograde memory. Objective memory can be roughly defined as the ability to retrieve stored information and can be measured by various standardized neuropsychological tests.

Subjective memory or meta-memory, on the other hand, refers to the ability to make judgments about one's ability to retrieve stored information.[58] As described previously, it has been conclusively demonstrated that anterograde memory impairment does not persist beyond 2 weeks after ECT.[57] However, one of the major limitations of this meta-analysis was the lack of evidence on retrograde amnesia following ECT. This is particularly unfortunate considering that it is memory impairment – particularly retrograde amnesia which has received the most attention.[59] In addition, reports of catastrophic retrograde amnesia have been repeatedly held up as sensational evidence of the lasting brain damage produced by ECT.[59] Admittedly, studies on retrograde amnesia are fewer and less conclusive than on anterograde amnesia.[60],[61] At present, the results are conflicting, with some studies finding some impairment in retrograde memory – particularly autobiographical retrograde memory up to 6 months after ECT.[62],[63],[64],[65] However, more recent studies have failed to support this finding.[66],[67] While they do demonstrate an impairment in retrograde memory immediately after ECT, it was seen that this deficit returned to pre-ECT levels within a span of 1–2 months and improved beyond baseline performance at 6 months post ECT.[66] Adding to the confusion are numerous factors which confound the assessment of retrograde amnesia. It has been shown that depressive symptoms can produce significant impairment of retrograde memory.[68],[69] It has also been demonstrated that sine-wave ECT produces significantly more impairment of retrograde memory as compared to brief-pulse ECT.[70] However, from the 1990s onward, sine-wave ECT has been completely replaced by brief-pulse ECT, and it is unclear as to the implications of cognitive impairment from the sine-wave era in contemporary ECT practice.Another area of concern are reports of subjective memory impairment following ECT.

One of the pioneers of research into subjective memory impairment were Squire and Chace who published a series of studies in the 1970s demonstrating the adverse effect of bilateral ECT on subjective assessment of memory.[62],[63],[64],[65] However, most of the studies conducted post 1980 – from when sine-wave ECT was replaced by brief-pulse ECT report a general improvement in subjective memory assessments following ECT.[71] In addition, most of the recent studies have failed to find a significant association between measures of subjective and objective memory.[63],[66],[70],[72],[73],[74] It has also been shown that subjective memory impairment is strongly associated with the severity of depressive symptoms.[75] In light of these facts, the validity and value of measures of subjective memory impairment as a marker of cognitive impairment and brain damage following ECT have been questioned. However, concerns regarding subjective memory impairment and catastrophic retrograde amnesia continue to persist, with significant dissonance between the findings of different research groups and patient self-reports in various media.[57]Some studies reported the possibility of ECT being associated with the development of subsequent dementia.[76],[77] However, a recent large, well-controlled prospective Danish study found that the use of ECT was not associated with elevated incidence of dementia.[78] Conclusion Our titular question is whether ECT leads to brain damage, where damage indicates destruction or degeneration of nerves or nerve tracts in the brain, which leads to loss of function. This issue was last addressed by Devanand et al.

In 1994 since which time our understanding of ECT has grown substantially, helped particularly by the advent of modern-day neuroimaging techniques which we have reviewed in detail. And, what these studies reveal is rather than damaging the brain, ECT has a neuromodulatory effect on the brain. The various lines of evidence – structural neuroimaging studies, functional neuroimaging studies, neurochemical and metabolic studies, and serum BDNF studies all point toward this.

These neuromodulatory changes have been localized to the hippocampus, amygdala, and certain other parts of the limbic system. How exactly these changes mediate the improvement of depressive symptoms is a question that remains unanswered. However, there is little by way of evidence from neuroimaging studies which indicates that ECT causes destruction or degeneration of neurons.

Though cognitive impairment studies do show that there is objective impairment of certain functions – particularly memory immediately after ECT, these impairments are transient with full recovery within a span of 2 weeks. Perhaps, the single-most important unaddressed concern is retrograde amnesia, which has been shown to persist for up to 2 months post ECT. In this regard, the recent neurometabolic studies have offered a tentative mechanism of action of ECT, producing a transient inflammation in the limbic cortex, which, in turn, drives neurogenesis, thereby exerting a neuromodulatory effect.

This hypothesis would explain both the cognitive adverse effects of ECT – due to the transient inflammation – and the long-term improvement in mood – neurogenesis in the hippocampus. Although unproven at present, such a hypothesis would imply that cognitive impairment is tied in with the mechanism of action of ECT and not an indicator of damage to the brain produced by ECT.The review of literature suggests that ECT does cause at least structural and functional changes in the brain, and these are in all probability related to the effects of the ECT. However, these cannot be construed as brain damage as is usually understood.

Due to the relative scarcity of data that directly examines the question of whether ECT causes brain damage, it is not possible to conclusively answer this question. However, in light of enduring ECT survivor accounts, there is a need to design studies that specifically answer this question.Financial support and sponsorshipNil.Conflicts of interestThere are no conflicts of interest. References 1.Payne NA, Prudic J.

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J Affect Disord 1996;41:9-15. 70.Weiner RD, Rogers HJ, Davidson JR, Squire LR. Effects of stimulus parameters on cognitive side effects.

Ann N Y Acad Sci 1986;462:315-25. 71.Prudic J, Peyser S, Sackeim HA. Subjective memory complaints.

A review of patient self-assessment of memory after electroconvulsive therapy. J ECT 2000;16:121-32. 72.Sackeim HA, Prudic J, Devanand DP, Kiersky JE, Fitzsimons L, Moody BJ, et al.

Effects of stimulus intensity and electrode placement on the efficacy and cognitive effects of electroconvulsive therapy. N Engl J Med 1993;328:839-46. 73.Frith CD, Stevens M, Johnstone EC, Deakin JF, Lawler P, Crow TJ.

Effects of ECT and depression on various aspects of memory. Br J Psychiatry 1983;142:610-7. 74.Ng C, Schweitzer I, Alexopoulos P, Celi E, Wong L, Tuckwell V, et al.

Efficacy and cognitive effects of right unilateral electroconvulsive therapy. J ECT 2000;16:370-9. 75.Coleman EA, Sackeim HA, Prudic J, Devanand DP, McElhiney MC, Moody BJ.

Subjective memory complaints prior to and following electroconvulsive therapy. Biol Psychiatry 1996;39:346-56. 76.Berggren Š, Gustafson L, Höglund P, Johanson A.

A long-term longitudinal follow-up of depressed patients treated with ECT with special focus on development of dementia. J Affect Disord 2016;200:15-24. 77.Brodaty H, Hickie I, Mason C, Prenter L.

A prospective follow-up study of ECT outcome in older depressed patients. J Affect Disord 2000;60:101-11. 78.Osler M, Rozing MP, Christensen GT, Andersen PK, Jørgensen MB.

Electroconvulsive therapy and risk of dementia in patients with affective disorders. A cohort study. Lancet Psychiatry 2018;5:348-56.

Correspondence Address:Dr. Shubh Mohan SinghDepartment of Psychiatry, Postgraduate Institute of Medical Education and Research, Chandigarh IndiaSource of Support. None, Conflict of Interest.

NoneDOI. 10.4103/psychiatry.IndianJPsychiatry_239_19 Tables [Table 1], [Table 2].

How to cite this article:Singh Go Here O P best online singulair. Aftermath of celebrity suicide – Media coverage and role of psychiatrists. Indian J Psychiatry 2020;62:337-8Celebrity suicide is one best online singulair of the highly publicized events in our country.

Indians got a glimpse of this following an unfortunate incident where a popular Hindi film actor died of suicide. As expected, the media went into a frenzy as newspapers, news channels, and social media were full of stories providing best online singulair minute details of the suicidal act. Some even going as far as highlighting the color of the cloth used in the suicide as well as showing the lifeless body of the actor.

All kinds of personal details were dug up, and speculations and hypotheses became the order of the day in the next few days that followed. In the process, reputations of many people associated with the actor were besmirched and their private and personal details were freely and blatantly broadcast and discussed on electronic, best online singulair print, and social media. We understand that media houses have their own need and duty to report and sensationalize news for increasing their visibility (aka TRP), but such reporting has huge impacts on the mental health of the vulnerable population.The impact of this was soon realized when many incidents of copycat suicide were reported from all over the country within a few days of the incident.

Psychiatrists suddenly best online singulair started getting distress calls from their patients in despair with increased suicidal ideation. This has become a major area of concern for the psychiatry community.The Indian Psychiatric Society has been consistently trying to engage with media to promote ethical reporting of suicide. Section 24 (1) of Mental Health Care Act, 2017, forbids publication of photograph of mentally ill person without his consent.[1] The Press Council of India has adopted the guidelines of World Health Organization report on Preventing Suicide best online singulair.

A resource for media professionals, which came out with an advisory to be followed by media in reporting cases of suicide. It includes points forbidding them from putting stories in prominent positions and unduly repeating them, explicitly describing the method used, providing details about the site/location, using sensational headlines, or using photographs and video footage of the incident.[2] Unfortunately, the advisory seems to have little effect in the aftermath of celebrity suicides. Channels were full of speculations about the person's mental best online singulair condition and illness and also his relationships and finances.

Many fictional accounts of his symptoms and illness were touted, which is not only against the ethics but is also contrary to MHCA, 2017.[1]It went to the extent that the name of his psychiatrist was mentioned and quotes were attributed to him without taking any account from him. The Indian best online singulair Psychiatric Society has written to the Press Council of India underlining this concern and asking for measures to ensure ethics in reporting suicide.While there is a need for engagement with media to make them aware of the grave impact of negative suicide reporting on the lives of many vulnerable persons, there is even a more urgent need for training of psychiatrists regarding the proper way of interaction with media. This has been amply brought out in the aftermath of this incident.

Many psychiatrists and mental health best online singulair professionals were called by media houses to comment on the episode. Many psychiatrists were quoted, or “misquoted,” or “quoted out of context,” commenting on the life of a person whom they had never examined and had no “professional authority” to do so. There were even stories with byline of a psychiatrist where the content provided was not only unscientific but also way beyond the expertise of a psychiatrist.

These types of viewpoints perpetuate stigma, myths, and “misleading concepts” about psychiatry and are detrimental to the image of psychiatry in addition to doing harm and injustice to our best online singulair patients. Hence, the need to formulate a guideline for interaction of psychiatrists with the media is imperative.In the infamous Goldwater episode, 12,356 psychiatrists were asked to cast opinion about the fitness of Barry Goldwater for presidential candidature. Out of 2417 respondents, 1189 psychiatrists reported him to be mentally unfit while none had actually examined him.[3] This led to the formulation best online singulair of “The Goldwater Rule” by the American Psychiatric Association in 1973,[4] but we have witnessed the same phenomenon at the time of presidential candidature of Donald Trump.Psychiatrists should be encouraged to interact with media to provide scientific information about mental illnesses and reduction of stigma, but “statements to the media” can be a double-edged sword, and we should know about the rules of engagements and boundaries of interactions.

Methods and principles of interaction with media should form a part of our training curriculum. Many professional societies have guidelines and resource books for interacting with media, and psychiatrists should familiarize themselves best online singulair with these documents. The Press Council guideline is likely to prompt reporters to seek psychiatrists for their expert opinion.

It is useful for them to have a template ready with suicide rates, emphasizing multicausality of suicide, role of mental disorders, as well as help available.[5]It is about time that the Indian Psychiatric Society formulated its own guidelines laying down the broad principles and boundaries governing the interaction of Indian psychiatrists with the media. Till then, it is desirable to be guided by the following broad principles:It should be assumed that no statement goes “off the record” as the media person is most likely recording the interview, and we should also record best online singulair any such conversation from our endIt should be clarified in which capacity comments are being made – professional, personal, or as a representative of an organizationOne should not comment on any person whom he has not examinedPsychiatrists should take any such opportunity to educate the public about mental health issuesThe comments should be justified and limited by the boundaries of scientific knowledge available at the moment. References Correspondence Address:Dr.

O P SinghAA 304, Ashabari Apartments, O/31, Baishnabghata, Patuli Township, Kolkata best online singulair - 700 094, West Bengal IndiaSource of Support. None, Conflict of Interest. NoneDOI.

10.4103/psychiatry.IndianJPsychiatry_816_20Abstract Electroconvulsive therapy (ECT) is an effective modality of treatment for a variety of psychiatric disorders. However, it has always been accused of being a coercive, unethical, and dangerous modality of treatment. The dangerousness of ECT has been mainly attributed to its claimed ability to cause brain damage.

This narrative review aims to provide an update of the evidence with regard to whether the practice of ECT is associated with damage to the brain. An accepted definition of brain damage remains elusive. There are also ethical and technical problems in designing studies that look at this question specifically.

Thus, even though there are newer technological tools and innovations, any review attempting to answer this question would have to take recourse to indirect methods. These include structural, functional, and metabolic neuroimaging. Body fluid biochemical marker studies.

And follow-up studies of cognitive impairment and incidence of dementia in people who have received ECT among others. The review of literature and present evidence suggests that ECT has a demonstrable impact on the structure and function of the brain. However, there is a lack of evidence at present to suggest that ECT causes brain damage.Keywords.

Adverse effect, brain damage, electroconvulsive therapyHow to cite this article:Jolly AJ, Singh SM. Does electroconvulsive therapy cause brain damage. An update.

Indian J Psychiatry 2020;62:339-53 Introduction Electroconvulsive therapy (ECT) as a modality of treatment for psychiatric disorders has existed at least since 1938.[1] ECT is an effective modality of treatment for various psychiatric disorders. However, from the very beginning, the practice of ECT has also faced resistance from various groups who claim that it is coercive and harmful.[2] While the ethical aspects of the practice of ECT have been dealt with elsewhere, the question of harmfulness or brain damage consequent upon the passage of electric current needs to be examined afresh in light of technological advances and new knowledge.[3]The question whether ECT causes brain damage was reviewed in a holistic fashion by Devanand et al. In the mid-1990s.[4],[5] The authors had attempted to answer this question by reviewing the effect of ECT on the brain in various areas – cognitive side effects, structural neuroimaging studies, neuropathologic studies of patients who had received ECT, autopsy studies of epileptic patients, and finally animal ECS studies.

The authors had concluded that ECT does not produce brain damage.This narrative review aims to update the evidence with regard to whether ECT causes brain damage by reviewing relevant literature from 1994 to the present time. Framing the Question The Oxford Dictionary defines damage as physical harm that impairs the value, usefulness, or normal function of something.[6] Among medical dictionaries, the Peter Collins Dictionary defines damage as harm done to things (noun) or to harm something (verb).[7] Brain damage is defined by the British Medical Association Medical Dictionary as degeneration or death of nerve cells and tracts within the brain that may be localized to a particular area of the brain or diffuse.[8] Going by such a definition, brain damage in the context of ECT should refer to death or degeneration of brain tissue, which results in the impairment of functioning of the brain. The importance of precisely defining brain damage shall become evident subsequently in this review.There are now many more tools available to investigate the structure and function of brain in health and illness.

However, there are obvious ethical issues in designing human studies that are designed to answer this specific question. Therefore, one must necessarily take recourse to indirect evidences available through studies that have been designed to answer other research questions. These studies have employed the following methods:Structural neuroimaging studiesFunctional neuroimaging studiesMetabolic neuroimaging studiesBody fluid biochemical marker studiesCognitive impairment studies.While the early studies tended to focus more on establishing the safety of ECT and finding out whether ECT causes gross microscopic brain damage, the later studies especially since the advent of advanced neuroimaging techniques have been focusing more on a mechanistic understanding of ECT.

Hence, the primary objective of the later neuroimaging studies has been to look for structural and functional brain changes which might explain how ECT acts rather than evidence of gross structural damage per se. However, put together, all these studies would enable us to answer our titular question to some satisfaction. [Table 1] and [Table 2] provide an overview of the evidence base in this area.

Structural and Functional Neuroimaging Studies Devanand et al. Reviewed 16 structural neuroimaging studies on the effect of ECT on the brain.[4] Of these, two were pneumoencephalography studies, nine were computed tomography (CT) scan studies, and five were magnetic resonance imaging (MRI) studies. However, most of these studies were retrospective in design, with neuroimaging being done in patients who had received ECT in the past.

In the absence of baseline neuroimaging, it would be very difficult to attribute any structural brain changes to ECT. In addition, pneumoencephalography, CT scan, and even early 0.3 T MRI provided images with much lower spatial resolution than what is available today. The authors concluded that there was no evidence to show that ECT caused any structural damage to the brain.[4] Since then, at least twenty more MRI-based structural neuroimaging studies have studied the effect of ECT on the brain.

The earliest MRI studies in the early 1990s focused on detecting structural damage following ECT. All of these studies were prospective in design, with the first MRI scan done at baseline and a second MRI scan performed post ECT.[9],[11],[12],[13],[41] While most of the studies imaged the patient once around 24 h after receiving ECT, some studies performed multiple post ECT neuroimaging in the first 24 h after ECT to better capture the acute changes. A single study by Coffey et al.

Followed up the patients for a duration of 6 months and repeated neuroimaging again at 6 months in order to capture any long-term changes following ECT.[10]The most important conclusion which emerged from this early series of studies was that there was no evidence of cortical atrophy, change in ventricle size, or increase in white matter hyperintensities.[4] The next major conclusion was that there appeared to be an increase in the T1 and T2 relaxation time immediately following ECT, which returned to normal within 24 h. This supported the theory that immediately following ECT, there appears to be a temporary breakdown of the blood–brain barrier, leading to water influx into the brain tissue.[11] The last significant observation by Coffey et al. In 1991 was that there was no significant temporal changes in the total volumes of the frontal lobes, temporal lobes, or amygdala–hippocampal complex.[10] This was, however, something which would later be refuted by high-resolution MRI studies.

Nonetheless, one inescapable conclusion of these early studies was that there was no evidence of any gross structural brain changes following administration of ECT. Much later in 2007, Szabo et al. Used diffusion-weighted MRI to image patients in the immediate post ECT period and failed to observe any obvious brain tissue changes following ECT.[17]The next major breakthrough came in 2010 when Nordanskog et al.

Demonstrated that there was a significant increase in the volume of the hippocampus bilaterally following a course of ECT in a cohort of patients with depressive illness.[18] This contradicted the earlier observations by Coffey et al. That there was no volume increase in any part of the brain following ECT.[10] This was quite an exciting finding and was followed by several similar studies. However, the perspective of these studies was quite different from the early studies.

