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Wednesday, September 22, 2021

New R.1 COVID-19 variant spreads quickly at Kentucky nursing home

 A new variant of the COVID-19 virus has been identified at a Kentucky nursing home, where it infected 45 residents and workers, many of whom were vaccinated.

The R.1 variant originated in Japan, and contains dangerous mutations that can improve “transmission, replication, and immune suppression,” a scientist wrote in Forbes Monday.

There are already more than 10,000 entries of the R.1 variant in a database used by researchers to track genomic material, infectious disease expert Dr. William Haseltine said.

The variant shares the highly-infectious D614G mutation that is present in other variants fueling new surges of the coronavirus, according to the doctor.

“R.1 is a variant to watch. It has established a foothold in both Japan and the United States,” Haseltine wrote.

The news comes days after the FDA approved booster vaccination shots for adults over 65 or anyone in poor health. The shots would be available six months after a second dose.

The agency said more research is needed about the effectiveness of booster shots against the Delta variant before it can green-light their use for the general public.

Nearly 4.7 million people worldwide, including 675,000 Americans, have been killed by COVID-19, according to health officials.

https://nypost.com/2021/09/21/covid-19-variant-r-1-spreads-quickly-at-kentucky-nursing-home/

Tuesday, September 21, 2021

Tenn. limiting monoclonal antibody treatment to unvaccinated residents

 In Tennessee, the patients first in line for the monoclonal antibody Covid-19 treatment are likely to be the ones who landed in the emergency room because they did not get vaccinated.

Extraordinary demand coupled with the federal government’s need to cap shipments of these scarce drugs has forced Tennessee health officials to recommend limiting the treatment to unvaccinated patients with the worst cases of Covid-19.

But doing so raises ethical questions, public health experts said, about who should get this treatment and who shouldn’t.

“For example, if a patient who had a heart transplant had received the vaccine but is still at risk of severe Covid-19 infection was denied access to antibody treatment that could have reduced the severity of their infection, how is this fair?” asked Dr. Sadiya Khan, an epidemiologist at the Northwestern University Feinberg School of Medicine.

Dr. Lisa Piercey, Tennessee’s top health official, agreed that the state’s “logical” decision is not likely to be popular.

“Clinically, it makes sense,” Piercey said Friday, The Tennessean reported. “But the doctor in me thinks about all these ‘what ifs?’ What if there is a super-high-risk older person, but they are not technically considered immunocompromised? Do they not get it but a 22-year-old unvaccinated person with asthma – they get it?”

Under the Tennessee recommendations, vaccinated people who are immunocompromised will also be eligible for the treatment, Piercey said.

Tennessee, which is following the guidance of the National Institutes of Health, appears to be the first state to recommend limiting monoclonal antibody treatment to Covid-19 patients who are unvaccinated or vaccinated but immunocompromised.

“What the state is doing is putting the highest risk patients first in line,” Dr. Karen Bloch of Vanderbilt University Medical Center said. “And not having a vaccine does place one at a higher risk of dying from Covid. So identifying those most at risk makes sense.”

Monoclonal antibody treatment lessens the severity of Covid-19 symptoms, and with more cases of the highly infectious delta variant, the demand for it has soared.

But in recent months, 70 percent of the country’s supply has gone to seven Southern states: Alabama, Florida, Texas, Mississippi, Tennessee, Georgia and Louisiana.

All but Louisiana are led by Republicans who have opposed mandating Covid-19 vaccinations. And all but Florida have below average Covid-19 vaccination rates.

“The recent increase in COVID-19 cases has caused a substantial rise in the utilization of monoclonal antibody drugs, particularly in areas of the country with low vaccination rates,” Dr. Daniel Skovronsky, Eli Lilly and Company’s chief scientific and medical officer, said in a recent statement.

Tennessee’s vaccination rate is 44.1 percent, which is one of the worst in the country, according to the latest Mayo Clinic statistics.

Last week the Biden administration ordered more doses from the two main suppliers, Regeneron and Eli Lilly and Company, and informed state officials it would start capping the shipments of the drug to make sure there’s enough for the rest of the country.

“Our supply is not unlimited,” White House spokeswoman Jen Psaki said. “And we believe it should be equitable across states across the country.”

That move drew immediate criticism from the Republican governors of Florida, Mississippi and Texas (Ron DeSantis, Tate Reeves and Greg Abbott).

