Kamala Harris has a complicated record, but her zeal to support abortion and attack its opponents has been consistent
Reports of coronavirus victims often include pictures of intensive care units filled with intubated patients—that is, patients with breathing tubes connected to ventilators. Long used to help patients who are under anesthesia or whose breathing has failed, ventilators mechanically push air into the lungs under pressure. Like any powerful tool, they should be used wisely—and reports are starting to suggest that, in the context of the coronavirus pandemic, wise use of ventilators may mean less use of them.
COVID-19 often causes a specific type of pneumonia, leading to dramatic respiratory distress and very low oxygen “saturation.” Oxygen saturation refers to the percentage of hemoglobin (the molecule in blood cells responsible for carrying oxygen) that’s actually carrying oxygen. To measure saturation, doctors often use a “pulse oximeter” that shines light through a finger. Oxygenated blood absorbs light at one frequency and deoxygenated blood at another, and with a little automated math, the system gives an oxygen reading. A healthy percentage is in the high 90s, and more typical pneumonias don’t usually cause a dramatic “desaturation” until the patient is gravely ill.
But COVID-19 is different. Patients with COVID-19 pneumonia often enter the hospital with oxygen numbers far lower than the point at which doctors would normally rush to intubate.
Originally, doctors did indeed rush to intubate such COVID-19 patients. But two things happened: First, patients on mechanical ventilation often fared poorly. Doctors initially ascribed this to the disease’s progression—after all, they were intubating these patients precisely because they were so sick. Yet patients treated without mechanical ventilation often did better than expected clinically, despite their bad numbers on the monitor. (Exactly why patients with COVID-19 are often able to tolerate such low oxygen levels is an interesting question, but one without a satisfactory answer yet.)
In his influential work The ICU Book, intensive care physician Paul Marino argues doctors should use oxygen, ventilators, and sedation thoughtfully, seeking not to “treat the monitor” (that is, to make the best possible numbers our goal) but to provide patients with just enough support to heal. Marino suggests that even if a doctor avoids causing direct, obvious harm through ham-handed use of these tools, their effect can still be counterproductive. The goal, then, should be to conserve their use.
A treatment protocol released by Eastern Virginia Medical School (EVMS) in Norfolk, Va., follows this conservation approach for COVID-19 patients, recommending doctors avoid intubations whenever possible. Under the protocol, the first step for treating COVID-19 patients remains oxygen via nasal cannula—the ubiquitous “prongs” that longtime smokers attach to their portable oxygen concentrators. But when patients need something more, doctors are now trying high-flow oxygen via nasal cannula—and are accepting oxygen saturations in the low 80s, an idea that would have before been unthinkable. Only when this fails does EVMS suggest mechanical ventilation, and even then the goal is to use the lowest possible pressures. (As a disclaimer, the school notes “there is no known therapeutic intervention that has unequivocally been proven to improve the outcome of COVID-19.”)
I’ve heard this approach described as a way to conserve ventilators. It could have that effect, but that’s not the main idea behind it: Even where ventilators are widely available, EVMS—and Dr. Marino’s book—argue the best treatment is as gentle as possible.
As we cautiously emerge during this eye-of-the-storm phase of the pandemic, I’ll look forward to reading more of what we’ve learned from the first wave of cases.
—This story has been updated to correct the name of the Eastern Virginia Medical School.
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Several readers have wondered about proposed treatments for the coronavirus. One asked this question: How did the experimental drug remdesivir suddenly supplant hydroxychloroquine as the most likely candidate to help COVID-19 patients? If remdesivir helps and hydroxychloroquine doesn’t, why haven’t all the studies shown that?
The short answer first: We’re dealing with preliminary studies, each with shortcomings. All studies have a hypothesis (an idea to test). Good medical studies generally have a control group (a group of participants who don’t get the proposed treatment), assign patients randomly to a treatment or placebo, and analyze all the relevant data the experiment produces. (Good studies share several other characteristics, too.)
With those qualities in mind, let’s look at the relevant studies examining whether hydroxychloroquine and remdesivir are beneficial for people suffering from COVID-19.
One small French study appeared to support the use of hydroxychloroquine for COVID-19, but the study had no control group. Worse, the authors excluded patients who worsened while on the drug. That wasn’t good research technique: If we want to know whether a drug helps people recover, drug recipients who instead get sicker are actually a valuable clue.
A larger U.S. study of Veterans Health Administration patients who had the coronavirus appeared to show that hydroxychloroquine didn’t help and might even cause harm. But the VA was only giving hydroxychloroquine to the sickest patients: As with any disease, sicker patients don’t do as well on average. The patients also received an “antiviral” dose of the drug, a much higher dose than patients with other conditions would get. That can lead to problems—especially in older, less healthy patients like those in the VA study. The VA study referenced Brazilian research that found the closely related drug chloroquine increased the likelihood of death when given in high doses, most likely due to effects on the heart. (Kudos to the researchers for exploring what their data might signify, even if it wasn’t what they’d hoped for.)