In contrast to the early studies looking for the evidence of ECT-related brain damage, the newer studies were focused more on elucidating the mechanism of action of ECT. Further on in 2014, Nordanskog et al. In a follow-up study showed that though there was a significant increase in the volume of the hippocampus 1 week after a course of ECT, the hippocampal volume returned to the baseline after 6 months.[19] Two other studies in 2013 showed that in addition to the hippocampus, the amygdala also showed significant volume increase following ECT.[20],[21] A series of structural neuroimaging studies after that have expanded on these findings and as of now, gray matter volume increase following ECT has been demonstrated in the hippocampus, amygdala, anterior temporal pole, subgenual cortex,[21] right caudate nucleus, and the whole of the medial temporal lobe (MTL) consisting of the hippocampus, amygdala, insula, and the posterosuperior temporal cortex,[24] para hippocampi, right subgenual anterior cingulate gyrus, and right anterior cingulate gyrus,[25] left cerebellar area VIIa crus I,[29] putamen, caudate nucleus, and nucleus acumbens [31] and clusters of increased cortical thickness involving the temporal pole, middle and superior temporal cortex, insula, and inferior temporal cortex.[27] However, the most consistently reported and replicated finding has been the bilateral increase in the volume of the hippocampus and amygdala.

In light of these findings, it has been tentatively suggested that ECT acts by inducing neuronal regeneration in the hippocampus – amygdala complex.[42],[43] However, there are certain inconsistencies to this hypothesis. Till date, only one study – Nordanskog et al., 2014 – has followed study patients for a long term – 6 months in their case. And significantly, the authors found out that after increasing immediately following ECT, the hippocampal volume returns back to baseline by 6 months.[19] This, however, was not associated with the relapse of depressive symptoms.

Another area of significant confusion has been the correlation of hippocampal volume increase with improvement of depressive symptoms. Though almost all studies demonstrate a significant increase in hippocampal volume following ECT, a majority of studies failed to demonstrate a correlation between symptom improvement and hippocampal volume increase.[19],[20],[22],[24],[28] However, a significant minority of volumetric studies have demonstrated correlation between increase in hippocampal and/or amygdala volume and improvement of symptoms.[21],[25],[30]Another set of studies have used diffusion tensor imaging, functional MRI (fMRI), anatomical connectome, and structural network analysis to study the effect of ECT on the brain. The first of these studies by Abbott et al.

In 2014 demonstrated that on fMRI, the connectivity between right and left hippocampus was significantly reduced in patients with severe depression. It was also shown that the connectivity was normalized following ECT, and symptom improvement was correlated with an increase in connectivity.[22] In a first of its kind DTI study, Lyden et al. In 2014 demonstrated that fractional anisotropy which is a measure of white matter tract or fiber density is increased post ECT in patients with severe depression in the anterior cingulum, forceps minor, and the dorsal aspect of the left superior longitudinal fasciculus.

The authors suggested that ECT acts to normalize major depressive disorder-related abnormalities in the structural connectivity of the dorsal fronto-limbic pathways.[23] Another DTI study in 2015 constructed large-scale anatomical networks of the human brain – connectomes, based on white matter fiber tractography. The authors found significant reorganization in the anatomical connections involving the limbic structure, temporal lobe, and frontal lobe. It was also found that connection changes between amygdala and para hippocampus correlated with reduction in depressive symptoms.[26] In 2016, Wolf et al.

Used a source-based morphometry approach to study the structural networks in patients with depression and schizophrenia and the effect of ECT on the same. It was found that the medial prefrontal cortex/anterior cingulate cortex (ACC/MPFC) network, MTL network, bilateral thalamus, and left cerebellar regions/precuneus exhibited significant difference between healthy controls and the patient population. It was also demonstrated that administration of ECT leads to significant increase in the network strength of the ACC/MPFC network and the MTL network though the increase in network strength and symptom amelioration were not correlated.[32]Building on these studies, a recently published meta-analysis has attempted a quantitative synthesis of brain volume changes – focusing on hippocampal volume increase following ECT in patients with major depressive disorder and bipolar disorder.

The authors initially selected 32 original articles from which six articles met the criteria for quantitative synthesis. The results showed significant increase in the volume of the right and left hippocampus following ECT. For the rest of the brain regions, the heterogeneity in protocols and imaging techniques did not permit a quantitative analysis, and the authors have resorted to a narrative review similar to the present one with similar conclusions.[44] Focusing exclusively on hippocampal volume change in ECT, Oltedal et al.

In 2018 conducted a mega-analysis of 281 patients with major depressive disorder treated with ECT enrolled at ten different global sites of the Global ECT-MRI Research Collaboration.[45] Similar to previous studies, there was a significant increase in hippocampal volume bilaterally with a dose–response relationship with the number of ECTs administered. Furthermore, bilateral (B/L) ECT was associated with an equal increase in volume in both right and left hippocampus, whereas right unilateral ECT was associated with greater volume increase in the right hippocampus. Finally, contrary to expectation, clinical improvement was found to be negatively correlated with hippocampal volume.Thus, a review of the current evidence amply demonstrates that from looking for ECT-related brain damage – and finding none, we have now moved ahead to looking for a mechanistic understanding of the effect of ECT.

In this regard, it has been found that ECT does induce structural changes in the brain – a fact which has been seized upon by some to claim that ECT causes brain damage.[46] Such statements should, however, be weighed against the definition of damage as understood by the scientific medical community and patient population. Neuroanatomical changes associated with effective ECT can be better described as ECT-induced brain neuroplasticity or ECT-induced brain neuromodulation rather than ECT-induced brain damage. Metabolic Neuroimaging Studies.

Magnetic Resonance Spectroscopic Imaging Magnetic resonance spectroscopic imaging (MRSI) uses a phase-encoding procedure to map the spatial distribution of magnetic resonance (MR) signals of different molecules. The crucial difference, however, is that while MRI maps the MR signals of water molecules, MRSI maps the MR signals generated by different metabolites – such as N-acetyl aspartate (NAA) and choline-containing compounds. However, the concentration of these metabolites is at least 10,000 times lower than water molecules and hence the signal strength generated would also be correspondingly lower.

However, MRSI offers us the unique advantage of studying in vivo the change in the concentration of brain metabolites, which has been of great significance in fields such as psychiatry, neurology, and basic neuroscience research.[47]MRSI studies on ECT in patients with depression have focused largely on four metabolites in the human brain – NAA, choline-containing compounds (Cho) which include majorly cell membrane compounds such as glycerophosphocholine, phosphocholine and a miniscule contribution from acetylcholine, creatinine (Cr) and glutamine and glutamate together (Glx). NAA is located exclusively in the neurons, and is suggested to be a marker of neuronal viability and functionality.[48] Choline-containing compounds (Cho) mainly include the membrane compounds, and an increase in Cho would be suggestive of increased membrane turnover. Cr serves as a marker of cellular energy metabolism, and its levels are usually expected to remain stable.

The regions which have been most widely studied in MRSI studies include the bilateral hippocampus and amygdala, dorsolateral prefrontal cortex (DLPFC), and ACC.Till date, five MRSI studies have measured NAA concentration in the hippocampus before and after ECT. Of these, three studies showed that there is no significant change in the NAA concentration in the hippocampus following ECT.[33],[38],[49] On the other hand, two recent studies have demonstrated a statistically significant reduction in NAA concentration in the hippocampus following ECT.[39],[40] The implications of these results are of significant interest to us in answering our titular question. A normal level of NAA following ECT could signify that there is no significant neuronal death or damage following ECT, while a reduction would signal the opposite.

However, a direct comparison between these studies is complicated chiefly due to the different ECT protocols, which has been used in these studies. It must, however, be acknowledged that the three older studies used 1.5 T MRI, whereas the two newer studies used a higher 3 T MRI which offers betters signal-to-noise ratio and hence lesser risk of errors in the measurement of metabolite concentrations. The authors of a study by Njau et al.[39] argue that a change in NAA levels might reflect reversible changes in neural metabolism rather than a permanent change in the number or density of neurons and also that reduced NAA might point to a change in the ratio of mature to immature neurons, which, in fact, might reflect enhanced adult neurogenesis.

Thus, the authors warn that to conclude whether a reduction in NAA concentration is beneficial or harmful would take a simultaneous measurement of cognitive functioning, which was lacking in their study. In 2017, Cano et al. Also demonstrated a significant reduction in NAA/Cr ratio in the hippocampus post ECT.

More significantly, the authors also showed a significant increase in Glx levels in the hippocampus following ECT, which was also associated with an increase in hippocampal volume.[40] To explain these three findings, the authors proposed that ECT produces a neuroinflammatory response in the hippocampus – likely mediated by Glx, which has been known to cause inflammation at higher concentrations, thereby accounting for the increase in hippocampal volume with a reduction in NAA concentration. The cause for the volume increase remains unclear – with the authors speculating that it might be due to neuronal swelling or due to angiogenesis. However, the same study and multiple other past studies [21],[25],[30] have demonstrated that hippocampal volume increase was correlated with clinical improvement following ECT.

Thus, we are led to the hypothesis that the same mechanism which drives clinical improvement with ECT is also responsible for the cognitive impairment following ECT. Whether this is a purely neuroinflammatory response or a neuroplastic response or a neuroinflammatory response leading to some form of neuroplasticity is a critical question, which remains to be answered.[40]Studies which have analyzed NAA concentration change in other brain areas have also produced conflicting results. The ACC is another area which has been studied in some detail utilizing the MRSI technique.

In 2003, Pfleiderer et al. Demonstrated that there was no significant change in the NAA and Cho levels in the ACC following ECT. This would seem to suggest that there was no neurogenesis or membrane turnover in the ACC post ECT.[36] However, this finding was contested by Merkl et al.

In 2011, who demonstrated that NAA levels were significantly reduced in the left ACC in patients with depression and that these levels were significantly elevated following ECT.[37] This again is contested by Njau et al. Who showed that NAA levels are significantly reduced following ECT in the left dorsal ACC.[39] A direct comparison of these three studies is complicated by the different ECT and imaging parameters used and hence, no firm conclusion can be made on this point at this stage. In addition to this, one study had demonstrated increased NAA levels in the amygdala following administration of ECT,[34] with a trend level increase in Cho levels, which again is suggestive of neurogenesis and/or neuroplasticity.

A review of studies on the DLPFC reveals a similarly confusing picture with one study, each showing no change, reduction, and elevation of concentration of NAA following ECT.[35],[37],[39] Here, again, a direct comparison of the three studies is made difficult by the heterogeneous imaging and ECT protocols followed by them.A total of five studies have analyzed the concentration of choline-containing compounds (Cho) in patients undergoing ECT. Conceptually, an increase in Cho signals is indicative of increased membrane turnover, which is postulated to be associated with synaptogenesis, neurogenesis, and maturation of neurons.[31] Of these, two studies measured Cho concentration in the B/L hippocampus, with contrasting results. Ende et al.

In 2000 demonstrated a significant elevation in Cho levels in B/L hippocampus after ECT, while Jorgensen et al. In 2015 failed to replicate the same finding.[33],[38] Cho levels have also been studied in the amygdala, ACC, and the DLPFC. However, none of these studies showed a significant increase or decrease in Cho levels before and after ECT in the respective brain regions studied.

In addition, no significant difference was seen in the pre-ECT Cho levels of patients compared to healthy controls.[34],[36],[37]In review, we must admit that MRSI studies are still at a preliminary stage with significant heterogeneity in ECT protocols, patient population, and regions of the brain studied. At this stage, it is difficult to draw any firm conclusions except to acknowledge the fact that the more recent studies – Njau et al., 2017, Cano, 2017, and Jorgensen et al., 2015 – have shown decrease in NAA concentration and no increase in Cho levels [38],[39],[40] – as opposed to the earlier studies by Ende et al.[33] The view offered by the more recent studies is one of a neuroinflammatory models of action of ECT, probably driving neuroplasticity in the hippocampus. This would offer a mechanistic understanding of both clinical response and the phenomenon of cognitive impairment associated with ECT.

However, this conclusion is based on conjecture, and more work needs to be done in this area. Body Fluid Biochemical Marker Studies Another line of evidence for analyzing the effect of ECT on the human brain is the study of concentration of neurotrophins in the plasma or serum. Neurotrophins are small protein molecules which mediate neuronal survival and development.

The most prominent among these is brain-derived neurotrophic factor (BDNF) which plays an important role in neuronal survival, plasticity, and migration.[50] A neurotrophic theory of mood disorders was suggested which hypothesized that depressive disorders are associated with a decreased expression of BDNF in the limbic structures, resulting in the atrophy of these structures.[51] It was also postulated that antidepressant treatment has a neurotrophic effect which reverses the neuronal cell loss, thereby producing a therapeutic effect. It has been well established that BDNF is decreased in mood disorders.[52] It has also been shown that clinical improvement of depression is associated with increase in BDNF levels.[53] Thus, serum BDNF levels have been tentatively proposed as a biomarker for treatment response in depression. Recent meta-analytic evidence has shown that ECT is associated with significant increase in serum BDNF levels in patients with major depressive disorder.[54] Considering that BDNF is a potent stimulator of neurogenesis, the elevation of serum BDNF levels following ECT lends further credence to the theory that ECT leads to neurogenesis in the hippocampus and other limbic structures, which, in turn, mediates the therapeutic action of ECT.

Cognitive Impairment Studies Cognitive impairment has always been the single-most important side effect associated with ECT.[55] Concerns regarding long-term cognitive impairment surfaced soon after the introduction of ECT and since then has grown to become one of the most controversial aspects of ECT.[56] Anti-ECT groups have frequently pointed out to cognitive impairment following ECT as evidence of ECT causing brain damage.[56] A meta-analysis by Semkovska and McLoughlin in 2010 is one of the most detailed studies which had attempted to settle this long-standing debate.[57] The authors reviewed 84 studies (2981 participants), which had used a combined total of 22 standardized neuropsychological tests assessing various cognitive functions before and after ECT in patients diagnosed with major depressive disorder. The different cognitive domains reviewed included processing speed, attention/working memory, verbal episodic memory, visual episodic memory, spatial problem-solving, executive functioning, and intellectual ability. The authors concluded that administration of ECT for depression is associated with significant cognitive impairment in the first few days after ECT administration.

However, it was also seen that impairment in cognitive functioning resolved within a span of 2 weeks and thereafter, a majority of cognitive domains even showed mild improvement compared to the baseline performance. It was also demonstrated that not a single cognitive domain showed persistence of impairment beyond 15 days after ECT.Memory impairment following ECT can be analyzed broadly under two conceptual schemes – one that classifies memory impairment as objective memory impairment and subjective memory impairment and the other that classifies it as impairment in anterograde memory versus impairment in retrograde memory. Objective memory can be roughly defined as the ability to retrieve stored information and can be measured by various standardized neuropsychological tests.

Subjective memory or meta-memory, on the other hand, refers to the ability to make judgments about one's ability to retrieve stored information.[58] As described previously, it has been conclusively demonstrated that anterograde memory impairment does not persist beyond 2 weeks after ECT.[57] However, one of the major limitations of this meta-analysis was the lack of evidence on retrograde amnesia following ECT. This is particularly unfortunate considering that it is memory impairment – particularly retrograde amnesia which has received the most attention.[59] In addition, reports of catastrophic retrograde amnesia have been repeatedly held up as sensational evidence of the lasting brain damage produced by ECT.[59] Admittedly, studies on retrograde amnesia are fewer and less conclusive than on anterograde amnesia.[60],[61] At present, the results are conflicting, with some studies finding some impairment in retrograde memory – particularly autobiographical retrograde memory up to 6 months after ECT.[62],[63],[64],[65] However, more recent studies have failed to support this finding.[66],[67] While they do demonstrate an impairment in retrograde memory immediately after ECT, it was seen that this deficit returned to pre-ECT levels within a span of 1–2 months and improved beyond baseline performance at 6 months post ECT.[66] Adding to the confusion are numerous factors which confound the assessment of retrograde amnesia. It has been shown that depressive symptoms can produce significant impairment of retrograde memory.[68],[69] It has also been demonstrated that sine-wave ECT produces significantly more impairment of retrograde memory as compared to brief-pulse ECT.[70] However, from the 1990s onward, sine-wave ECT has been completely replaced by brief-pulse ECT, and it is unclear as to the implications of cognitive impairment from the sine-wave era in contemporary ECT practice.Another area of concern are reports of subjective memory impairment following ECT.

One of the pioneers of research into subjective memory impairment were Squire and Chace who published a series of studies in the 1970s demonstrating the adverse effect of bilateral ECT on subjective assessment of memory.[62],[63],[64],[65] However, most of the studies conducted post 1980 – from when sine-wave ECT was replaced by brief-pulse ECT report a general improvement in subjective memory assessments following ECT.[71] In addition, most of the recent studies have failed to find a significant association between measures of subjective and objective memory.[63],[66],[70],[72],[73],[74] It has also been shown that subjective memory impairment is strongly associated with the severity of depressive symptoms.[75] In light of these facts, the validity and value of measures of subjective memory impairment as a marker of cognitive impairment and brain damage following ECT have been questioned. However, concerns regarding subjective memory impairment and catastrophic retrograde amnesia continue to persist, with significant dissonance between the findings of different research groups and patient self-reports in various media.[57]Some studies reported the possibility of ECT being associated with the development of subsequent dementia.[76],[77] However, a recent large, well-controlled prospective Danish study found that the use of ECT was not associated with elevated incidence of dementia.[78] Conclusion Our titular question is whether ECT leads to brain damage, where damage indicates destruction or degeneration of nerves or nerve tracts in the brain, which leads to loss of function. This issue was last addressed by Devanand et al.

In 1994 since which time our understanding of ECT has grown substantially, helped particularly by the advent of modern-day neuroimaging techniques which we have reviewed in detail. And, what these studies reveal is rather than damaging the brain, ECT has a neuromodulatory effect on the brain. The various lines of evidence – structural neuroimaging studies, functional neuroimaging studies, neurochemical and metabolic studies, and serum BDNF studies all point toward this.

These neuromodulatory changes have been localized to the hippocampus, amygdala, and certain other parts of the limbic system. How exactly these changes mediate the improvement of depressive symptoms is a question that remains unanswered. However, there is little by way of evidence from neuroimaging studies which indicates that ECT causes destruction or degeneration of neurons.

Though cognitive impairment studies do show that there is objective impairment of certain functions – particularly memory immediately after ECT, these impairments are transient with full recovery within a span of 2 weeks. Perhaps, the single-most important unaddressed concern is retrograde amnesia, which has been shown to persist for up to 2 months post ECT. In this regard, the recent neurometabolic studies have offered a tentative mechanism of action of ECT, producing a transient inflammation in the limbic cortex, which, in turn, drives neurogenesis, thereby exerting a neuromodulatory effect.

This hypothesis would explain both the cognitive adverse effects of ECT – due to the transient inflammation – and the long-term improvement in mood – neurogenesis in the hippocampus. Although unproven at present, such a hypothesis would imply that cognitive impairment is tied in with the mechanism of action of ECT and not an indicator of damage to the brain produced by ECT.The review of literature suggests that ECT does cause at least structural and functional changes in the brain, and these are in all probability related to the effects of the ECT. However, these cannot be construed as brain damage as is usually understood.

Due to the relative scarcity of data that directly examines the question of whether ECT causes brain damage, it is not possible to conclusively answer this question. However, in light of enduring ECT survivor accounts, there is a need to design studies that specifically answer this question.Financial support and sponsorshipNil.Conflicts of interestThere are no conflicts of interest. References 1.Payne NA, Prudic J.