DeSantis, in particular, has touted expensive monoclonal antibody treatments (about $2,100 a dose) but has refused to mandate the far-cheaper vaccines (between $10 and $20 a dose) or proven safety measures like wearing masks.

https://www.nbcnews.com/news/us-news/tennessee-limiting-monoclonal-antibody-treatment-unvaccinated-residents-n1279740

How largely untested AI algorithm crept into hundreds of hospitals

 Last spring, physicians like us were confused. COVID-19 was just starting its deadly journey around the world, afflicting our patients with severe lung infections, strokes, skin rashes, debilitating fatigue, and numerous other acute and chronic symptoms. Armed with outdated clinical intuitions, we were left disoriented by a disease shrouded in ambiguity.

In the midst of the uncertainty, Epic, a private electronic health record giant and a key purveyor of American health data, accelerated the deployment of a clinical prediction tool called the Deterioration Index. Built with a type of artificial intelligence called machine learning and in use at some hospitals prior to the pandemic, the index is designed to help physicians decide when to move a patient into or out of intensive care, and is influenced by factors like breathing rate and blood potassium level. Epic had been tinkering with the index for years but expanded its use during the pandemic. At hundreds of hospitals, including those in which we both work, a Deterioration Index score is prominently displayed on the chart of every patient admitted to the hospital.

The Deterioration Index is poised to upend a key cultural practice in medicine: triage. Loosely speaking, triage is an act of determining how sick a patient is at any given moment to prioritize treatment and limited resources. In the past, physicians have performed this task by rapidly interpreting a patient’s vital signs, physical exam findings, test results, and other data points, using heuristics learned through years of on-the-job medical training.

Ostensibly, the core assumption of the Deterioration Index is that traditional triage can be augmented, or perhaps replaced entirely, by machine learning and big data. Indeed, a study of 392 COVID-19 patients admitted to Michigan Medicine that the index was moderately successful at discriminating between low-risk patients and those who were at high-risk of being transferred to an ICU, getting placed on a ventilator, or dying while admitted to the hospital. But last year’s hurried rollout of the Deterioration Index also sets a worrisome precedent, and it illustrates the potential for such decision-support tools to propagate biases in medicine and change the ways in which doctors think about their patients.

The use of algorithms to support clinical decision-making isn’t new. But historically, these tools have been put into use only after a rigorous peer review of the raw data and statistical analyses used to develop them. Epic’s Deterioration Index, on the other hand, remains proprietary despite its widespread deployment. Although physicians are provided with a list of the variables used to calculate the index and a rough estimate of each variable’s impact on the score, we aren’t allowed under the hood to evaluate the raw data and calculations.

Furthermore, the Deterioration Index was not independently validated or peer-reviewed before the tool was rapidly deployed to America’s largest healthcare systems. Even now, there have been, to our knowledge, only two peer-reviewed published studies of the index. The deployment of a largely untested proprietary algorithm into clinical practice—with minimal understanding of the potential unintended consequences for patients or clinicians—raises a host of issues.

It remains unclear, for instance, what biases may be encoded into the index. Medicine already has a fraught history with race and gender disparities and biases. Studies have shown that, among other injustices, physicians underestimate the pain of minority patients and are less likely to refer women to total knee replacement surgery when it is warranted. Some clinical scores, including calculations commonly used to assess kidney and lung function, have traditionally been adjusted based on a patient’s race—a practice that many in the medical community now oppose. Without direct access to the equations underlying Epic’s Deterioration Index, or further external inquiry, it is impossible to know whether the index incorporates such race-adjusted scores in its own algorithm, potentially propagating biases.

Introducing machine learning into the triage process could fundamentally alter the way we teach medicine. It has the potential to improve inpatient care by highlighting new links between clinical data and outcomes—links that might otherwise have gone unnoticed. But it could also over-sensitize young physicians to the specific tests and health factors that the algorithm deems important; it could compromise trainees’ ability to hone their own clinical intuition. In essence, physicians in training would be learning medicine on Epic’s terms.

Thankfully, there are safeguards that can be relatively painlessly put in place. In 2015, the international Equator Network created a 22-point Tripod checklist to guide the responsible development, validation, and improvement of clinical prediction tools like the Deterioration Index. For example, it asks tool developers to provide details on how risk groups were created, report performance measures with confidence intervals, and discuss limitations of validation studies. Private health data brokers like Epic should always be held to this standard.