The research team in France responded with a larger retrospective study, but it has two major flaws. The first flaw is recruiting young, otherwise healthy patients: The COVID-19 coronavirus prefers to attack the elderly, so good outcomes in patients averaging 43 years of age may not be noteworthy. (By comparison, the VA study’s average age was 69—and its patients were in poorer overall health to begin with.) The second flaw prevents us from knowing whether those young patients treated with hydroxychloroquine would have recovered anyway: There’s still no control group! Without a control group, we have no way of knowing whether the treatment helped, harmed, or didn’t do anything at all.
How about remdesivir, then? A well-designed study in China planned to compare the drug with a placebo, but researchers suspended it after failing to enroll as many patients as they’d intended. Preliminary data posted to the World Health Organization’s website, then later deleted, did not appear to show a benefit to patients, dampening enthusiasm. Drugmaker Gilead has its own large study, but it lacks a control group.
More recently, the Adaptive COVID-19 Treatment Trial, sponsored by the National Institutes of Health (NIH), released preliminary results appearing to support the use of remdesivir, but with a catch. The study’s original goal was to demonstrate reduced mortality: The drug appeared to do so, but never “reached statistical significance.” In other words, the study’s outcomes could have been due simply to chance. The study’s new goal assessed the length of patient hospitalization, and remdesivir appeared to shorten that—but moving the goalposts midgame suggests researchers may have been unimpressed with their early results.
Ending with a plea for more research is a common trope in writing about research, but it’s more relevant now than ever. The currently published research is the preliminary work that happens while we’re racing to determine what’s worth further study. Based on what I’ve seen, I’d focus on the VA study for hydroxychloroquine and the NIH study for remdesivir—their control groups make them more reliable. My conclusion: Remdesivir appears to have a modest, if somewhat weak, benefit for COVID-19 patients. Also, high-dose hydroxychloroquine appears to carry more health risks than the low-dose version given to lupus patients.
In the meantime, wear your mask and wash your hands. An ounce of coronavirus prevention may still be worth a pound of cure.
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Early tests to detect the coronavirus were designed literally to do that: They detect the virus itself, identifying patients who harbor it. Those tests help with decisions about quarantines and treatment, but they have a key weakness. They don’t reveal whether a patient has already encountered the virus and then successfully recovered.
But new antibody tests (or “serological tests”), capable of recognizing a successful immune response to the coronavirus, are now entering the market. Not only can they identify people whose blood plasma might help the sickest patients recover, but antibody tests make possible new studies measuring how many people in a given region have already beaten SARS-CoV-2. What can they tell us about the virus’s death rate?
In early April, a team at Stanford University tested over 3,000 Californians, concluding between 2.5 percent and 4.3 percent of residents in Santa Clara County already had immunity to the coronavirus. The study fueled a debate among statisticians: Were the tests reliable, and were the 1.5 percent of tests that came back positive truly evidence that 2.5 percent to 4.3 percent of Santa Clara residents were immune? And were the study participants a representative sample of their community? The study had recruited volunteers by posting a Facebook ad for free coronavirus tests, raising concerns that people with recent symptoms were more likely to sign up in order to learn whether they’d had the virus.
Andrew Gelman, a professor of statistics at Columbia University, analyzed the study in a detailed (and profanity-sprinkled) blog post. He criticized the study from several angles, but also noted that a 3 percent immunity rate doesn’t sound implausible, and would imply a relatively low death rate of 0.16 percent, or 1 in 600 people exposed to the virus: “That’s good news, relatively speaking: we’d still like to avoid 300 million Americans getting the virus and 500,000 dying, but that’s still better than the doomsday scenario.”
Assuming the Stanford study is accurate, 96 percent of people in Santa Clara County have yet to encounter the virus. Studies in regions with larger outbreaks have found higher immunity rates. One gave a preliminary look at 500 people in the German town of Gangelt, finding current coronavirus infections in 2 percent of study participants and evidence of immunity in 14 percent—for a case fatality rate of about 0.37 percent. A study of New York residents tested 3,000 people, finding 14.9 percent with evidence of immunity. In New York City, the immunity rate was about 21 percent.
So is this virus just like the flu, as some argue? It feels reassuring to say the case fatality rate is “only” 0.37 percent in the German study, and I’d certainly take that over the 3 percent to 5 percent initially reported in places like Wuhan. It’s less reassuring to look at New York City’s 18,000 deaths (as of May 4), divide them by 21 percent of NYC’s 8.3 million people, and come up with a case fatality rate of about 1 percent.
I rejoice with those who celebrate that the coronavirus does not normally claim the lives of 3 percent to 5 percent of those it infects, as initially feared, and I share the hope of those who eagerly read new reports of promising treatments. But a case fatality rate of 0.37 percent to 1 percent would still be far higher than flu: As America moves cautiously toward reopening, let’s remember the reason it closed.