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Correspondence Address:Dr. Shubh Mohan SinghDepartment of Psychiatry, Postgraduate Institute of Medical Education and Research, Chandigarh IndiaSource of Support. None, Conflict of Interest.

NoneDOI. 10.4103/psychiatry.IndianJPsychiatry_239_19 Tables [Table 1], [Table 2].

Singulair and pregnancy

Patients Figure singulair and pregnancy 1. Figure 1 singulair and pregnancy. Enrollment and Randomization. Of the 1107 patients singulair and pregnancy who were assessed for eligibility, 1063 underwent randomization.

541 were assigned to the remdesivir group and 522 to the placebo group (Figure 1). Of those assigned to receive remdesivir, 531 patients (98.2%) received the treatment as singulair and pregnancy assigned. Forty-nine patients had remdesivir treatment discontinued before day 10 because of an adverse event or a serious adverse event other than death (36 patients) or because the patient withdrew consent (13). Of those assigned to receive singulair and pregnancy placebo, 518 patients (99.2%) received placebo as assigned.

Fifty-three patients discontinued placebo before day 10 because of an adverse event or a serious adverse event other than death (36 patients), because the patient withdrew consent (15), or because the patient was found to be ineligible for trial enrollment (2). As of April 28, 2020, a total of 391 patients in the remdesivir group singulair and pregnancy and 340 in the placebo group had completed the trial through day 29, recovered, or died. Eight patients who received remdesivir and 9 who received placebo terminated their participation in the trial before day 29. There were singulair and pregnancy 132 patients in the remdesivir group and 169 in the placebo group who had not recovered and had not completed the day 29 follow-up visit.

The analysis population included 1059 patients for whom we have at least some postbaseline data available (538 in the remdesivir group and 521 in the placebo group). Four of the 1063 patients were not included in the primary analysis because no postbaseline data were available at the time of the singulair and pregnancy database freeze. Table 1. Table 1 singulair and pregnancy.

Demographic and Clinical Characteristics at Baseline. The mean age of patients was 58.9 singulair and pregnancy years, and 64.3% were male (Table 1). On the basis of the evolving epidemiology of Covid-19 during the trial, 79.8% of patients were enrolled at sites in North America, 15.3% in Europe, and 4.9% in Asia (Table S1). Overall, 53.2% of the patients were white, singulair and pregnancy 20.6% were black, 12.6% were Asian, and 13.6% were designated as other or not reported.

249 (23.4%) were Hispanic or Latino. Most patients had either one (27.0%) or two or more (52.1%) of the prespecified coexisting conditions at enrollment, most commonly hypertension (49.6%), obesity (37.0%), singulair and pregnancy and type 2 diabetes mellitus (29.7%). The median singulair and pregnancy number of days between symptom onset and randomization was 9 (interquartile range, 6 to 12). Nine hundred forty-three (88.7%) patients had severe disease at enrollment as defined in the Supplementary Appendix.

272 (25.6%) patients met category 7 criteria on the singulair and pregnancy ordinal scale, 197 (18.5%) category 6, 421 (39.6%) category 5, and 127 (11.9%) category 4. There were 46 (4.3%) patients who had missing ordinal scale data at enrollment. No substantial imbalances in baseline characteristics singulair and pregnancy were observed between the remdesivir group and the placebo group. Primary Outcome Figure 2.

Figure 2 singulair and pregnancy. Kaplan–Meier Estimates of Cumulative Recoveries. Cumulative recovery estimates singulair and pregnancy are shown in the overall population (Panel A), in patients with a baseline score of 4 on the ordinal scale (not receiving oxygen. Panel B), in those with a baseline score of 5 (receiving oxygen.

Panel C), in those singulair and pregnancy with a baseline score of 6 (receiving high-flow oxygen or noninvasive mechanical ventilation. Panel D), and in those with a baseline score of 7 (receiving mechanical ventilation or ECMO. Panel E) singulair and pregnancy. Table 2.

Table 2 singulair and pregnancy. Outcomes Overall and According to Score on the Ordinal Scale in the Intention-to-Treat Population. Figure singulair and pregnancy 3. Figure 3.

Time to singulair and pregnancy Recovery According to Subgroup. The widths of the confidence intervals have not been adjusted for multiplicity and therefore cannot be used to infer treatment effects. Race and ethnic group were reported by the patients singulair and pregnancy. Patients in the remdesivir group had a shorter time to singulair and pregnancy recovery than patients in the placebo group (median, 11 days, as compared with 15 days.

Rate ratio for recovery, 1.32. 95% confidence interval [CI], 1.12 to singulair and pregnancy 1.55. P<0.001. 1059 patients singulair and pregnancy (Figure 2 and Table 2).

Among patients with a baseline ordinal score of 5 (421 patients), the rate ratio for recovery was 1.47 (95% CI, 1.17 to 1.84). Among patients with a baseline score of 4 (127 patients) and those with singulair and pregnancy a baseline score of 6 (197 patients), the rate ratio estimates for recovery were 1.38 (95% CI, 0.94 to 2.03) and 1.20 (95% CI, 0.79 to 1.81), respectively. For those receiving mechanical ventilation or ECMO at enrollment (baseline ordinal scores of 7. 272 patients), the rate ratio for recovery was 0.95 (95% CI, 0.64 to 1.42) singulair and pregnancy.

A test of interaction of treatment with baseline score on the ordinal scale was not significant. An analysis adjusting singulair and pregnancy for baseline ordinal score as a stratification variable was conducted to evaluate the overall effect (of the percentage of patients in each ordinal score category at baseline) on the primary outcome. This adjusted analysis produced a similar treatment-effect estimate (rate ratio for recovery, 1.31. 95% CI, 1.12 to 1.54 singulair and pregnancy.

1017 patients). Table S2 in the Supplementary Appendix shows results according to singulair and pregnancy the baseline severity stratum of mild-to-moderate as compared with severe. Patients who underwent randomization during the first 10 days after the onset of symptoms had a rate ratio for recovery of 1.28 (95% CI, 1.05 to 1.57. 664 patients), whereas patients who underwent randomization more than 10 days after singulair and pregnancy the onset of symptoms had a rate ratio for recovery of 1.38 (95% CI, 1.05 to 1.81.

380 patients) (Figure 3). Key Secondary Outcome The odds of improvement in the ordinal scale score were higher in the remdesivir group, as determined by a proportional singulair and pregnancy odds model at the day 15 visit, than in the placebo group (odds ratio for improvement, 1.50. 95% CI, 1.18 to singulair and pregnancy 1.91. P=0.001.

844 patients) singulair and pregnancy (Table 2 and Fig. S5). Mortality was numerically singulair and pregnancy lower in the remdesivir group than in the placebo group, but the difference was not significant (hazard ratio for death, 0.70. 95% CI, 0.47 to 1.04.

1059 patients) singulair and pregnancy. The Kaplan–Meier estimates of mortality by 14 days were 7.1% and 11.9% in the remdesivir and placebo groups, respectively (Table 2). The Kaplan–Meier estimates of mortality by 28 days singulair and pregnancy are not reported in this preliminary analysis, given the large number of patients that had yet to complete day 29 visits. An analysis with adjustment for baseline ordinal score as a stratification variable showed a hazard ratio for death of 0.74 (95% CI, 0.50 to 1.10).

Safety Outcomes Serious adverse events occurred in 114 patients (21.1%) in the singulair and pregnancy remdesivir group and 141 patients (27.0%) in the placebo group (Table S3). 4 events (2 in each group) were judged by site investigators to be related to remdesivir or placebo. There were 28 serious respiratory failure adverse events in the remdesivir group (5.2% of patients) and 42 in singulair and pregnancy the placebo group (8.0% of patients). Acute respiratory failure, hypotension, viral pneumonia, and acute kidney injury were slightly more common among patients in the placebo group.

No deaths were considered to be related to treatment assignment, as singulair and pregnancy judged by the site investigators. Grade 3 or 4 adverse events occurred in 156 patients (28.8%) in the remdesivir group and in 172 in the placebo group (33.0%) (Table S4). The most common adverse events in the remdesivir group were anemia or decreased hemoglobin (43 events [7.9%], as compared with 47 [9.0%] in singulair and pregnancy the placebo group). Acute kidney injury, decreased estimated glomerular filtration rate or creatinine clearance, or increased blood creatinine (40 events [7.4%], as compared with 38 [7.3%]).

Pyrexia (27 events [5.0%], singulair and pregnancy as compared with 17 [3.3%]). Hyperglycemia or increased blood glucose level (22 events [4.1%], as compared with 17 [3.3%]). And increased aminotransferase levels including alanine aminotransferase, aspartate aminotransferase, singulair and pregnancy or both (22 events [4.1%], as compared with 31 [5.9%]). Otherwise, the incidence of adverse events was not found to be significantly different between the remdesivir group and the placebo group..

Patients Figure https://www.voiture-et-handicap.fr/singulair-price-at-walmart/ 1 best online singulair. Figure 1 best online singulair. Enrollment and Randomization. Of the best online singulair 1107 patients who were assessed for eligibility, 1063 underwent randomization.

541 were assigned to the remdesivir group and 522 to the placebo group (Figure 1). Of those assigned to receive remdesivir, 531 patients (98.2%) best online singulair received the treatment as assigned. Forty-nine patients had remdesivir treatment discontinued before day 10 because of an adverse event or a serious adverse event other than death (36 patients) or because the patient withdrew consent (13). Of those assigned to best online singulair receive placebo, 518 patients (99.2%) received placebo as assigned.

Fifty-three patients discontinued placebo before day 10 because of an adverse event or a serious adverse event other than death (36 patients), because the patient withdrew consent (15), or because the patient was found to be ineligible for trial enrollment (2). As of April 28, 2020, a best online singulair total of 391 patients in the remdesivir group and 340 in the placebo group had completed the trial through day 29, recovered, or died. Eight patients who received remdesivir and 9 who received placebo terminated their participation in the trial before day 29. There were 132 patients in the remdesivir group and 169 in the placebo group who had not recovered and had not completed the day 29 follow-up best online singulair visit.

The analysis population included 1059 patients for whom we have at least some postbaseline data available (538 in the remdesivir group and 521 in the placebo group). Four of the 1063 patients were not included in the primary analysis because no postbaseline data were available at the time of the best online singulair database freeze. Table 1. Table 1 best online singulair.

Demographic and Clinical Characteristics at Baseline. The mean age of patients was 58.9 years, and 64.3% were male (Table 1) best online singulair. On the basis of the evolving epidemiology of Covid-19 during the trial, 79.8% of patients were enrolled at sites in North America, 15.3% in Europe, and 4.9% in Asia (Table S1). Overall, 53.2% best online singulair of the patients were white, 20.6% were black, 12.6% were Asian, and 13.6% were designated as other or not reported.

249 (23.4%) were Hispanic or Latino. Most patients best online singulair had either one (27.0%) or two or more (52.1%) of the prespecified coexisting conditions at enrollment, most commonly hypertension (49.6%), obesity (37.0%), and type 2 diabetes mellitus (29.7%). The median number of days between symptom best online singulair onset and randomization was 9 (interquartile range, 6 to 12). Nine hundred forty-three (88.7%) patients had severe disease at enrollment as defined in the Supplementary Appendix.

272 (25.6%) patients met category 7 criteria on the ordinal scale, 197 (18.5%) category 6, 421 (39.6%) category 5, and 127 best online singulair (11.9%) category 4. There were 46 (4.3%) patients who had missing ordinal scale data at enrollment. No substantial imbalances best online singulair in baseline characteristics were observed between the remdesivir group and the placebo group. Primary Outcome Figure 2.

Figure 2 best online singulair. Kaplan–Meier Estimates of Cumulative Recoveries. Cumulative recovery estimates are shown in the overall population (Panel A), in patients with a baseline score of 4 on the ordinal scale (not receiving oxygen best online singulair. Panel B), in those with a baseline score of 5 (receiving oxygen.

Panel C), in those with a baseline score of 6 (receiving high-flow oxygen or noninvasive mechanical ventilation best online singulair. Panel D), and in those with a baseline score of 7 (receiving mechanical ventilation or ECMO. Panel E) best online singulair. Table 2.

Table 2 best online singulair. Outcomes Overall and According to Score on the Ordinal Scale in the Intention-to-Treat Population. Figure best online singulair 3. Figure 3.

Time to Recovery According to Subgroup best online singulair. The widths of the confidence intervals have not been adjusted for multiplicity and therefore cannot be used to infer treatment effects. Race and ethnic group best online singulair were singulair best buy reported by the patients. Patients in the remdesivir group had a shorter time to recovery than patients in the best online singulair placebo group (median, 11 days, as compared with 15 days.

Rate ratio for recovery, 1.32. 95% confidence best online singulair interval [CI], 1.12 to 1.55. P<0.001. 1059 patients (Figure 2 best online singulair and Table 2).

Among patients with a baseline ordinal score of 5 (421 patients), the rate ratio for recovery was 1.47 (95% CI, 1.17 to 1.84). Among patients with a baseline score of 4 (127 patients) and those with a baseline score of 6 (197 patients), the rate ratio estimates for recovery were 1.38 (95% best online singulair CI, 0.94 to 2.03) and 1.20 (95% CI, 0.79 to 1.81), respectively. For those receiving mechanical ventilation or ECMO at enrollment (baseline ordinal scores of 7. 272 patients), the rate best online singulair ratio for recovery was 0.95 (95% CI, 0.64 to 1.42).

A test of interaction of treatment with baseline score on the ordinal scale was not significant. An analysis adjusting for baseline ordinal score as a stratification variable was conducted to evaluate the best online singulair overall effect (of the percentage of patients in each ordinal score category at baseline) on the primary outcome. This adjusted analysis produced a similar treatment-effect estimate (rate ratio for recovery, 1.31. 95% CI, 1.12 best online singulair to 1.54.

1017 patients). Table S2 best online singulair in the Supplementary Appendix shows results according to the baseline severity stratum of mild-to-moderate as compared with severe. Patients who underwent randomization during the first 10 days after the onset of symptoms had a rate ratio for recovery of 1.28 (95% CI, 1.05 to 1.57. 664 patients), whereas patients who underwent randomization more than 10 days after the onset of symptoms had a best online singulair rate ratio for recovery of 1.38 (95% CI, 1.05 to 1.81.

380 patients) (Figure 3). Key Secondary Outcome The odds of improvement in the ordinal scale score were higher in the remdesivir group, as best online singulair determined by a proportional odds model at the day 15 visit, than in the placebo group (odds ratio for improvement, 1.50. 95% CI, best online singulair 1.18 to 1.91. P=0.001.

844 patients) best online singulair (Table 2 and Fig. S5). Mortality was numerically lower in the remdesivir group than in the placebo best online singulair group, but the difference was not significant (hazard ratio for death, 0.70. 95% CI, 0.47 to 1.04.

1059 patients) best online singulair. The Kaplan–Meier estimates of mortality by 14 days were 7.1% and 11.9% in the remdesivir and placebo groups, respectively (Table 2). The Kaplan–Meier estimates of mortality by 28 days best online singulair are not reported in this preliminary analysis, given the large number of patients that had yet to complete day 29 visits. An analysis with adjustment for baseline ordinal score as a stratification variable showed a hazard ratio for death of 0.74 (95% CI, 0.50 to 1.10).

Safety Outcomes Serious adverse events occurred in 114 patients (21.1%) in the remdesivir group and 141 patients (27.0%) in the placebo group (Table best online singulair S3). 4 events (2 in each group) were judged by site investigators to be related to remdesivir or placebo. There were 28 serious best online singulair respiratory failure adverse events in the remdesivir group (5.2% of patients) and 42 in the placebo group (8.0% of patients). Acute respiratory failure, hypotension, viral pneumonia, and acute kidney injury were slightly more common among patients in the placebo group.

No deaths were considered to be related to treatment assignment, as best online singulair judged by the site investigators. Grade 3 or 4 adverse events occurred in 156 patients (28.8%) in the remdesivir group and in 172 in the placebo group (33.0%) (Table S4). The most common adverse events in the remdesivir group were anemia or decreased hemoglobin (43 events [7.9%], as compared with 47 [9.0%] in best online singulair the placebo group). Acute kidney injury, decreased estimated glomerular filtration rate or creatinine clearance, or increased blood creatinine (40 events [7.4%], as compared with 38 [7.3%]).

Pyrexia (27 best online singulair events [5.0%], as compared with 17 [3.3%]). Hyperglycemia or increased blood glucose level (22 events [4.1%], as compared with 17 [3.3%]). And increased aminotransferase levels including alanine aminotransferase, aspartate aminotransferase, or both (22 events [4.1%], as compared with 31 [5.9%]). Otherwise, the incidence of adverse events was not found to be significantly different between the remdesivir group and the placebo group..

Singulair purpose

NCHS Data singulair purpose https://www.voiture-et-handicap.fr/price-of-singulair-without-insurance/ Brief No. 286, September 2017PDF Versionpdf icon (374 KB)Anjel Vahratian, Ph.D.Key findingsData from the National Health Interview Survey, 2015Among those aged 40–59, perimenopausal women (56.0%) were more likely than postmenopausal (40.5%) and premenopausal (32.5%) women to sleep less than 7 hours, on average, in a 24-hour period.Postmenopausal women aged 40–59 were more likely than premenopausal women aged 40–59 to have trouble falling asleep (27.1% compared with 16.8%, respectively), and staying asleep (35.9% compared with 23.7%), four times or more in the past week.Postmenopausal women aged 40–59 (55.1%) were more likely than premenopausal women aged 40–59 (47.0%) to not wake up feeling well rested 4 days or more in the past week.Sleep duration and quality are important contributors to health and wellness. Insufficient sleep is associated singulair purpose with an increased risk for chronic conditions such as cardiovascular disease (1) and diabetes (2). Women may be particularly vulnerable to sleep problems during times of reproductive hormonal change, such as after the menopausal transition. Menopause is “the permanent cessation of menstruation that occurs after the loss of ovarian activity” (3) singulair purpose.

This data brief describes sleep duration and sleep quality among nonpregnant women aged 40–59 by menopausal status. The age range selected for this analysis reflects the focus on midlife sleep health. In this singulair purpose analysis, 74.2% of women are premenopausal, 3.7% are perimenopausal, and 22.1% are postmenopausal. Keywords. Insufficient sleep, menopause, National Health Interview Survey Perimenopausal women were more likely than premenopausal and postmenopausal women to sleep less than 7 hours, on average, in a 24-hour period.More than one in three nonpregnant women singulair purpose aged 40–59 slept less than 7 hours, on average, in a 24-hour period (35.1%) (Figure 1).

Perimenopausal women were most likely to sleep less than 7 hours, on average, in a 24-hour period (56.0%), compared with 32.5% of premenopausal and 40.5% of postmenopausal women. Postmenopausal women were significantly more likely than premenopausal women to sleep less than 7 hours, on average, in a 24-hour period. Figure 1 singulair purpose. Percentage of nonpregnant women aged 40–59 who slept less than 7 hours, on average, in a 24-hour period, by menopausal status. United States, 2015image icon1Significant quadratic singulair purpose trend by menopausal status (p <.