Now that its Deterioration Index is already being used in clinical settings, Epic should immediately release for peer review the underlying equations and the anonymized data sets it used for its internal validation so that doctors and health services researchers can better understand any potential implications they may have for health equity. There need to be clear communication channels to raise, discuss, and resolve any issues that emerge in peer review, including concerns about the score’s validity, prognostic value, bias, or unintended consequences. Companies like Epic should also engage more deliberately and openly with the physicians who use their algorithms; they should share information about the populations on which the algorithms were trained, the questions the algorithms are best equipped to answer, and the flaws the algorithms may carry. Caveats and warnings should be communicated clearly and quickly to all clinicians who use the indices.

The COVID-19 pandemic, having accelerated the widespread deployment of clinical prediction tools like the Deterioration Index, may herald a new coexistence between physicians and machines in the art of medicine. Now is the time to set the ground rules to ensure that this partnership helps us change medicine for the better, and not the worse.


Dr. Vishal Khetpal is a resident physician training in the Brown University Internal Medicine Program.

Dr. Nishant R. Shah is an assistant professor of medicine at the Alpert Medical School of Brown University and an assistant professor of health services, practice, and policy at the Brown University School of Public Health.

https://www.fastcompany.com/90641343/epic-deterioration-index-algorithm-pandemic-concerns

Nektar Up on Deal With Pfizer, Merck KGaA

 Nektar Therapeutics shares were up 5% to $17.10 after the company said it entered into a new oncology clinical collaboration with Merck KGaA and Pfizer Inc.

The deal is for the company to evaluate the maintenance regimen of NKTR-255, Nektar's interleukin-15 receptor agonist, in combination with avelumab, a PD-L1 inhibitor, in patients with locally advanced or metastatic urothelial carcinoma in a Phase II study.

NKTR-255 is wholly owned by Nektar and is currently being evaluated in two separate clinical studies in both liquid and solid tumors. The novel IL-15 agonist is designed to activate the IL-15 pathway to expand both natural killer cells and memory CD8+ T cell populations.

Avelumab, which is marketed in the U.S. as Bavencio, is co-developed and co-commercialized by Merck KGaA and Pfizer Inc.

Under the new collaboration, Merck KGaA and Pfizer Inc. will include the combination of NKTR-255 plus avelumab in the study. Nektar will supply NKTR-255 for the trial. Nektar and the Merck KGaA-Pfizer alliance will each maintain existing global commercial rights to their respective medicines. The study is expected to begin enrolling patients in the first quarter of 2022.

https://www.marketscreener.com/quote/stock/NEKTAR-THERAPEUTICS-45013433/news/Nektar-Therapeutics-Shares-Rise-5-on-Deal-With-Pfizer-Merck-KGaA-36480149/

America Has Been Flying Blind This Pandemic

 


The cover of the book Uncontrolled Spread, and a photo of Scott Gottlieb, MD

I recently finished reading Uncontrolled Spread, a new book by Scott Gottlieb, MD, which offers an incredible deep dive into what was and is still happening with the U.S. government's pandemic response. I believe Uncontrolled Spread will be the most authoritative book on the COVID-19 pandemic in the U.S. out of the many books that will be written.

From the beginning, Gottlieb has had an outlook on the COVID-19 pandemic that was both prophetic and personal. He carefully tracked the initial spread of the coronavirus from its early days in Wuhan, China, and then in Lombardy, Italy. Most of the country didn't take the pandemic seriously at that point, but Gottlieb -- who left his post as FDA commissioner in 2019 -- sounded the alarm. In January 2020, he warned that the outbreaks in other countries were previews of what would happen in the U.S. It's one of many predictions Gottlieb got right when so many were wrong.

One of the first places in the U.S. hit hard was a hospital where he had trained as a medical resident -- Elmhurst Hospital in Queens, where refrigerator trucks lined up outside to receive some of the earliest COVID-19 victims. He could personally feel the weight of the tragedy. Testing was a mess. In his book, Gottlieb does a root cause analysis. As he writes, the original sin of our pandemic response was relying on government bureaucracies to guide us using legacy systems that no one understood or dared to question.