0.05).NOTES. Women were postmenopausal if they had gone without a menstrual cycle for more than 1 year or were in surgical menopause after the removal of their ovaries. Women were perimenopausal if they no longer had a menstrual cycle and their last menstrual cycle was 1 year ago singulair purpose or less. Women were premenopausal if they still had a menstrual cycle. Access data table for Figure singulair purpose 1pdf icon.SOURCE.

NCHS, National Health Interview Survey, 2015. The percentage of women aged 40–59 who had trouble falling asleep four times or more in the past week varied singulair purpose by menopausal status.Nearly one in five nonpregnant women aged 40–59 had trouble falling asleep four times or more in the past week (19.4%) (Figure 2). The percentage of women in this age group who had trouble falling asleep four times or more in the past week increased from 16.8% among premenopausal women to 24.7% among perimenopausal and 27.1% among postmenopausal women. Postmenopausal women were significantly more likely than premenopausal women to have trouble falling asleep four times or more in the past week. Figure 2 singulair purpose.

Percentage of nonpregnant women aged 40–59 who had trouble falling asleep four times or more in the past week, by menopausal status. United States, 2015image icon1Significant linear trend by menopausal singulair purpose status (p <. 0.05).NOTES. Women were postmenopausal if they had gone without a menstrual cycle for more than 1 year or were in surgical menopause after the removal of their ovaries. Women were perimenopausal if they no longer had a menstrual cycle and their last menstrual cycle was 1 year singulair purpose ago or less.

Women were premenopausal if they still had a menstrual cycle. Access data table for Figure 2pdf singulair purpose icon.SOURCE. NCHS, National Health Interview Survey, 2015. The percentage of women singulair purpose aged 40–59 who had trouble staying asleep four times or more in the past week varied by menopausal status.More than one in four nonpregnant women aged 40–59 had trouble staying asleep four times or more in the past week (26.7%) (Figure 3). The percentage of women aged 40–59 who had trouble staying asleep four times or more in the past week increased from 23.7% among premenopausal, to 30.8% among perimenopausal, and to 35.9% among postmenopausal women.

Postmenopausal women were significantly more likely than premenopausal women to have trouble staying asleep four times or more in the past week. Figure 3 singulair purpose. Percentage of nonpregnant women aged 40–59 who had trouble staying asleep four times or more in the past week, by menopausal status. United States, 2015image icon1Significant linear singulair purpose trend by menopausal status (p <. 0.05).NOTES.

Women were postmenopausal if they had gone without a menstrual cycle for more than 1 year or were in surgical menopause after the removal of their ovaries. Women were perimenopausal singulair purpose if they no longer had a menstrual cycle and their last menstrual cycle was 1 year ago or less. Women were premenopausal if they still had a menstrual cycle. Access data singulair purpose table for Figure 3pdf icon.SOURCE. NCHS, National Health Interview Survey, 2015.

The percentage of women aged 40–59 who did not wake up feeling well rested 4 days or more in the past week varied by menopausal status.Nearly one in two nonpregnant women aged 40–59 did not wake up feeling well rested 4 days or more in the past week (48.9%) (Figure 4). The percentage singulair purpose of women in this age group who did not wake up feeling well rested 4 days or more in the past week increased from 47.0% among premenopausal women to 49.9% among perimenopausal and 55.1% among postmenopausal women. Postmenopausal women were significantly more likely than premenopausal women to not wake up feeling well rested 4 days or more in the past week. Figure 4 singulair purpose. Percentage of nonpregnant women aged 40–59 who did not wake up feeling well rested 4 days or more in the past week, by menopausal status.

United States, 2015image icon1Significant linear trend by menopausal status (p <. 0.05).NOTES. Women were postmenopausal if they had gone without a menstrual cycle for more than 1 year or were in surgical menopause after the removal of their ovaries. Women were perimenopausal if they no longer had a menstrual cycle and their last menstrual cycle was 1 year ago or less. Women were premenopausal if they still had a menstrual cycle.

Access data table for Figure 4pdf icon.SOURCE. NCHS, National Health Interview Survey, 2015. SummaryThis report describes sleep duration and sleep quality among U.S. Nonpregnant women aged 40–59 by menopausal status. Perimenopausal women were most likely to sleep less than 7 hours, on average, in a 24-hour period compared with premenopausal and postmenopausal women.

In contrast, postmenopausal women were most likely to have poor-quality sleep. A greater percentage of postmenopausal women had frequent trouble falling asleep, staying asleep, and not waking well rested compared with premenopausal women. The percentage of perimenopausal women with poor-quality sleep was between the percentages for the other two groups in all three categories. Sleep duration changes with advancing age (4), but sleep duration and quality are also influenced by concurrent changes in women’s reproductive hormone levels (5). Because sleep is critical for optimal health and well-being (6), the findings in this report highlight areas for further research and targeted health promotion.

DefinitionsMenopausal status. A three-level categorical variable was created from a series of questions that asked women. 1) “How old were you when your periods or menstrual cycles started?. € official website. 2) “Do you still have periods or menstrual cycles?.

€. 3) “When did you have your last period or menstrual cycle?. €. And 4) “Have you ever had both ovaries removed, either as part of a hysterectomy or as one or more separate surgeries?. € Women were postmenopausal if they a) had gone without a menstrual cycle for more than 1 year or b) were in surgical menopause after the removal of their ovaries.

Women were perimenopausal if they a) no longer had a menstrual cycle and b) their last menstrual cycle was 1 year ago or less. Premenopausal women still had a menstrual cycle.Not waking feeling well rested. Determined by respondents who answered 3 days or less on the questionnaire item asking, “In the past week, on how many days did you wake up feeling well rested?. €Short sleep duration. Determined by respondents who answered 6 hours or less on the questionnaire item asking, “On average, how many hours of sleep do you get in a 24-hour period?.

€Trouble falling asleep. Determined by respondents who answered four times or more on the questionnaire item asking, “In the past week, how many times did you have trouble falling asleep?. €Trouble staying asleep. Determined by respondents who answered four times or more on the questionnaire item asking, “In the past week, how many times did you have trouble staying asleep?. € Data source and methodsData from the 2015 National Health Interview Survey (NHIS) were used for this analysis.

NHIS is a multipurpose health survey conducted continuously throughout the year by the National Center for Health Statistics. Interviews are conducted in person in respondents’ homes, but follow-ups to complete interviews may be conducted over the telephone. Data for this analysis came from the Sample Adult core and cancer supplement sections of the 2015 NHIS. For more information about NHIS, including the questionnaire, visit the NHIS website.All analyses used weights to produce national estimates. Estimates on sleep duration and quality in this report are nationally representative of the civilian, noninstitutionalized nonpregnant female population aged 40–59 living in households across the United States.

The sample design is described in more detail elsewhere (7). Point estimates and their estimated variances were calculated using SUDAAN software (8) to account for the complex sample design of NHIS. Linear and quadratic trend tests of the estimated proportions across menopausal status were tested in SUDAAN via PROC DESCRIPT using the POLY option. Differences between percentages were evaluated using two-sided significance tests at the 0.05 level. About the authorAnjel Vahratian is with the National Center for Health Statistics, Division of Health Interview Statistics.

The author gratefully acknowledges the assistance of Lindsey Black in the preparation of this report. ReferencesFord ES. Habitual sleep duration and predicted 10-year cardiovascular risk using the pooled cohort risk equations among US adults. J Am Heart Assoc 3(6):e001454. 2014.Ford ES, Wheaton AG, Chapman DP, Li C, Perry GS, Croft JB.

Associations between self-reported sleep duration and sleeping disorder with concentrations of fasting and 2-h glucose, insulin, and glycosylated hemoglobin among adults without diagnosed diabetes. J Diabetes 6(4):338–50. 2014.American College of Obstetrics and Gynecology. ACOG Practice Bulletin No. 141.

Management of menopausal symptoms. Obstet Gynecol 123(1):202–16. 2014.Black LI, Nugent CN, Adams PF. Tables of adult health behaviors, sleep. National Health Interview Survey, 2011–2014pdf icon.

2016.Santoro N. Perimenopause. From research to practice. J Women’s Health (Larchmt) 25(4):332–9. 2016.Watson NF, Badr MS, Belenky G, Bliwise DL, Buxton OM, Buysse D, et al.

Recommended amount of sleep for a healthy adult. A joint consensus statement of the American Academy of Sleep Medicine and Sleep Research Society. J Clin Sleep Med 11(6):591–2. 2015.Parsons VL, Moriarity C, Jonas K, et al. Design and estimation for the National Health Interview Survey, 2006–2015.

National Center for Health Statistics. Vital Health Stat 2(165). 2014.RTI International. SUDAAN (Release 11.0.0) [computer software]. 2012.

Suggested citationVahratian A. Sleep duration and quality among women aged 40–59, by menopausal status. NCHS data brief, no 286. Hyattsville, MD. National Center for Health Statistics.

2017.Copyright informationAll material appearing in this report is in the public domain and may be reproduced or copied without permission. Citation as to source, however, is appreciated.National Center for Health StatisticsCharles J. Rothwell, M.S., M.B.A., DirectorJennifer H. Madans, Ph.D., Associate Director for ScienceDivision of Health Interview StatisticsMarcie L. Cynamon, DirectorStephen J.

Blumberg, Ph.D., Associate Director for Science.

NCHS Data best online singulair Brief No. 286, September 2017PDF Versionpdf icon (374 KB)Anjel Vahratian, Ph.D.Key findingsData from the National Health Interview Survey, 2015Among those aged 40–59, perimenopausal women (56.0%) were more likely than postmenopausal (40.5%) and premenopausal (32.5%) women to sleep less than 7 hours, on average, in a 24-hour period.Postmenopausal women aged 40–59 were more likely than premenopausal women aged 40–59 to have trouble falling asleep (27.1% compared with 16.8%, respectively), and staying asleep (35.9% compared with 23.7%), four times or more in the past week.Postmenopausal women aged 40–59 (55.1%) were more likely than premenopausal women aged 40–59 (47.0%) to not wake up feeling well rested 4 days or more in the past week.Sleep duration and quality are important contributors to health and wellness. Insufficient sleep is associated with an increased risk for chronic conditions such best online singulair as cardiovascular disease (1) and diabetes (2).

Women may be particularly vulnerable to sleep problems during times of reproductive hormonal change, such as after the menopausal transition. Menopause is “the permanent best online singulair cessation of menstruation that occurs after the loss of ovarian activity” (3). This data brief describes sleep duration and sleep quality among nonpregnant women aged 40–59 by menopausal status.

The age range selected for this analysis reflects the focus on midlife sleep health. In this analysis, 74.2% of women are premenopausal, 3.7% are perimenopausal, and 22.1% are best online singulair postmenopausal. Keywords.

Insufficient sleep, menopause, National Health Interview Survey Perimenopausal women were more likely than premenopausal and postmenopausal women to sleep less than 7 hours, on average, in a 24-hour period.More than one in three nonpregnant women aged 40–59 slept less than 7 hours, on average, in a 24-hour period (35.1%) best online singulair (Figure 1). Perimenopausal women were most likely to sleep less than 7 hours, on average, in a 24-hour period (56.0%), compared with 32.5% of premenopausal and 40.5% of postmenopausal women. Postmenopausal women were significantly more likely than premenopausal women to sleep less than 7 hours, on average, in a 24-hour period.

Figure 1 best online singulair. Percentage of nonpregnant women aged 40–59 who slept less than 7 hours, on average, in a 24-hour period, by menopausal status. United States, 2015image icon1Significant quadratic trend by menopausal best online singulair status (p <.

0.05).NOTES. Women were postmenopausal if they had gone without a menstrual cycle for more than 1 year or were in surgical menopause after the removal of their ovaries. Women were best online singulair perimenopausal if they no longer had a menstrual cycle and their last menstrual cycle was 1 year ago or less.

Women were premenopausal if they still had a menstrual cycle. Access data best online singulair table for Figure 1pdf icon.SOURCE. NCHS, National Health Interview Survey, 2015.

The percentage of women aged 40–59 who had trouble falling asleep four times or more in the past week varied by menopausal status.Nearly one in five nonpregnant women aged 40–59 had trouble best online singulair falling asleep four times or more in the past week (19.4%) (Figure 2). The percentage of women in this age group who had trouble falling asleep four times or more in the past week increased from 16.8% among premenopausal women to 24.7% among perimenopausal and 27.1% among postmenopausal women. Postmenopausal women were significantly more likely than premenopausal women to have trouble falling asleep four times or more in the past week.

Figure 2 best online singulair. Percentage of nonpregnant women aged 40–59 who had trouble falling asleep four times or more in the past week, by menopausal status. United States, 2015image icon1Significant best online singulair linear trend by menopausal status (p <.

0.05).NOTES. Women were postmenopausal if they had gone without a menstrual cycle for more than 1 year or were in surgical menopause after the removal of their ovaries. Women were perimenopausal if they no longer had a menstrual cycle best online singulair and their last menstrual cycle was 1 year ago or less.

Women were premenopausal if they still had a menstrual cycle. Access data table for best online singulair Figure 2pdf icon.SOURCE. NCHS, National Health Interview Survey, 2015.

The percentage best online singulair of women aged 40–59 who had trouble staying asleep four times or more in the past week varied by menopausal status.More than one in four nonpregnant women aged 40–59 had trouble staying asleep four times or more in the past week (26.7%) (Figure 3). The percentage of women aged 40–59 who had trouble staying asleep four times or more in the past week increased from 23.7% among premenopausal, to 30.8% among perimenopausal, and to 35.9% among postmenopausal women. Postmenopausal women were significantly more likely than premenopausal women to have trouble staying asleep four times or more in the past week.

Figure 3 best online singulair. Percentage of nonpregnant women aged 40–59 who had trouble staying asleep four times or more in the past week, by menopausal status. United States, 2015image icon1Significant linear best online singulair trend by menopausal status (p <.

0.05).NOTES. Women were postmenopausal if they had gone without a menstrual cycle for more than 1 year or were in surgical menopause after the removal of their ovaries. Women were perimenopausal if they no longer had a menstrual cycle and their last menstrual best online singulair cycle was 1 year ago or less.

Women were premenopausal if they still had a menstrual cycle. Access data best online singulair table for Figure 3pdf icon.SOURCE. NCHS, National Health Interview Survey, 2015.

The percentage of women aged 40–59 who did not wake up feeling well rested 4 days or more in the past week varied by menopausal status.Nearly one in two nonpregnant women aged 40–59 did not wake up feeling well rested 4 days or more in the past week (48.9%) (Figure 4). The percentage of women in this age group who did not wake up feeling well rested 4 best online singulair days or more in the past week increased from 47.0% among premenopausal women to 49.9% among perimenopausal and 55.1% among postmenopausal women. Postmenopausal women were significantly more likely than premenopausal women to not wake up feeling well rested 4 days or more in the past week.

Figure 4 best online singulair. Percentage of nonpregnant women aged 40–59 who did not wake up feeling well rested 4 days or more in the past week, by menopausal status. United States, 2015image icon1Significant linear trend by menopausal status (p <.

0.05).NOTES. Women were postmenopausal if they had gone without a menstrual cycle for more than 1 year or were in surgical menopause after the removal of their ovaries. Women were perimenopausal if they no longer had a menstrual cycle and their last menstrual cycle was 1 year ago or less.

Women were premenopausal if they still had a menstrual cycle. Access data table for Figure 4pdf icon.SOURCE. NCHS, National Health Interview Survey, 2015.

SummaryThis report describes sleep duration and sleep quality among U.S. Nonpregnant women aged 40–59 by menopausal status. Perimenopausal women were most likely to sleep less than 7 hours, on average, in a 24-hour period compared with premenopausal and postmenopausal women.

In contrast, postmenopausal women were most likely to have poor-quality sleep. A greater percentage of postmenopausal women had frequent trouble falling asleep, staying asleep, and not waking well rested compared with premenopausal women. The percentage of perimenopausal women with poor-quality sleep was between the percentages for the other two groups in all three categories.

Sleep duration changes with advancing age (4), but sleep duration and quality are also influenced by concurrent changes in women’s reproductive hormone levels (5). Because sleep is critical for optimal health and well-being (6), the findings in this report highlight areas for further research and targeted health promotion. DefinitionsMenopausal status.

A three-level categorical variable was created from a series of questions that asked women. 1) “How old were you when your periods or menstrual cycles started?. €.

2) “Do you still have periods or menstrual cycles?. €. 3) “When did you have your last period or menstrual cycle?.

€. And 4) “Have you ever had both ovaries removed, either as part of a hysterectomy or as one or more separate surgeries?. € Women were postmenopausal if they a) had gone without a menstrual cycle for more than 1 year or b) were in surgical menopause after the removal of their ovaries.

Women were perimenopausal if they a) no longer had a menstrual cycle and b) their last menstrual cycle was 1 year ago or less. Premenopausal women still had a menstrual cycle.Not waking feeling well rested. Determined by respondents who answered 3 days or less on the questionnaire item asking, “In the past week, on how many days did you wake up feeling well rested?.

€Short sleep duration. Determined by respondents who answered 6 hours or less on the questionnaire item asking, “On average, how many hours of sleep do you get in a 24-hour period?. €Trouble falling asleep.

Determined by respondents who answered four times or more on the questionnaire item asking, “In the past week, how many times did you have trouble falling asleep?. €Trouble staying asleep. Determined by respondents who answered four times or more on the questionnaire item asking, “In the past week, how many times did you have trouble staying asleep?.

€ Data source and methodsData from the 2015 National Health Interview Survey (NHIS) were used for this analysis. NHIS is a multipurpose health survey conducted continuously throughout the year by the National Center for Health Statistics. Interviews are conducted in person in respondents’ homes, but follow-ups to complete interviews may be conducted over the telephone.

Data for this analysis came from the Sample Adult core and cancer supplement sections of the 2015 NHIS. For more information about NHIS, including the questionnaire, visit the NHIS website.All analyses used weights to produce national estimates. Estimates on sleep duration and quality in this report are nationally representative of the civilian, noninstitutionalized nonpregnant female population aged 40–59 living in households across the United States.

The sample design is described in more detail elsewhere (7). Point estimates and their estimated variances were calculated using SUDAAN software (8) to account for the complex sample design of NHIS. Linear and quadratic trend tests of the estimated proportions across menopausal status were tested in SUDAAN via PROC DESCRIPT using the POLY option.

Differences between percentages were evaluated using two-sided significance tests at the 0.05 level. About the authorAnjel Vahratian is with the National Center for Health Statistics, Division of Health Interview Statistics. The author gratefully acknowledges the assistance of Lindsey Black in the preparation of this report.

ReferencesFord ES. Habitual sleep duration and predicted 10-year cardiovascular risk using the pooled cohort risk equations among US adults. J Am Heart Assoc 3(6):e001454.

2014.Ford ES, Wheaton AG, Chapman DP, Li C, Perry GS, Croft JB. Associations between self-reported sleep duration and sleeping disorder with concentrations of fasting and 2-h glucose, insulin, and glycosylated hemoglobin among adults without diagnosed diabetes. J Diabetes 6(4):338–50.

2014.American College of Obstetrics and Gynecology. ACOG Practice Bulletin No. 141.

Management of menopausal symptoms. Obstet Gynecol 123(1):202–16. 2014.Black LI, Nugent CN, Adams PF.

Tables of adult health behaviors, sleep. National Health Interview Survey, 2011–2014pdf icon. 2016.Santoro N.

Perimenopause. From research to practice. J Women’s Health (Larchmt) 25(4):332–9.

2016.Watson NF, Badr MS, Belenky G, Bliwise DL, Buxton OM, Buysse D, et al. Recommended amount of sleep for a healthy adult. A joint consensus statement of the American Academy of Sleep Medicine and Sleep Research Society.

J Clin Sleep Med 11(6):591–2. 2015.Parsons VL, Moriarity C, Jonas K, et al. Design and estimation for the National Health Interview Survey, 2006–2015.

National Center for Health Statistics. Vital Health Stat 2(165). 2014.RTI International.

SUDAAN (Release 11.0.0) [computer software]. 2012. Suggested citationVahratian A.

Sleep duration and quality among women aged 40–59, by menopausal status. NCHS data brief, no 286. Hyattsville, MD.

National Center for Health Statistics. 2017.Copyright informationAll material appearing in this report is in the public domain and may be reproduced or copied without permission. Citation as to source, however, is appreciated.National Center for Health StatisticsCharles J.

Rothwell, M.S., M.B.A., DirectorJennifer H. Madans, Ph.D., Associate Director for ScienceDivision of Health Interview StatisticsMarcie L. Cynamon, DirectorStephen J.

Blumberg, Ph.D., Associate Director for Science.

Singulair pill price

Trial Population singulair 5 mg precio Table singulair pill price 1. Table 1. Characteristics of the Participants in the singulair pill price mRNA-1273 Trial at Enrollment. The 45 enrolled participants received their first vaccination between March 16 and April 14, 2020 (Fig.

S1). Three participants did not receive the second vaccination, including one in the 25-μg group who had urticaria on both legs, with onset 5 days after the first vaccination, and two (one in the 25-μg group and one in the 250-μg group) who missed the second vaccination window owing to isolation for suspected Covid-19 while the test results, ultimately negative, were pending. All continued to attend scheduled trial visits. The demographic characteristics of participants at enrollment are provided in Table 1.

Vaccine Safety No serious adverse events were noted, and no prespecified trial halting rules were met. As noted above, one participant in the 25-μg group was withdrawn because of an unsolicited adverse event, transient urticaria, judged to be related to the first vaccination. Figure 1. Figure 1.

Systemic and Local Adverse Events. The severity of solicited adverse events was graded as mild, moderate, or severe (see Table S1).After the first vaccination, solicited systemic adverse events were reported by 5 participants (33%) in the 25-μg group, 10 (67%) in the 100-μg group, and 8 (53%) in the 250-μg group. All were mild or moderate in severity (Figure 1 and Table S2). Solicited systemic adverse events were more common after the second vaccination and occurred in 7 of 13 participants (54%) in the 25-μg group, all 15 in the 100-μg group, and all 14 in the 250-μg group, with 3 of those participants (21%) reporting one or more severe events.

None of the participants had fever after the first vaccination. After the second vaccination, no participants in the 25-μg group, 6 (40%) in the 100-μg group, and 8 (57%) in the 250-μg group reported fever. One of the events (maximum temperature, 39.6°C) in the 250-μg group was graded severe. (Additional details regarding adverse events for that participant are provided in the Supplementary Appendix.) Local adverse events, when present, were nearly all mild or moderate, and pain at the injection site was common.

Across both vaccinations, solicited systemic and local adverse events that occurred in more than half the participants included fatigue, chills, headache, myalgia, and pain at the injection site. Evaluation of safety clinical laboratory values of grade 2 or higher and unsolicited adverse events revealed no patterns of concern (Supplementary Appendix and Table S3). SARS-CoV-2 Binding Antibody Responses Table 2. Table 2.

Geometric Mean Humoral Immunogenicity Assay Responses to mRNA-1273 in Participants and in Convalescent Serum Specimens. Figure 2. Figure 2. SARS-CoV-2 Antibody and Neutralization Responses.

Shown are geometric mean reciprocal end-point enzyme-linked immunosorbent assay (ELISA) IgG titers to S-2P (Panel A) and receptor-binding domain (Panel B), PsVNA ID50 responses (Panel C), and live virus PRNT80 responses (Panel D). In Panel A and Panel B, boxes and horizontal bars denote interquartile range (IQR) and median area under the curve (AUC), respectively. Whisker endpoints are equal to the maximum and minimum values below or above the median ±1.5 times the IQR. The convalescent serum panel includes specimens from 41 participants.

Red dots indicate the 3 specimens that were also tested in the PRNT assay. The other 38 specimens were used to calculate summary statistics for the box plot in the convalescent serum panel. In Panel C, boxes and horizontal bars denote IQR and median ID50, respectively. Whisker end points are equal to the maximum and minimum values below or above the median ±1.5 times the IQR.

In the convalescent serum panel, red dots indicate the 3 specimens that were also tested in the PRNT assay. The other 38 specimens were used to calculate summary statistics for the box plot in the convalescent panel. In Panel D, boxes and horizontal bars denote IQR and median PRNT80, respectively. Whisker end points are equal to the maximum and minimum values below or above the median ±1.5 times the IQR.

The three convalescent serum specimens were also tested in ELISA and PsVNA assays. Because of the time-intensive nature of the PRNT assay, for this preliminary report, PRNT results were available only for the 25-μg and 100-μg dose groups.Binding antibody IgG geometric mean titers (GMTs) to S-2P increased rapidly after the first vaccination, with seroconversion in all participants by day 15 (Table 2 and Figure 2A). Dose-dependent responses to the first and second vaccinations were evident. Receptor-binding domain–specific antibody responses were similar in pattern and magnitude (Figure 2B).

For both assays, the median magnitude of antibody responses after the first vaccination in the 100-μg and 250-μg dose groups was similar to the median magnitude in convalescent serum specimens, and in all dose groups the median magnitude after the second vaccination was in the upper quartile of values in the convalescent serum specimens. The S-2P ELISA GMTs at day 57 (299,751 [95% confidence interval {CI}, 206,071 to 436,020] in the 25-μg group, 782,719 [95% CI, 619,310 to 989,244] in the 100-μg group, and 1,192,154 [95% CI, 924,878 to 1,536,669] in the 250-μg group) exceeded that in the convalescent serum specimens (142,140 [95% CI, 81,543 to 247,768]). SARS-CoV-2 Neutralization Responses No participant had detectable PsVNA responses before vaccination. After the first vaccination, PsVNA responses were detected in less than half the participants, and a dose effect was seen (50% inhibitory dilution [ID50].

Figure 2C, Fig. S8, and Table 2. 80% inhibitory dilution [ID80]. Fig.

S2 and Table S6). However, after the second vaccination, PsVNA responses were identified in serum samples from all participants. The lowest responses were in the 25-μg dose group, with a geometric mean ID50 of 112.3 (95% CI, 71.2 to 177.1) at day 43. The higher responses in the 100-μg and 250-μg groups were similar in magnitude (geometric mean ID50, 343.8 [95% CI, 261.2 to 452.7] and 332.2 [95% CI, 266.3 to 414.5], respectively, at day 43).

These responses were similar to values in the upper half of the distribution of values for convalescent serum specimens. Before vaccination, no participant had detectable 80% live-virus neutralization at the highest serum concentration tested (1:8 dilution) in the PRNT assay. At day 43, wild-type virus–neutralizing activity capable of reducing SARS-CoV-2 infectivity by 80% or more (PRNT80) was detected in all participants, with geometric mean PRNT80 responses of 339.7 (95% CI, 184.0 to 627.1) in the 25-μg group and 654.3 (95% CI, 460.1 to 930.5) in the 100-μg group (Figure 2D). Neutralizing PRNT80 average responses were generally at or above the values of the three convalescent serum specimens tested in this assay.

Good agreement was noted within and between the values from binding assays for S-2P and receptor-binding domain and neutralizing activity measured by PsVNA and PRNT (Figs. S3 through S7), which provides orthogonal support for each assay in characterizing the humoral response induced by mRNA-1273. SARS-CoV-2 T-Cell Responses The 25-μg and 100-μg doses elicited CD4 T-cell responses (Figs. S9 and S10) that on stimulation by S-specific peptide pools were strongly biased toward expression of Th1 cytokines (tumor necrosis factor α >.

Interleukin 2 >. Interferon γ), with minimal type 2 helper T-cell (Th2) cytokine expression (interleukin 4 and interleukin 13). CD8 T-cell responses to S-2P were detected at low levels after the second vaccination in the 100-μg dose group (Fig. S11).Patients Figure 1.

Figure 1. Enrollment and Randomization. Of the 1107 patients who were assessed for eligibility, 1063 underwent randomization. 541 were assigned to the remdesivir group and 522 to the placebo group (Figure 1).

Of those assigned to receive remdesivir, 531 patients (98.2%) received the treatment as assigned. Forty-nine patients had remdesivir treatment discontinued before day 10 because of an adverse event or a serious adverse event other than death (36 patients) or because the patient withdrew consent (13). Of those assigned to receive placebo, 518 patients (99.2%) received placebo as assigned. Fifty-three patients discontinued placebo before day 10 because of an adverse event or a serious adverse event other than death (36 patients), because the patient withdrew consent (15), or because the patient was found to be ineligible for trial enrollment (2).

As of April 28, 2020, a total of 391 patients in the remdesivir group and 340 in the placebo group had completed the trial through day 29, recovered, or died. Eight patients who received remdesivir and 9 who received placebo terminated their participation in the trial before day 29. There were 132 patients in the remdesivir group and 169 in the placebo group who had not recovered and had not completed the day 29 follow-up visit. The analysis population included 1059 patients for whom we have at least some postbaseline data available (538 in the remdesivir group and 521 in the placebo group).

Four of the 1063 patients were not included in the primary analysis because no postbaseline data were available at the time of the database freeze. Table 1. Table 1. Demographic and Clinical Characteristics at Baseline.

The mean age of patients was 58.9 years, and 64.3% were male (Table 1). On the basis of the evolving epidemiology of Covid-19 during the trial, 79.8% of patients were enrolled at sites in North America, 15.3% in Europe, and 4.9% in Asia (Table S1). Overall, 53.2% of the patients were white, 20.6% were black, 12.6% were Asian, and 13.6% were designated as other or not reported. 249 (23.4%) were Hispanic or Latino.

Most patients had either one (27.0%) or two or more (52.1%) of the prespecified coexisting conditions at enrollment, most commonly hypertension (49.6%), obesity (37.0%), and type 2 diabetes mellitus (29.7%). The median number of days between symptom onset and randomization was 9 (interquartile range, 6 to 12). Nine hundred forty-three (88.7%) patients had severe disease at enrollment as defined in the Supplementary Appendix. 272 (25.6%) patients met category 7 criteria on the ordinal scale, 197 (18.5%) category 6, 421 (39.6%) category 5, and 127 (11.9%) category 4.

There were 46 (4.3%) patients who had missing ordinal scale data at enrollment. No substantial imbalances in baseline characteristics were observed between the remdesivir group and the placebo group. Primary Outcome Figure 2. Figure 2.

Kaplan–Meier Estimates of Cumulative Recoveries. Cumulative recovery estimates are shown in the overall population (Panel A), in patients with a baseline score of 4 on the ordinal scale (not receiving oxygen. Panel B), in those with a baseline score of 5 (receiving oxygen. Panel C), in those with a baseline score of 6 (receiving high-flow oxygen or noninvasive mechanical ventilation.

Panel D), and in those with a baseline score of 7 (receiving mechanical ventilation or ECMO. Panel E). Table 2. Table 2.

Outcomes Overall and According to Score on the Ordinal Scale in the Intention-to-Treat Population. Figure 3. Figure 3. Time to Recovery According to Subgroup.

The widths of the confidence intervals have not been adjusted for multiplicity and therefore cannot be used to infer treatment effects. Race and ethnic group were reported by the patients. Patients in the remdesivir group had a shorter time to recovery than patients in the placebo group (median, 11 days, as compared with 15 days. Rate ratio for recovery, 1.32.

95% confidence interval [CI], 1.12 to 1.55. P<0.001. 1059 patients (Figure 2 and Table 2). Among patients with a baseline ordinal score of 5 (421 patients), the rate ratio for recovery was 1.47 (95% CI, 1.17 to 1.84).

Among patients with a baseline score of 4 (127 patients) and those with a baseline score of 6 (197 patients), the rate ratio estimates for recovery were 1.38 (95% CI, 0.94 to 2.03) and 1.20 (95% CI, 0.79 to 1.81), respectively. For those receiving mechanical ventilation or ECMO at enrollment (baseline ordinal scores of 7. 272 patients), the rate ratio for recovery was 0.95 (95% CI, 0.64 to 1.42). A test of interaction of treatment with baseline score on the ordinal scale was not significant.

An analysis adjusting for baseline ordinal score as a stratification variable was conducted to evaluate the overall effect (of the percentage of patients in each ordinal score category at baseline) on the primary outcome. This adjusted analysis produced a similar treatment-effect estimate (rate ratio for recovery, 1.31. 95% CI, 1.12 to 1.54. 1017 patients).

Table S2 in the Supplementary Appendix shows results according to the baseline severity stratum of mild-to-moderate as compared with severe. Patients who underwent randomization during the first 10 days after the onset of symptoms had a rate ratio for recovery of 1.28 (95% CI, 1.05 to 1.57. 664 patients), whereas patients who underwent randomization more than 10 days after the onset of symptoms had a rate ratio for recovery of 1.38 (95% CI, 1.05 to 1.81. 380 patients) (Figure 3).

Key Secondary Outcome The odds of improvement in the ordinal scale score were higher in the remdesivir group, as determined by a proportional odds model at the day 15 visit, than in the placebo group (odds ratio for improvement, 1.50. 95% CI, 1.18 to 1.91. P=0.001. 844 patients) (Table 2 and Fig.

S5). Mortality was numerically lower in the remdesivir group than in the placebo group, but the difference was not significant (hazard ratio for death, 0.70. 95% CI, 0.47 to 1.04. 1059 patients).

The Kaplan–Meier estimates of mortality by 14 days were 7.1% and 11.9% in the remdesivir and placebo groups, respectively (Table 2). The Kaplan–Meier estimates of mortality by 28 days are not reported in this preliminary analysis, given the large number of patients that had yet to complete day 29 visits. An analysis with adjustment for baseline ordinal score as a stratification variable showed a hazard ratio for death of 0.74 (95% CI, 0.50 to 1.10). Safety Outcomes Serious adverse events occurred in 114 patients (21.1%) in the remdesivir group and 141 patients (27.0%) in the placebo group (Table S3).

4 events (2 in each group) were judged by site investigators to be related to remdesivir or placebo. There were 28 serious respiratory failure adverse events in the remdesivir group (5.2% of patients) and 42 in the placebo group (8.0% of patients). Acute respiratory failure, hypotension, viral pneumonia, and acute kidney injury were slightly more common among patients in the placebo group. No deaths were considered to be related to treatment assignment, as judged by the site investigators.

Grade 3 or 4 adverse events occurred in 156 patients (28.8%) in the remdesivir group and in 172 in the placebo group (33.0%) (Table S4). The most common adverse events in the remdesivir group were anemia or decreased hemoglobin (43 events [7.9%], as compared with 47 [9.0%] in the placebo group). Acute kidney injury, decreased estimated glomerular filtration rate or creatinine clearance, or increased blood creatinine (40 events [7.4%], as compared with 38 [7.3%]). Pyrexia (27 events [5.0%], as compared with 17 [3.3%]).

Hyperglycemia or increased blood glucose level (22 events [4.1%], as compared with 17 [3.3%]). And increased aminotransferase levels including alanine aminotransferase, aspartate aminotransferase, or both (22 events [4.1%], as compared with 31 [5.9%]). Otherwise, the incidence of adverse events was not found to be significantly different between the remdesivir group and the placebo group.Announced on May 15, Operation Warp Speed (OWS) — a partnership of the Department of Health and Human Services (HHS), the Department of Defense (DOD), and the private sector — aims to accelerate control of the Covid-19 pandemic by advancing development, manufacturing, and distribution of vaccines, therapeutics, and diagnostics. OWS is providing support to promising candidates and enabling the expeditious, parallel execution of the necessary steps toward approval or authorization of safe products by the Food and Drug Administration (FDA).The partnership grew out of an acknowledged need to fundamentally restructure the way the U.S.

Government typically supports go to this site product development and vaccine distribution. The initiative was premised on setting a “stretch goal” — one that initially seemed impossible but that is becoming increasingly achievable.The concept of an integrated structure for Covid-19 countermeasure research and development across the U.S. Government was based on experience with Zika and the Zika Leadership Group led by the National Institutes of Health (NIH) and the assistant secretary for preparedness and response (ASPR). One of us (M.S.) serves as OWS chief advisor.

We are drawing on expertise from the NIH, ASPR, the Centers for Disease Control and Prevention (CDC), the Biomedical Advanced Research and Development Authority (BARDA), and the DOD, including the Joint Program Executive Office for Chemical, Biological, Radiological and Nuclear Defense and the Defense Advanced Research Projects Agency. OWS has engaged experts in all critical aspects of medical countermeasure research, development, manufacturing, and distribution to work in close coordination.The initiative set ambitious objectives. To deliver tens of millions of doses of a SARS-CoV-2 vaccine — with demonstrated safety and efficacy, and approved or authorized by the FDA for use in the U.S. Population — beginning at the end of 2020 and to have as many as 300 million doses of such vaccines available and deployed by mid-2021.

The pace and scope of such a vaccine effort are unprecedented. The 2014 West African Ebola virus epidemic spurred rapid vaccine development, but though preclinical data existed before the outbreak, a period of 12 months was required to progress from phase 1 first-in-human trials to phase 3 efficacy trials. OWS aims to compress this time frame even further. SARS-CoV-2 vaccine development began in January, phase 1 clinical studies in March, and the first phase 3 trials in July.

Our objectives are based on advances in vaccine platform technology, improved understanding of safe and efficacious vaccine design, and similarities between the SARS-CoV-1 and SARS-CoV-2 disease mechanisms.OWS’s role is to enable, accelerate, harmonize, and advise the companies developing the selected vaccines. The companies will execute the clinical or process development and manufacturing plans, while OWS leverages the full capacity of the U.S. Government to ensure that no technical, logistic, or financial hurdles hinder vaccine development or deployment.OWS selected vaccine candidates on the basis of four criteria. We required candidates to have robust preclinical data or early-stage clinical trial data supporting their potential for clinical safety and efficacy.