The U.S. took a top-down approach that created bottlenecks, when what we needed was decentralized action that would allow for a nimble response. It began with a regulation that no doctor or medical center could test a person for COVID-19 -- even though they could easily do so -- unless their test had been authorized by the government. The test the CDC put out was flawed, but that was entirely avoidable. Moreover, any lab that wanted to develop a test needed a sample of the virus, which only the CDC could provide. Without a sample, there was no way to prove that COVID-19 tests would work. But, like an angry librarian who gets mad if you want to borrow a book, the regulators made it hard for labs and public health experts to do their jobs. This hamstrung the U.S. response, causing us to lag far behind other countries in testing. By the time we had testing, the virus was on the run and it was hard to catch up.

Without good information about the number of COVID-19 cases we were flying blind. U.S. public health officials used hospitalizations as a proxy indicator for the epidemic, but this didn't offer a complete or accurate picture of what was going on. Government doctors had been accustomed to relying on hospitalizations as a key indicator in the influenza-like surveillance system. But since it was a mild flu season and COVID-19 hospitalization are a lagging indicator, many, including all of our nation's top physician-public health officials, falsely concluded that we did not have widespread community transmission. But in hindsight, we obviously did. In fact, the coronavirus was seeded all over the country. Like sheep, the media and public health leaders got caught up in the debates, while being myopically dependent on "confirmed cases" on the Johns Hopkins COVID-19 map, as if two cases on a map really meant there were two cases. It didn't. Meanwhile, in the absence of data, political opinions filled the void and became louder over time.

Gottlieb argues that these critical mistakes are not just interesting tidbits of historical trivia. These are structural problems that desperately need to be fixed today. The CDC has consistently delivered tardy and inadequate data throughout this pandemic, leaving both the public and the medical community with few tools to fight it. He attributes this to an agency culture that has historically performed "high-scienced" and "retrospective reviews," as done in Morbidity and Mortality Weekly Report (MMWR).

Remarkably, the CDC, an agency with 21,000 employees, does not have much of a rapid response team. But in a pandemic, we need the CDC to deliver real-time data. Have you ever wondered why so many of our insights about COVID-19 come from Israel, and the best study about masks comes from Bangladesh? We spend more than $100 billion on taxpayer funded medical research each year in the U.S., yet the CDC has failed in its primary function to deliver data to guide our pandemic response.

Even today, as policymakers discuss COVID-19 vaccine booster shots, we don't have the information we need. We currently have about 100,000 Americans in the hospital with COVID-19. The CDC has data on the small subset of those who were vaccinated, including which vaccine they had, how long it's been since their shots, and whether they have any pre-existing conditions. Analyzing and sharing this information would help shape our booster plan and inform vaccinated Americans of their current risk. But sadly, the CDC is not providing this data.

One of Gottlieb's main book themes is that we need to stop treating pandemics as a boutique medical subject. The preparation for the next public health emergency needs to begin right now. Moreover, it needs to recruit our clandestine services to assess threats early. Doing so in Wuhan would have helped us get an important head start. Getting ready for the next crisis may sound esoteric, especially since we're still trying to claw our way out of this one. But it may not be a viral pandemic that's generations away -- it may be a tsunami, antibiotic-resistant bacteria, a mass shooting, or biological warfare. The next crisis could be right around the corner.

In fact, for those wanting to harm masses of people, the pandemic introduced a new weapon. Gottlieb sternly concludes that we must treat labs as sources of biologic weapons and that this activity should be monitored around the world, just as nuclear weapons are monitored globally.

Throughout the pandemic, Gottlieb spoke with the front-line physicians, researchers, and top decision-makers at the highest levels in government. He became a leading voice of reason as the American people tried to make sense of COVID-19, and policymakers and business leaders struggled to protect the public. Every clinician can learn a thing or two from reading his new book and paying attention to his detailed guidance on what needs to change. Now is the time to redesign our healthcare agencies, not in the future when the urgency is forgotten.

There are many books on COVID-19, and there will be more to come. I believe Uncontrolled Spread will emerge as the best of them. It comes from a unique and impeccably qualified vantage point. Gottlieb's comprehensive analysis and take-home messages offer hope and direction that we can only hope our decisionmakers will heed.

Marty Makary, MD, MPH, is editor-in-chief of MedPage Today, a professor at the Johns Hopkins University School of Medicine, and author of The Price We Pay: What Broke American Healthcare -- And How to Fix It.

https://www.medpagetoday.com/opinion/marty-makary/94619

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