Candidates had to have the potential, with our acceleration support, to enter large phase 3 field efficacy trials this summer or fall (July to November 2020) and, assuming continued active transmission of the virus, to deliver efficacy outcomes by the end of 2020 or the first half of 2021. Candidates had to be based on vaccine-platform technologies permitting fast and effective manufacturing, and their developers had to demonstrate the industrial process scalability, yields, and consistency necessary to reliably produce more than 100 million doses by mid-2021. Finally, candidates had to use one of four vaccine-platform technologies that we believe are the most likely to yield a safe and effective vaccine against Covid-19. The mRNA platform, the replication-defective live-vector platform, the recombinant-subunit-adjuvanted protein platform, or the attenuated replicating live-vector platform.OWS’s strategy relies on a few key principles.

First, we sought to build a diverse project portfolio that includes two vaccine candidates based on each of the four platform technologies. Such diversification mitigates the risk of failure due to safety, efficacy, industrial manufacturability, or scheduling factors and may permit selection of the best vaccine platform for each subpopulation at risk for contracting or transmitting Covid-19, including older adults, frontline and essential workers, young adults, and pediatric populations. In addition, advancing eight vaccines in parallel will increase the chances of delivering 300 million doses in the first half of 2021.Second, we must accelerate vaccine program development without compromising safety, efficacy, or product quality. Clinical development, process development, and manufacturing scale-up can be substantially accelerated by running all streams, fully resourced, in parallel.

Doing so requires taking on substantial financial risk, as compared with the conventional sequential development approach. OWS will maximize the size of phase 3 trials (30,000 to 50,000 participants each) and optimize trial-site location by consulting daily epidemiologic and disease-forecasting models to ensure the fastest path to an efficacy readout. Such large trials also increase the safety data set for each candidate vaccine.With heavy up-front investment, companies can conduct clinical operations and site preparation for these phase 3 efficacy trials even as they file their Investigational New Drug application (IND) for their phase 1 studies, thereby ensuring immediate initiation of phase 3 when they get a green light from the FDA. To permit appropriate comparisons among the vaccine candidates and to optimize vaccine utilization after approval by the FDA, the phase 3 trial end points and assay readouts have been harmonized through a collaborative effort involving the National Institute of Allergy and Infectious Diseases (NIAID), the Coronavirus Prevention Network, OWS, and the sponsor companies.Finally, OWS is supporting the companies financially and technically to commence process development and scale up manufacturing while their vaccines are in preclinical or very early clinical stages.

To ensure that industrial processes are set, running, and validated for FDA inspection when phase 3 trials end, OWS is also supporting facility building or refurbishing, equipment fitting, staff hiring and training, raw-material sourcing, technology transfer and validation, bulk product processing into vials, and acquisition of ample vials, syringes, and needles for each vaccine candidate. We aim to have stockpiled, at OWS’s expense, a few tens of millions of vaccine doses that could be swiftly deployed once FDA approval is obtained.This strategy aims to accelerate vaccine development without curtailing the critical steps required by sound science and regulatory standards. The FDA recently reissued guidance and standards that will be used to assess each vaccine for a Biologics License Application (BLA). Alternatively, the agency could decide to issue an Emergency Use Authorization to permit vaccine administration before all BLA procedures are completed.Of the eight vaccines in OWS’s portfolio, six have been announced and partnerships executed with the companies.

Moderna and Pfizer/BioNTech (both mRNA), AstraZeneca and Janssen (both replication-defective live-vector), and Novavax and Sanofi/GSK (both recombinant-subunit-adjuvanted protein). These candidates cover three of the four platform technologies and are currently in clinical trials. The remaining two candidates will enter trials soon.Moderna developed its RNA vaccine in collaboration with the NIAID, began its phase 1 trial in March, recently published encouraging safety and immunogenicity data,1 and entered phase 3 on July 27. Pfizer and BioNTech’s RNA vaccine also produced encouraging phase 1 results2 and started its phase 3 trial on July 27.

The ChAdOx replication-defective live-vector vaccine developed by AstraZeneca and Oxford University is in phase 3 trials in the United Kingdom, Brazil, and South Africa, and it should enter U.S. Phase 3 trials in August.3 The Janssen Ad26 Covid-19 replication-defective live-vector vaccine has demonstrated excellent protection in nonhuman primate models and began its U.S. Phase 1 trial on July 27. It should be in phase 3 trials in mid-September.

Novavax completed a phase 1 trial of its recombinant-subunit-adjuvanted protein vaccine in Australia and should enter phase 3 trials in the United States by the end of September.4 Sanofi/GSK is completing preclinical development steps and plans to commence a phase 1 trial in early September and to be well into phase 3 by year’s end.5On the process-development front, the RNA vaccines are already being manufactured at scale. The other candidates are well advanced in their scale-up development, and manufacturing sites are being refurbished.While development and manufacturing proceed, the HHS–DOD partnership is laying the groundwork for vaccine distribution, subpopulation prioritization, financing, and logistic support. We are working with bioethicists and experts from the NIH, the CDC, BARDA, and the Centers for Medicare and Medicaid Services to address these critical issues. We will receive recommendations from the CDC Advisory Committee on Immunization Practices, and we are working to ensure that the most vulnerable and at-risk persons will receive vaccine doses once they are ready.

Prioritization will also depend on the relative performance of each vaccine and its suitability for particular populations. Because some technologies have limited previous data on safety in humans, the long-term safety of these vaccines will be carefully assessed using pharmacovigilance surveillance strategies.No scientific enterprise could guarantee success by January 2021, but the strategic decisions and choices we’ve made, the support the government has provided, and the accomplishments to date make us optimistic that we will succeed in this unprecedented endeavor.Trial Design and Oversight We conducted a randomized, double-blind, placebo-controlled trial to evaluate postexposure prophylaxis with hydroxychloroquine after exposure to Covid-19.12 We randomly assigned participants in a 1:1 ratio to receive either hydroxychloroquine or placebo. Participants had known exposure (by participant report) to a person with laboratory-confirmed Covid-19, whether as a household contact, a health care worker, or a person with other occupational exposures. Trial enrollment began on March 17, 2020, with an eligibility threshold to enroll within 3 days after exposure.

The objective was to intervene before the median incubation period of 5 to 6 days. Because of limited access to prompt testing, health care workers could initially be enrolled on the basis of presumptive high-risk exposure to patients with pending tests. However, on March 23, eligibility was changed to exposure to a person with a positive polymerase-chain-reaction (PCR) assay for SARS-CoV-2, with the eligibility window extended to within 4 days after exposure. This trial was approved by the institutional review board at the University of Minnesota and conducted under a Food and Drug Administration Investigational New Drug application.

In Canada, the trial was approved by Health Canada. Ethics approvals were obtained from the Research Institute of the McGill University Health Centre, the University of Manitoba, and the University of Alberta. Participants We included participants who had household or occupational exposure to a person with confirmed Covid-19 at a distance of less than 6 ft for more than 10 minutes while wearing neither a face mask nor an eye shield (high-risk exposure) or while wearing a face mask but no eye shield (moderate-risk exposure). Participants were excluded if they were younger than 18 years of age, were hospitalized, or met other exclusion criteria (see the Supplementary Appendix, available with the full text of this article at NEJM.org).

Persons with symptoms of Covid-19 or with PCR-proven SARS-CoV-2 infection were excluded from this prevention trial but were separately enrolled in a companion clinical trial to treat early infection. Setting Recruitment was performed primarily with the use of social media outreach as well as traditional media platforms. Participants were enrolled nationwide in the United States and in the Canadian provinces of Quebec, Manitoba, and Alberta. Participants enrolled themselves through a secure Internet-based survey using the Research Electronic Data Capture (REDCap) system.13 After participants read the consent form, their comprehension of its contents was assessed.

Participants provided a digitally captured signature to indicate informed consent. We sent follow-up e-mail surveys on days 1, 5, 10, and 14. A survey at 4 to 6 weeks asked about any follow-up testing, illness, or hospitalizations. Participants who did not respond to follow-up surveys received text messages, e-mails, telephone calls, or a combination of these to ascertain their outcomes.

When these methods were unsuccessful, the emergency contact provided by the enrollee was contacted to determine the participant’s illness and vital status. When all communication methods were exhausted, Internet searches for obituaries were performed to ascertain vital status. Interventions Randomization occurred at research pharmacies in Minneapolis and Montreal. The trial statisticians generated a permuted-block randomization sequence using variably sized blocks of 2, 4, or 8, with stratification according to country.

A research pharmacist sequentially assigned participants. The assignments were concealed from investigators and participants. Only pharmacies had access to the randomization sequence. Hydroxychloroquine sulfate or placebo was dispensed and shipped overnight to participants by commercial courier.

The dosing regimen for hydroxychloroquine was 800 mg (4 tablets) once, then 600 mg (3 tablets) 6 to 8 hours later, then 600 mg (3 tablets) daily for 4 more days for a total course of 5 days (19 tablets total). If participants had gastrointestinal upset, they were advised to divide the daily dose into two or three doses. We chose this hydroxychloroquine dosing regimen on the basis of pharmacokinetic simulations to achieve plasma concentrations above the SARS-CoV-2 in vitro half maximal effective concentration for 14 days.14 Placebo folate tablets, which were similar in appearance to the hydroxychloroquine tablets, were prescribed as an identical regimen for the control group. Rising Pharmaceuticals provided a donation of hydroxychloroquine, and some hydroxychloroquine was purchased.

Outcomes The primary outcome was prespecified as symptomatic illness confirmed by a positive molecular assay or, if testing was unavailable, Covid-19–related symptoms. We assumed that health care workers would have access to Covid-19 testing if symptomatic. However, access to testing was limited throughout the trial period. Covid-19–related symptoms were based on U.S.

Council for State and Territorial Epidemiologists criteria for confirmed cases (positivity for SARS-Cov-2 on PCR assay), probable cases (the presence of cough, shortness of breath, or difficulty breathing, or the presence of two or more symptoms of fever, chills, rigors, myalgia, headache, sore throat, and new olfactory and taste disorders), and possible cases (the presence of one or more compatible symptoms, which could include diarrhea).15 All the participants had epidemiologic linkage,15 per trial eligibility criteria. Four infectious disease physicians who were unaware of the trial-group assignments reviewed symptomatic participants to generate a consensus with respect to whether their condition met the case definition.15 Secondary outcomes included the incidence of hospitalization for Covid-19 or death, the incidence of PCR-confirmed SARS-CoV-2 infection, the incidence of Covid-19 symptoms, the incidence of discontinuation of the trial intervention owing to any cause, and the severity of symptoms (if any) at days 5 and 14 according to a visual analogue scale (scores ranged from 0 [no symptoms] to 10 [severe symptoms]). Data on adverse events were also collected with directed questioning for common side effects along with open-ended free text. Outcome data were measured within 14 days after trial enrollment.

Outcome data including PCR testing results, possible Covid-19–related symptoms, adherence to the trial intervention, side effects, and hospitalizations were all collected through participant report. Details of trial conduct are provided in the protocol and statistical analysis plan, available at NEJM.org. Sample Size We anticipated that illness compatible with Covid-19 would develop in 10% of close contacts exposed to Covid-19.9 Using Fisher’s exact method with a 50% relative effect size to reduce new symptomatic infections, a two-sided alpha of 0.05, and 90% power, we estimated that 621 persons would need to be enrolled in each group. With a pragmatic, Internet-based, self-referral recruitment strategy, we planned for a 20% incidence of attrition by increasing the sample size to 750 participants per group.

We specified a priori that participants who were already symptomatic on day 1 before receiving hydroxychloroquine or placebo would be excluded from the prophylaxis trial and would instead be separately enrolled in the companion symptomatic treatment trial. Because the estimates for both incident symptomatic Covid-19 after an exposure and loss to follow-up were relatively unknown in early March 2020,9 the protocol prespecified a sample-size reestimation at the second interim analysis. This reestimation, which used the incidence of new infections in the placebo group and the observed percentage of participants lost to follow-up, was aimed at maintaining the ability to detect an effect size of a 50% relative reduction in new symptomatic infections. Interim Analyses An independent data and safety monitoring board externally reviewed the data after 25% and 50% of the participants had completed 14 days of follow-up.

Stopping guidelines were provided to the data and safety monitoring board with the use of a Lan–DeMets spending function analogue of the O’Brien–Fleming boundaries for the primary outcome. A conditional power analysis was performed at the second and third interim analysis with the option of early stopping for futility. At the second interim analysis on April 22, 2020, the sample size was reduced to 956 participants who could be evaluated with 90% power on the basis of the higher-than-expected event rate of infections in the control group. At the third interim analysis on May 6, the trial was halted on the basis of a conditional power of less than 1%, since it was deemed futile to continue.

Statistical Analysis We assessed the incidence of Covid-19 disease by day 14 with Fisher’s exact test. Secondary outcomes with respect to percentage of patients were also compared with Fisher’s exact test. Among participants in whom incident illness compatible with Covid-19 developed, we summarized the symptom severity score at day 14 with the median and interquartile range and assessed the distributions with a Kruskal–Wallis test. We conducted all analyses with SAS software, version 9.4 (SAS Institute), according to the intention-to-treat principle, with two-sided type I error with an alpha of 0.05.

For participants with missing outcome data, we conducted a sensitivity analysis with their outcomes excluded or included as an event. Subgroups that were specified a priori included type of contact (household vs. Health care), days from exposure to enrollment, age, and sex.Trial Design and Oversight The RECOVERY trial was designed to evaluate the effects of potential treatments in patients hospitalized with Covid-19 at 176 National Health Service organizations in the United Kingdom and was supported by the National Institute for Health Research Clinical Research Network. (Details regarding this trial are provided in the Supplementary Appendix, available with the full text of this article at NEJM.org.) The trial is being coordinated by the Nuffield Department of Population Health at the University of Oxford, the trial sponsor.

Although the randomization of patients to receive dexamethasone, hydroxychloroquine, or lopinavir–ritonavir has now been stopped, the trial continues randomization to groups receiving azithromycin, tocilizumab, or convalescent plasma. Hospitalized patients were eligible for the trial if they had clinically suspected or laboratory-confirmed SARS-CoV-2 infection and no medical history that might, in the opinion of the attending clinician, put patients at substantial risk if they were to participate in the trial. Initially, recruitment was limited to patients who were at least 18 years of age, but the age limit was removed starting on May 9, 2020. Pregnant or breast-feeding women were eligible.

Written informed consent was obtained from all the patients or from a legal representative if they were unable to provide consent. The trial was conducted in accordance with the principles of the Good Clinical Practice guidelines of the International Conference on Harmonisation and was approved by the U.K. Medicines and Healthcare Products Regulatory Agency and the Cambridge East Research Ethics Committee. The protocol with its statistical analysis plan is available at NEJM.org and on the trial website at www.recoverytrial.net.

The initial version of the manuscript was drafted by the first and last authors, developed by the writing committee, and approved by all members of the trial steering committee. The funders had no role in the analysis of the data, in the preparation or approval of the manuscript, or in the decision to submit the manuscript for publication. The first and last members of the writing committee vouch for the completeness and accuracy of the data and for the fidelity of the trial to the protocol and statistical analysis plan. Randomization We collected baseline data using a Web-based case-report form that included demographic data, the level of respiratory support, major coexisting illnesses, suitability of the trial treatment for a particular patient, and treatment availability at the trial site.

Randomization was performed with the use of a Web-based system with concealment of the trial-group assignment. Eligible and consenting patients were assigned in a 2:1 ratio to receive either the usual standard of care alone or the usual standard of care plus oral or intravenous dexamethasone (at a dose of 6 mg once daily) for up to 10 days (or until hospital discharge if sooner) or to receive one of the other suitable and available treatments that were being evaluated in the trial. For some patients, dexamethasone was unavailable at the hospital at the time of enrollment or was considered by the managing physician to be either definitely indicated or definitely contraindicated. These patients were excluded from entry in the randomized comparison between dexamethasone and usual care and hence were not included in this report.

The randomly assigned treatment was prescribed by the treating clinician. Patients and local members of the trial staff were aware of the assigned treatments. Procedures A single online follow-up form was to be completed when the patients were discharged or had died or at 28 days after randomization, whichever occurred first. Information was recorded regarding the patients’ adherence to the assigned treatment, receipt of other trial treatments, duration of admission, receipt of respiratory support (with duration and type), receipt of renal support, and vital status (including the cause of death).

In addition, we obtained routine health care and registry data, including information on vital status (with date and cause of death), discharge from the hospital, and respiratory and renal support therapy. Outcome Measures The primary outcome was all-cause mortality within 28 days after randomization. Further analyses were specified at 6 months. Secondary outcomes were the time until discharge from the hospital and, among patients not receiving invasive mechanical ventilation at the time of randomization, subsequent receipt of invasive mechanical ventilation (including extracorporeal membrane oxygenation) or death.

Other prespecified clinical outcomes included cause-specific mortality, receipt of renal hemodialysis or hemofiltration, major cardiac arrhythmia (recorded in a subgroup), and receipt and duration of ventilation. Statistical Analysis As stated in the protocol, appropriate sample sizes could not be estimated when the trial was being planned at the start of the Covid-19 pandemic. As the trial progressed, the trial steering committee, whose members were unaware of the results of the trial comparisons, determined that if 28-day mortality was 20%, then the enrollment of at least 2000 patients in the dexamethasone group and 4000 in the usual care group would provide a power of at least 90% at a two-sided P value of 0.01 to detect a clinically relevant proportional reduction of 20% (an absolute difference of 4 percentage points) between the two groups. Consequently, on June 8, 2020, the steering committee closed recruitment to the dexamethasone group, since enrollment had exceeded 2000 patients.

For the primary outcome of 28-day mortality, the hazard ratio from Cox regression was used to estimate the mortality rate ratio. Among the few patients (0.1%) who had not been followed for 28 days by the time of the data cutoff on July 6, 2020, data were censored either on that date or on day 29 if the patient had already been discharged. That is, in the absence of any information to the contrary, these patients were assumed to have survived for 28 days. Kaplan–Meier survival curves were constructed to show cumulative mortality over the 28-day period.

Cox regression was used to analyze the secondary outcome of hospital discharge within 28 days, with censoring of data on day 29 for patients who had died during hospitalization. For the prespecified composite secondary outcome of invasive mechanical ventilation or death within 28 days (among patients who were not receiving invasive mechanical ventilation at randomization), the precise date of invasive mechanical ventilation was not available, so a log-binomial regression model was used to estimate the risk ratio. Table 1. Table 1.

Characteristics of the Patients at Baseline, According to Treatment Assignment and Level of Respiratory Support. Through the play of chance in the unstratified randomization, the mean age was 1.1 years older among patients in the dexamethasone group than among those in the usual care group (Table 1). To account for this imbalance in an important prognostic factor, estimates of rate ratios were adjusted for the baseline age in three categories (<70 years, 70 to 79 years, and ≥80 years). This adjustment was not specified in the first version of the statistical analysis plan but was added once the imbalance in age became apparent.

Results without age adjustment (corresponding to the first version of the analysis plan) are provided in the Supplementary Appendix. Prespecified analyses of the primary outcome were performed in five subgroups, as defined by characteristics at randomization. Age, sex, level of respiratory support, days since symptom onset, and predicted 28-day mortality risk. (One further prespecified subgroup analysis regarding race will be conducted once the data collection has been completed.) In prespecified subgroups, we estimated rate ratios (or risk ratios in some analyses) and their confidence intervals using regression models that included an interaction term between the treatment assignment and the subgroup of interest.

Chi-square tests for linear trend across the subgroup-specific log estimates were then performed in accordance with the prespecified plan. All P values are two-sided and are shown without adjustment for multiple testing. All analyses were performed according to the intention-to-treat principle. The full database is held by the trial team, which collected the data from trial sites and performed the analyses at the Nuffield Department of Population Health, University of Oxford..

Trial Population best online singulair he has a good point Table 1. Table 1. Characteristics of the Participants in best online singulair the mRNA-1273 Trial at Enrollment.

The 45 enrolled participants received their first vaccination between March 16 and April 14, 2020 (Fig. S1). Three participants did not receive the second vaccination, including one in the 25-μg group who had urticaria on both legs, with onset 5 days after the first vaccination, and two (one in the 25-μg group and one in the 250-μg group) who missed the second vaccination window owing to isolation for suspected Covid-19 while the test results, ultimately negative, were pending.

All continued to attend scheduled trial visits. The demographic characteristics of participants at enrollment are provided in Table 1. Vaccine Safety No serious adverse events were noted, and no prespecified trial halting rules were met.

As noted above, one participant in the 25-μg group was withdrawn because of an unsolicited adverse event, transient urticaria, judged to be related to the first vaccination. Figure 1. Figure 1.

Systemic and Local Adverse Events. The severity of solicited adverse events was graded as mild, moderate, or severe (see Table S1).After the first vaccination, solicited systemic adverse events were reported by 5 participants (33%) in the 25-μg group, 10 (67%) in the 100-μg group, and 8 (53%) in the 250-μg group. All were mild or moderate in severity (Figure 1 and Table S2).

Solicited systemic adverse events were more common after the second vaccination and occurred in 7 of 13 participants (54%) in the 25-μg group, all 15 in the 100-μg group, and all 14 in the 250-μg group, with 3 of those participants (21%) reporting one or more severe events. None of the participants had fever after the first vaccination. After the second vaccination, no participants in the 25-μg group, 6 (40%) in the 100-μg group, and 8 (57%) in the 250-μg group reported fever.

One of the events (maximum temperature, 39.6°C) in the 250-μg group was graded severe. (Additional details regarding adverse events for that participant are provided in the Supplementary Appendix.) Local adverse events, when present, were nearly all mild or moderate, and pain at the injection site was common. Across both vaccinations, solicited systemic and local adverse events that occurred in more than half the participants included fatigue, chills, headache, myalgia, and pain at the injection site.

Evaluation of safety clinical laboratory values of grade 2 or higher and unsolicited adverse events revealed no patterns of concern (Supplementary Appendix and Table S3). SARS-CoV-2 Binding Antibody Responses Table 2. Table 2.

Geometric Mean Humoral Immunogenicity Assay Responses to mRNA-1273 in Participants and in Convalescent Serum Specimens. Figure 2. Figure 2.

SARS-CoV-2 Antibody and Neutralization Responses. Shown are geometric mean reciprocal end-point enzyme-linked immunosorbent assay (ELISA) IgG titers to S-2P (Panel A) and receptor-binding domain (Panel B), PsVNA ID50 responses (Panel C), and live virus PRNT80 responses (Panel D). In Panel A and Panel B, boxes and horizontal bars denote interquartile range (IQR) and median area under the curve (AUC), respectively.

Whisker endpoints are equal to the maximum and minimum values below or above the median ±1.5 times the IQR. The convalescent serum panel includes specimens from 41 participants. Red dots indicate the 3 specimens that were also tested in the PRNT assay.

The other 38 specimens were used to calculate summary statistics for the box plot in the convalescent serum panel. In Panel C, boxes and horizontal bars denote IQR and median ID50, respectively. Whisker end points are equal to the maximum and minimum values below or above the median ±1.5 times the IQR.

In the convalescent serum panel, red dots indicate the 3 specimens that were also tested in the PRNT assay. The other 38 specimens were used to calculate summary statistics for the box plot in the convalescent panel. In Panel D, boxes and horizontal bars denote IQR and median PRNT80, respectively.

Whisker end points are equal to the maximum and minimum values below or above the median ±1.5 times the IQR. The three convalescent serum specimens were also tested in ELISA and PsVNA assays. Because of the time-intensive nature of the PRNT assay, for this preliminary report, PRNT results were available only for the 25-μg and 100-μg dose groups.Binding antibody IgG geometric mean titers (GMTs) to S-2P increased rapidly after the first vaccination, with seroconversion in all participants by day 15 (Table 2 and Figure 2A).

Dose-dependent responses to the first and second vaccinations were evident. Receptor-binding domain–specific antibody responses were similar in pattern and magnitude (Figure 2B). For both assays, the median magnitude of antibody responses after the first vaccination in the 100-μg and 250-μg dose groups was similar to the median magnitude in convalescent serum specimens, and in all dose groups the median magnitude after the second vaccination was in the upper quartile of values in the convalescent serum specimens.

The S-2P ELISA GMTs at day 57 (299,751 [95% confidence interval {CI}, 206,071 to 436,020] in the 25-μg group, 782,719 [95% CI, 619,310 to 989,244] in the 100-μg group, and 1,192,154 [95% CI, 924,878 to 1,536,669] in the 250-μg group) exceeded that in the convalescent serum specimens (142,140 [95% CI, 81,543 to 247,768]). SARS-CoV-2 Neutralization Responses No participant had detectable PsVNA responses before vaccination. After the first vaccination, PsVNA responses were detected in less than half the participants, and a dose effect was seen (50% inhibitory dilution [ID50].

Figure 2C, Fig. S8, and Table 2. 80% inhibitory dilution [ID80].

Fig. S2 and Table S6). However, after the second vaccination, PsVNA responses were identified in serum samples from all participants.

The lowest responses were in the 25-μg dose group, with a geometric mean ID50 of 112.3 (95% CI, 71.2 to 177.1) at day 43. The higher responses in the 100-μg and 250-μg groups were similar in magnitude (geometric mean ID50, 343.8 [95% CI, 261.2 to 452.7] and 332.2 [95% CI, 266.3 to 414.5], respectively, at day 43). These responses were similar to values in the upper half of the distribution of values for convalescent serum specimens.

Before vaccination, no participant had detectable 80% live-virus neutralization at the highest serum concentration tested (1:8 dilution) in the PRNT assay. At day 43, wild-type virus–neutralizing activity capable of reducing SARS-CoV-2 infectivity by 80% or more (PRNT80) was detected in all participants, with geometric mean PRNT80 responses of 339.7 (95% CI, 184.0 to 627.1) in the 25-μg group and 654.3 (95% CI, 460.1 to 930.5) in the 100-μg group (Figure 2D). Neutralizing PRNT80 average responses were generally at or above the values of the three convalescent serum specimens tested in this assay.

Good agreement was noted within and between the values from binding assays for S-2P and receptor-binding domain and neutralizing activity measured by PsVNA and PRNT (Figs. S3 through S7), which provides orthogonal support for each assay in characterizing the humoral response induced by mRNA-1273. SARS-CoV-2 T-Cell Responses The 25-μg and 100-μg doses elicited CD4 T-cell responses (Figs.

S9 and S10) that on stimulation by S-specific peptide pools were strongly biased toward expression of Th1 cytokines (tumor necrosis factor α >. Interleukin 2 >. Interferon γ), with minimal type 2 helper T-cell (Th2) cytokine expression (interleukin 4 and interleukin 13).

CD8 T-cell responses to S-2P were detected at low levels after the second vaccination in the 100-μg dose group (Fig. S11).Patients Figure 1. Figure 1.

Enrollment and Randomization. Of the 1107 patients who were assessed for eligibility, 1063 underwent randomization. 541 were assigned to the remdesivir group and 522 to the placebo group (Figure 1).

Of those assigned to receive remdesivir, 531 patients (98.2%) received the treatment as assigned. Forty-nine patients had remdesivir treatment discontinued before day 10 because of an adverse event or a serious adverse event other than death (36 patients) or because the patient withdrew consent (13). Of those assigned to receive placebo, 518 patients (99.2%) received placebo as assigned.

Fifty-three patients discontinued placebo before day 10 because of an adverse event or a serious adverse event other than death (36 patients), because the patient withdrew consent (15), or because the patient was found to be ineligible for trial enrollment (2). As of April 28, 2020, a total of 391 patients in the remdesivir group and 340 in the placebo group had completed the trial through day 29, recovered, or died. Eight patients who received remdesivir and 9 who received placebo terminated their participation in the trial before day 29.

There were 132 patients in the remdesivir group and 169 in the placebo group who had not recovered and had not completed the day 29 follow-up visit. The analysis population included 1059 patients for whom we have at least some postbaseline data available (538 in the remdesivir group and 521 in the placebo group). Four of the 1063 patients were not included in the primary analysis because no postbaseline data were available at the time of the database freeze.

Table 1. Table 1. Demographic and Clinical Characteristics at Baseline.

The mean age of patients was 58.9 years, and 64.3% were male (Table 1). On the basis of the evolving epidemiology of Covid-19 during the trial, 79.8% of patients were enrolled at sites in North America, 15.3% in Europe, and 4.9% in Asia (Table S1). Overall, 53.2% of the patients were white, 20.6% were black, 12.6% were Asian, and 13.6% were designated as other or not reported.

249 (23.4%) were Hispanic or Latino. Most patients had either one (27.0%) or two or more (52.1%) of the prespecified coexisting conditions at enrollment, most commonly hypertension (49.6%), obesity (37.0%), and type 2 diabetes mellitus (29.7%). The median number of days between symptom onset and randomization was 9 (interquartile range, 6 to 12).

Nine hundred forty-three (88.7%) patients had severe disease at enrollment as defined in the Supplementary Appendix. 272 (25.6%) patients met category 7 criteria on the ordinal scale, 197 (18.5%) category 6, 421 (39.6%) category 5, and 127 (11.9%) category 4. There were 46 (4.3%) patients who had missing ordinal scale data at enrollment.

No substantial imbalances in baseline characteristics were observed between the remdesivir group and the placebo group. Primary Outcome Figure 2. Figure 2.

Kaplan–Meier Estimates of Cumulative Recoveries. Cumulative recovery estimates are shown in the overall population (Panel A), in patients with a baseline score of 4 on the ordinal scale (not receiving oxygen. Panel B), in those with a baseline score of 5 (receiving oxygen.

Panel C), in those with a baseline score of 6 (receiving high-flow oxygen or noninvasive mechanical ventilation. Panel D), and in those with a baseline score of 7 (receiving mechanical ventilation or ECMO. Panel E).

Table 2. Table 2. Outcomes Overall and According to Score on the Ordinal Scale in the Intention-to-Treat Population.

Figure 3. Figure 3. Time to Recovery According to Subgroup.

The widths of the confidence intervals have not been adjusted for multiplicity and therefore cannot be used to infer treatment effects. Race and ethnic group were reported by the patients. Patients in the remdesivir group had a shorter time to recovery than patients in the placebo group (median, 11 days, as compared with 15 days.

Rate ratio for recovery, 1.32. 95% confidence interval [CI], 1.12 to 1.55. P<0.001.

1059 patients (Figure 2 and Table 2). Among patients with a baseline ordinal score of 5 (421 patients), the rate ratio for recovery was 1.47 (95% CI, 1.17 to 1.84). Among patients with a baseline score of 4 (127 patients) and those with a baseline score of 6 (197 patients), the rate ratio estimates for recovery were 1.38 (95% CI, 0.94 to 2.03) and 1.20 (95% CI, 0.79 to 1.81), respectively.

For those receiving mechanical ventilation or ECMO at enrollment (baseline ordinal scores of 7. 272 patients), the rate ratio for recovery was 0.95 (95% CI, 0.64 to 1.42). A test of interaction of treatment with baseline score on the ordinal scale was not significant.

An analysis adjusting for baseline ordinal score as a stratification variable was conducted to evaluate the overall effect (of the percentage of patients in each ordinal score category at baseline) on the primary outcome. This adjusted analysis produced a similar treatment-effect estimate (rate ratio for recovery, 1.31. 95% CI, 1.12 to 1.54.

1017 patients). Table S2 in the Supplementary Appendix shows results according to the baseline severity stratum of mild-to-moderate as compared with severe. Patients who underwent randomization during the first 10 days after the onset of symptoms had a rate ratio for recovery of 1.28 (95% CI, 1.05 to 1.57.

664 patients), whereas patients who underwent randomization more than 10 days after the onset of symptoms had a rate ratio for recovery of 1.38 (95% CI, 1.05 to 1.81. 380 patients) (Figure 3). Key Secondary Outcome The odds of improvement in the ordinal scale score were higher in the remdesivir group, as determined by a proportional odds model at the day 15 visit, than in the placebo group (odds ratio for improvement, 1.50.

95% CI, 1.18 to 1.91. P=0.001. 844 patients) (Table 2 and Fig.

S5). Mortality was numerically lower in the remdesivir group than in the placebo group, but the difference was not significant (hazard ratio for death, 0.70. 95% CI, 0.47 to 1.04.

1059 patients). The Kaplan–Meier estimates of mortality by 14 days were 7.1% and 11.9% in the remdesivir and placebo groups, respectively (Table 2). The Kaplan–Meier estimates of mortality by 28 days are not reported in this preliminary analysis, given the large number of patients that had yet to complete day 29 visits.

An analysis with adjustment for baseline ordinal score as a stratification variable showed a hazard ratio for death of 0.74 (95% CI, 0.50 to 1.10). Safety Outcomes Serious adverse events occurred in 114 patients (21.1%) in the remdesivir group and 141 patients (27.0%) in the placebo group (Table S3). 4 events (2 in each group) were judged by site investigators to be related to remdesivir or placebo.

There were 28 serious respiratory failure adverse events in the remdesivir group (5.2% of patients) and 42 in the placebo group (8.0% of patients). Acute respiratory failure, hypotension, viral pneumonia, and acute kidney injury were slightly more common among patients in the placebo group. No deaths were considered to be related to treatment assignment, as judged by the site investigators.

Grade 3 or 4 adverse events occurred in 156 patients (28.8%) in the remdesivir group and in 172 in the placebo group (33.0%) (Table S4). The most common adverse events in the remdesivir group were anemia or decreased hemoglobin (43 events [7.9%], as compared with 47 [9.0%] in the placebo group). Acute kidney injury, decreased estimated glomerular filtration rate or creatinine clearance, or increased blood creatinine (40 events [7.4%], as compared with 38 [7.3%]).

Pyrexia (27 events [5.0%], as compared with 17 [3.3%]). Hyperglycemia or increased blood glucose level (22 events [4.1%], as compared with 17 [3.3%]). And increased aminotransferase levels including alanine aminotransferase, aspartate aminotransferase, or both (22 events [4.1%], as compared with 31 [5.9%]).

Otherwise, the incidence of adverse events was not found to be significantly different between the remdesivir group and the placebo group.Announced on May 15, Operation Warp Speed (OWS) — a partnership of the Department of Health and Human Services (HHS), the Department of Defense (DOD), and the private sector — aims to accelerate control of the Covid-19 pandemic by advancing development, manufacturing, and distribution of vaccines, therapeutics, and diagnostics. OWS is providing support to promising candidates and enabling the expeditious, parallel execution of the necessary steps toward approval or authorization of safe products by the Food and Drug Administration (FDA).The partnership grew out of an acknowledged need to fundamentally restructure the way the U.S. Government typically supports product development and vaccine distribution.

The initiative was premised on setting a “stretch goal” — one that initially seemed impossible but that is becoming increasingly achievable.The concept of an integrated structure for Covid-19 countermeasure research and development across the U.S. Government was based on experience with Zika and the Zika Leadership Group led by the National Institutes of Health (NIH) and the assistant secretary for preparedness and response (ASPR). One of us (M.S.) serves as OWS chief advisor.

We are drawing on expertise from the NIH, ASPR, the Centers for Disease Control and Prevention (CDC), the Biomedical Advanced Research and Development Authority (BARDA), and the DOD, including the Joint Program Executive Office for Chemical, Biological, Radiological and Nuclear Defense and the Defense Advanced Research Projects Agency. OWS has engaged experts in all critical aspects of medical countermeasure research, development, manufacturing, and distribution to work in close coordination.The initiative set ambitious objectives. To deliver tens of millions of doses of a SARS-CoV-2 vaccine — with demonstrated safety and efficacy, and approved or authorized by the FDA for use in the U.S.

Population — beginning at the end of 2020 and to have as many as 300 million doses of such vaccines available and deployed by mid-2021. The pace and scope of such a vaccine effort are unprecedented. The 2014 West African Ebola virus epidemic spurred rapid vaccine development, but though preclinical data existed before the outbreak, a period of 12 months was required to progress from phase 1 first-in-human trials to phase 3 efficacy trials.

OWS aims to compress this time frame even further. SARS-CoV-2 vaccine development began in January, phase 1 clinical studies in March, and the first phase 3 trials in July. Our objectives are based on advances in vaccine platform technology, improved understanding of safe and efficacious vaccine design, and similarities between the SARS-CoV-1 and SARS-CoV-2 disease mechanisms.OWS’s role is to enable, accelerate, harmonize, and advise the companies developing the selected vaccines.

The companies will execute the clinical or process development and manufacturing plans, while OWS leverages the full capacity of the U.S. Government to ensure that no technical, logistic, or financial hurdles hinder vaccine development or deployment.OWS selected vaccine candidates on the basis of four criteria. We required candidates to have robust preclinical data or early-stage clinical trial data supporting their potential for clinical safety and efficacy.

Candidates had to have the potential, with our acceleration support, to enter large phase 3 field efficacy trials this summer or fall (July to November 2020) and, assuming continued active transmission of the virus, to deliver efficacy outcomes by the end of 2020 or the first half of 2021. Candidates had to be based on vaccine-platform technologies permitting fast and effective manufacturing, and their developers had to demonstrate the industrial process scalability, yields, and consistency necessary to reliably produce more than 100 million doses by mid-2021. Finally, candidates had to use one of four vaccine-platform technologies that we believe are the most likely to yield a safe and effective vaccine against Covid-19.

The mRNA platform, the replication-defective live-vector platform, the recombinant-subunit-adjuvanted protein platform, or the attenuated replicating live-vector platform.OWS’s strategy relies on a few key principles. First, we sought to build a diverse project portfolio that includes two vaccine candidates based on each of the four platform technologies. Such diversification mitigates the risk of failure due to safety, efficacy, industrial manufacturability, or scheduling factors and may permit selection of the best vaccine platform for each subpopulation at risk for contracting or transmitting Covid-19, including older adults, frontline and essential workers, young adults, and pediatric populations.

In addition, advancing eight vaccines in parallel will increase the chances of delivering 300 million doses in the first half of 2021.Second, we must accelerate vaccine program development without compromising safety, efficacy, or product quality. Clinical development, process development, and manufacturing scale-up can be substantially accelerated by running all streams, fully resourced, in parallel. Doing so requires taking on substantial financial risk, as compared with the conventional sequential development approach.

OWS will maximize the size of phase 3 trials (30,000 to 50,000 participants each) and optimize trial-site location by consulting daily epidemiologic and disease-forecasting models to ensure the fastest path to an efficacy readout. Such large trials also increase the safety data set for each candidate vaccine.With heavy up-front investment, companies can conduct clinical operations and site preparation for these phase 3 efficacy trials even as they file their Investigational New Drug application (IND) for their phase 1 studies, thereby ensuring immediate initiation of phase 3 when they get a green light from the FDA. To permit appropriate comparisons among the vaccine candidates and to optimize vaccine utilization after approval by the FDA, the phase 3 trial end points and assay readouts have been harmonized through a collaborative effort involving the National Institute of Allergy and Infectious Diseases (NIAID), the Coronavirus Prevention Network, OWS, and the sponsor companies.Finally, OWS is supporting the companies financially and technically to commence process development and scale up manufacturing while their vaccines are in preclinical or very early clinical stages.

To ensure that industrial processes are set, running, and validated for FDA inspection when phase 3 trials end, OWS is also supporting facility building or refurbishing, equipment fitting, staff hiring and training, raw-material sourcing, technology transfer and validation, bulk product processing into vials, and acquisition of ample vials, syringes, and needles for each vaccine candidate. We aim to have stockpiled, at OWS’s expense, a few tens of millions of vaccine doses that could be swiftly deployed once FDA approval is obtained.This strategy aims to accelerate vaccine development without curtailing the critical steps required by sound science and regulatory standards. The FDA recently reissued guidance and standards that will be used to assess each vaccine for a Biologics License Application (BLA).

Alternatively, the agency could decide to issue an Emergency Use Authorization to permit vaccine administration before all BLA procedures are completed.Of the eight vaccines in OWS’s portfolio, six have been announced and partnerships executed with the companies. Moderna and Pfizer/BioNTech (both mRNA), AstraZeneca and Janssen (both replication-defective live-vector), and Novavax and Sanofi/GSK (both recombinant-subunit-adjuvanted protein). These candidates cover three of the four platform technologies and are currently in clinical trials.

The remaining two candidates will enter trials soon.Moderna developed its RNA vaccine in collaboration with the NIAID, began its phase 1 trial in March, recently published encouraging safety and immunogenicity data,1 and entered phase 3 on July 27. Pfizer and BioNTech’s RNA vaccine also produced encouraging phase 1 results2 and started its phase 3 trial on July 27. The ChAdOx replication-defective live-vector vaccine developed by AstraZeneca and Oxford University is in phase 3 trials in the United Kingdom, Brazil, and South Africa, and it should enter U.S.

Phase 3 trials in August.3 The Janssen Ad26 Covid-19 replication-defective live-vector vaccine has demonstrated excellent protection in nonhuman primate models and began its U.S. Phase 1 trial on July 27. It should be in phase 3 trials in mid-September.

Novavax completed a phase 1 trial of its recombinant-subunit-adjuvanted protein vaccine in Australia and should enter phase 3 trials in the United States by the end of September.4 Sanofi/GSK is completing preclinical development steps and plans to commence a phase 1 trial in early September and to be well into phase 3 by year’s end.5On the process-development front, the RNA vaccines are already being manufactured at scale. The other candidates are well advanced in their scale-up development, and manufacturing sites are being refurbished.While development and manufacturing proceed, the HHS–DOD partnership is laying the groundwork for vaccine distribution, subpopulation prioritization, financing, and logistic support. We are working with bioethicists and experts from the NIH, the CDC, BARDA, and the Centers for Medicare and Medicaid Services to address these critical issues.

We will receive recommendations from the CDC Advisory Committee on Immunization Practices, and we are working to ensure that the most vulnerable and at-risk persons will receive vaccine doses once they are ready. Prioritization will also depend on the relative performance of each vaccine and its suitability for particular populations. Because some technologies have limited previous data on safety in humans, the long-term safety of these vaccines will be carefully assessed using pharmacovigilance surveillance strategies.No scientific enterprise could guarantee success by January 2021, but the strategic decisions and choices we’ve made, the support the government has provided, and the accomplishments to date make us optimistic that we will succeed in this unprecedented endeavor.Trial Design and Oversight We conducted a randomized, double-blind, placebo-controlled trial to evaluate postexposure prophylaxis with hydroxychloroquine after exposure to Covid-19.12 We randomly assigned participants in a 1:1 ratio to receive either hydroxychloroquine or placebo.

Participants had known exposure (by participant report) to a person with laboratory-confirmed Covid-19, whether as a household contact, a health care worker, or a person with other occupational exposures. Trial enrollment began on March 17, 2020, with an eligibility threshold to enroll within 3 days after exposure. The objective was to intervene before the median incubation period of 5 to 6 days.

Because of limited access to prompt testing, health care workers could initially be enrolled on the basis of presumptive high-risk exposure to patients with pending tests. However, on March 23, eligibility was changed to exposure to a person with a positive polymerase-chain-reaction (PCR) assay for SARS-CoV-2, with the eligibility window extended to within 4 days after exposure. This trial was approved by the institutional review board at the University of Minnesota and conducted under a Food and Drug Administration Investigational New Drug application.

In Canada, the trial was approved by Health Canada. Ethics approvals were obtained from the Research Institute of the McGill University Health Centre, the University of Manitoba, and the University of Alberta. Participants We included participants who had household or occupational exposure to a person with confirmed Covid-19 at a distance of less than 6 ft for more than 10 minutes while wearing neither a face mask nor an eye shield (high-risk exposure) or while wearing a face mask but no eye shield (moderate-risk exposure).

Participants were excluded if they were younger than 18 years of age, were hospitalized, or met other exclusion criteria (see the Supplementary Appendix, available with the full text of this article at NEJM.org). Persons with symptoms of Covid-19 or with PCR-proven SARS-CoV-2 infection were excluded from this prevention trial but were separately enrolled in a companion clinical trial to treat early infection. Setting Recruitment was performed primarily with the use of social media outreach as well as traditional media platforms.

Participants were enrolled nationwide in the United States and in the Canadian provinces of Quebec, Manitoba, and Alberta. Participants enrolled themselves through a secure Internet-based survey using the Research Electronic Data Capture (REDCap) system.13 After participants read the consent form, their comprehension of its contents was assessed. Participants provided a digitally captured signature to indicate informed consent.

We sent follow-up e-mail surveys on days 1, 5, 10, and 14. A survey at 4 to 6 weeks asked about any follow-up testing, illness, or hospitalizations. Participants who did not respond to follow-up surveys received text messages, e-mails, telephone calls, or a combination of these to ascertain their outcomes.

When these methods were unsuccessful, the emergency contact provided by the enrollee was contacted to determine the participant’s illness and vital status. When all communication methods were exhausted, Internet searches for obituaries were performed to ascertain vital status. Interventions Randomization occurred at research pharmacies in Minneapolis and Montreal.

The trial statisticians generated a permuted-block randomization sequence using variably sized blocks of 2, 4, or 8, with stratification according to country. A research pharmacist sequentially assigned participants. The assignments were concealed from investigators and participants.

Only pharmacies had access to the randomization sequence. Hydroxychloroquine sulfate or placebo was dispensed and shipped overnight to participants by commercial courier. The dosing regimen for hydroxychloroquine was 800 mg (4 tablets) once, then 600 mg (3 tablets) 6 to 8 hours later, then 600 mg (3 tablets) daily for 4 more days for a total course of 5 days (19 tablets total).

If participants had gastrointestinal upset, they were advised to divide the daily dose into two or three doses. We chose this hydroxychloroquine dosing regimen on the basis of pharmacokinetic simulations to achieve plasma concentrations above the SARS-CoV-2 in vitro half maximal effective concentration for 14 days.14 Placebo folate tablets, which were similar in appearance to the hydroxychloroquine tablets, were prescribed as an identical regimen for the control group. Rising Pharmaceuticals provided a donation of hydroxychloroquine, and some hydroxychloroquine was purchased.

Outcomes The primary outcome was prespecified as symptomatic illness confirmed by a positive molecular assay or, if testing was unavailable, Covid-19–related symptoms. We assumed that health care workers would have access to Covid-19 testing if symptomatic. However, access to testing was limited throughout the trial period.

Covid-19–related symptoms were based on U.S. Council for State and Territorial Epidemiologists criteria for confirmed cases (positivity for SARS-Cov-2 on PCR assay), probable cases (the presence of cough, shortness of breath, or difficulty breathing, or the presence of two or more symptoms of fever, chills, rigors, myalgia, headache, sore throat, and new olfactory and taste disorders), and possible cases (the presence of one or more compatible symptoms, which could include diarrhea).15 All the participants had epidemiologic linkage,15 per trial eligibility criteria. Four infectious disease physicians who were unaware of the trial-group assignments reviewed symptomatic participants to generate a consensus with respect to whether their condition met the case definition.15 Secondary outcomes included the incidence of hospitalization for Covid-19 or death, the incidence of PCR-confirmed SARS-CoV-2 infection, the incidence of Covid-19 symptoms, the incidence of discontinuation of the trial intervention owing to any cause, and the severity of symptoms (if any) at days 5 and 14 according to a visual analogue scale (scores ranged from 0 [no symptoms] to 10 [severe symptoms]).

Data on adverse events were also collected with directed questioning for common side effects along with open-ended free text. Outcome data were measured within 14 days after trial enrollment. Outcome data including PCR testing results, possible Covid-19–related symptoms, adherence to the trial intervention, side effects, and hospitalizations were all collected through participant report.

Details of trial conduct are provided in the protocol and statistical analysis plan, available at NEJM.org. Sample Size We anticipated that illness compatible with Covid-19 would develop in 10% of close contacts exposed to Covid-19.9 Using Fisher’s exact method with a 50% relative effect size to reduce new symptomatic infections, a two-sided alpha of 0.05, and 90% power, we estimated that 621 persons would need to be enrolled in each group. With a pragmatic, Internet-based, self-referral recruitment strategy, we planned for a 20% incidence of attrition by increasing the sample size to 750 participants per group.

We specified a priori that participants who were already symptomatic on day 1 before receiving hydroxychloroquine or placebo would be excluded from the prophylaxis trial and would instead be separately enrolled in the companion symptomatic treatment trial. Because the estimates for both incident symptomatic Covid-19 after an exposure and loss to follow-up were relatively unknown in early March 2020,9 the protocol prespecified a sample-size reestimation at the second interim analysis. This reestimation, which used the incidence of new infections in the placebo group and the observed percentage of participants lost to follow-up, was aimed at maintaining the ability to detect an effect size of a 50% relative reduction in new symptomatic infections.

Interim Analyses An independent data and safety monitoring board externally reviewed the data after 25% and 50% of the participants had completed 14 days of follow-up. Stopping guidelines were provided to the data and safety monitoring board with the use of a Lan–DeMets spending function analogue of the O’Brien–Fleming boundaries for the primary outcome. A conditional power analysis was performed at the second and third interim analysis with the option of early stopping for futility.

At the second interim analysis on April 22, 2020, the sample size was reduced to 956 participants who could be evaluated with 90% power on the basis of the higher-than-expected event rate of infections in the control group. At the third interim analysis on May 6, the trial was halted on the basis of a conditional power of less than 1%, since it was deemed futile to continue. Statistical Analysis We assessed the incidence of Covid-19 disease by day 14 with Fisher’s exact test.

Secondary outcomes with respect to percentage of patients were also compared with Fisher’s exact test. Among participants in whom incident illness compatible with Covid-19 developed, we summarized the symptom severity score at day 14 with the median and interquartile range and assessed the distributions with a Kruskal–Wallis test. We conducted all analyses with SAS software, version 9.4 (SAS Institute), according to the intention-to-treat principle, with two-sided type I error with an alpha of 0.05.

For participants with missing outcome data, we conducted a sensitivity analysis with their outcomes excluded or included as an event. Subgroups that were specified a priori included type of contact (household vs. Health care), days from exposure to enrollment, age, and sex.Trial Design and Oversight The RECOVERY trial was designed to evaluate the effects of potential treatments in patients hospitalized with Covid-19 at 176 National Health Service organizations in the United Kingdom and was supported by the National Institute for Health Research Clinical Research Network.

(Details regarding this trial are provided in the Supplementary Appendix, available with the full text of this article at NEJM.org.) The trial is being coordinated by the Nuffield Department of Population Health at the University of Oxford, the trial sponsor. Although the randomization of patients to receive dexamethasone, hydroxychloroquine, or lopinavir–ritonavir has now been stopped, the trial continues randomization to groups receiving azithromycin, tocilizumab, or convalescent plasma. Hospitalized patients were eligible for the trial if they had clinically suspected or laboratory-confirmed SARS-CoV-2 infection and no medical history that might, in the opinion of the attending clinician, put patients at substantial risk if they were to participate in the trial.

Initially, recruitment was limited to patients who were at least 18 years of age, but the age limit was removed starting on May 9, 2020. Pregnant or breast-feeding women were eligible. Written informed consent was obtained from all the patients or from a legal representative if they were unable to provide consent.

The trial was conducted in accordance with the principles of the Good Clinical Practice guidelines of the International Conference on Harmonisation and was approved by the U.K. Medicines and Healthcare Products Regulatory Agency and the Cambridge East Research Ethics Committee. The protocol with its statistical analysis plan is available at NEJM.org and on the trial website at www.recoverytrial.net.

The initial version of the manuscript was drafted by the first and last authors, developed by the writing committee, and approved by all members of the trial steering committee. The funders had no role in the analysis of the data, in the preparation or approval of the manuscript, or in the decision to submit the manuscript for publication. The first and last members of the writing committee vouch for the completeness and accuracy of the data and for the fidelity of the trial to the protocol and statistical analysis plan.

Randomization We collected baseline data using a Web-based case-report form that included demographic data, the level of respiratory support, major coexisting illnesses, suitability of the trial treatment for a particular patient, and treatment availability at the trial site. Randomization was performed with the use of a Web-based system with concealment of the trial-group assignment. Eligible and consenting patients were assigned in a 2:1 ratio to receive either the usual standard of care alone or the usual standard of care plus oral or intravenous dexamethasone (at a dose of 6 mg once daily) for up to 10 days (or until hospital discharge if sooner) or to receive one of the other suitable and available treatments that were being evaluated in the trial.

For some patients, dexamethasone was unavailable at the hospital at the time of enrollment or was considered by the managing physician to be either definitely indicated or definitely contraindicated. These patients were excluded from entry in the randomized comparison between dexamethasone and usual care and hence were not included in this report. The randomly assigned treatment was prescribed by the treating clinician.

Patients and local members of the trial staff were aware of the assigned treatments. Procedures A single online follow-up form was to be completed when the patients were discharged or had died or at 28 days after randomization, whichever occurred first. Information was recorded regarding the patients’ adherence to the assigned treatment, receipt of other trial treatments, duration of admission, receipt of respiratory support (with duration and type), receipt of renal support, and vital status (including the cause of death).

In addition, we obtained routine health care and registry data, including information on vital status (with date and cause of death), discharge from the hospital, and respiratory and renal support therapy. Outcome Measures The primary outcome was all-cause mortality within 28 days after randomization. Further analyses were specified at 6 months.

Secondary outcomes were the time until discharge from the hospital and, among patients not receiving invasive mechanical ventilation at the time of randomization, subsequent receipt of invasive mechanical ventilation (including extracorporeal membrane oxygenation) or death. Other prespecified clinical outcomes included cause-specific mortality, receipt of renal hemodialysis or hemofiltration, major cardiac arrhythmia (recorded in a subgroup), and receipt and duration of ventilation. Statistical Analysis As stated in the protocol, appropriate sample sizes could not be estimated when the trial was being planned at the start of the Covid-19 pandemic.

As the trial progressed, the trial steering committee, whose members were unaware of the results of the trial comparisons, determined that if 28-day mortality was 20%, then the enrollment of at least 2000 patients in the dexamethasone group and 4000 in the usual care group would provide a power of at least 90% at a two-sided P value of 0.01 to detect a clinically relevant proportional reduction of 20% (an absolute difference of 4 percentage points) between the two groups. Consequently, on June 8, 2020, the steering committee closed recruitment to the dexamethasone group, since enrollment had exceeded 2000 patients. For the primary outcome of 28-day mortality, the hazard ratio from Cox regression was used to estimate the mortality rate ratio.

Among the few patients (0.1%) who had not been followed for 28 days by the time of the data cutoff on July 6, 2020, data were censored either on that date or on day 29 if the patient had already been discharged. That is, in the absence of any information to the contrary, these patients were assumed to have survived for 28 days. Kaplan–Meier survival curves were constructed to show cumulative mortality over the 28-day period.

Cox regression was used to analyze the secondary outcome of hospital discharge within 28 days, with censoring of data on day 29 for patients who had died during hospitalization. For the prespecified composite secondary outcome of invasive mechanical ventilation or death within 28 days (among patients who were not receiving invasive mechanical ventilation at randomization), the precise date of invasive mechanical ventilation was not available, so a log-binomial regression model was used to estimate the risk ratio. Table 1.

Table 1. Characteristics of the Patients at Baseline, According to Treatment Assignment and Level of Respiratory Support. Through the play of chance in the unstratified randomization, the mean age was 1.1 years older among patients in the dexamethasone group than among those in the usual care group (Table 1).

To account for this imbalance in an important prognostic factor, estimates of rate ratios were adjusted for the baseline age in three categories (<70 years, 70 to 79 years, and ≥80 years). This adjustment was not specified in the first version of the statistical analysis plan but was added once the imbalance in age became apparent. Results without age adjustment (corresponding to the first version of the analysis plan) are provided in the Supplementary Appendix.

Prespecified analyses of the primary outcome were performed in five subgroups, as defined by characteristics at randomization. Age, sex, level of respiratory support, days since symptom onset, and predicted 28-day mortality risk. (One further prespecified subgroup analysis regarding race will be conducted once the data collection has been completed.) In prespecified subgroups, we estimated rate ratios (or risk ratios in some analyses) and their confidence intervals using regression models that included an interaction term between the treatment assignment and the subgroup of interest.

Chi-square tests for linear trend across the subgroup-specific log estimates were then performed in accordance with the prespecified plan. All P values are two-sided and are shown without adjustment for multiple testing. All analyses were performed according to the intention-to-treat principle.

The full database is held by the trial team, which collected the data from trial sites and performed the analyses at the Nuffield Department of Population Health, University of Oxford..

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