Tag Archives: Andrew Bostom

COVID Testing: Cycle Thresholds and Coffee Grounds

19 Saturday Dec 2020

Posted by in Coronavirus, Public Health, Uncategorized

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Here’s some incredible data on PCR tests demonstrating a radically excessive lab practice that generates false positives. I’m almost tempted to say we’d do just as well using a thermometer and the coffee ground test. Open a coffee tin and take a sniff. Can you smell the distinct aroma of the grounds? If not, and if you have other common symptoms, there’s a decent chance you have an active COVID infection. That test is actually in use in some parts of the globe!

The data shown below on PCR tests are from the Rhode Island Department of a Health and the Rhode Island State Health Lab. They summarize over 5,000 positive COVID PCR tests (collected via deep nasal swabs) taken from late March through early July. The vertical axis in the chart measures the cycle threshold (Ct) value of each positive test. Ct is the number of times the RNA in a sample must be replicated before any COVID-19 (or COVID-like) RNA is detected. It might be from a live virus or perhaps a fragment of a dead virus. A positive test with a low Ct value indicates that the subject is likely infected with billions of live COVID-19 viruses, while a high Ct value indicates perhaps a handful or no live virus at all.

The range of red dots in the chart (< 28 Ct) indicates relatively low Ct values and active infections. The yellow range of dots, for which 28 < Ct <= 32, indicates possible infections, and the upper range of green dots, where Ct > 32, indicates that active infections were highly unlikely. It’s important to note that all of these tests were recorded as new COVID cases, so the range of Ct values suggest that testing in Rhode Island was unreasonably sensitive. That’s broadly true across the U.S. as well, which means that COVID cases are over-counted by perhaps 30% or more. And yet it is extremely difficult for subjects testing positive to learn their Ct values. You can ask, but you probably won’t get an answer, which is absurd and counterproductive.

Notice that the concentration of red dots diminished over time, and we know that the spring wave of the virus in the Northeast was waning as the summer approached. The share of positives tests with high Ct values increased over that time frame, however. This is borne out by the next chart, which shows the daily mean Ct of these positive tests. The chart shows that active infections became increasingly rare over that time frame both because positive tests decreased and the average Ct value rose. What we don’t know is whether labs bumped up the number of cycles or replications to which samples were subjected. Still, the trend is rather disturbing because most of the positive cases in May and the first half of June were more likely to be virus remnants than live viruses.

It’s also worth noting that COVID deaths declined in concert with the upward trend in Ct values. This is shown in the chart below (where the Ct scale is inverted). This demonstrates the truly benign nature of positive tests having high Ct values.

This is also demonstrated by the following data from a New York City academic hospital, which was posted by Andrew Bostom. It shows that a more favorable “clinical status” of COVID patients is associated with higher Ct values.

It’s astounding that the U.S. has relied so heavily on a diagnostic tool that gets so many subjects wrong. And it’s nearly impossible for subjects testing positive to obtain their Ct values. Instead, they are subject to self-quarantine for up to two weeks. Even worse, until recently there were delays in reporting the results of these tests of up to a week or more. That made them extremely unhelpful. On the other hand, the coffee ground test is fast and cheap, and it might enhance the credibility of a subsequent positive PCR test, if one is necessary … and especially if the lab won’t report the Ct value.

The PCR test has identified far too many false infections, but it wouldn’t have been quite so damaging if 1) a reasonably low maximum cycle threshold had been established; 2) test results had not been subject to such long delays; and 3) rapid retests had been available for confirmation. The cycle threshold issue is starting to receive more attention, quite belatedly, and more rapid tests have become available. As I’ve emphasized in the past, cheap, rapid tests exist. But having dithered in February and March in approving even the PCR test, the FDA has remained extremely grudging in approving newer tests, and it persists in creating obstacles to their use. The FDA needs to wake up and smell the coffee!

The Pernicious COVID PCR Test: Ditch It or Fix It

02 Wednesday Dec 2020

Posted by in Coronavirus, Public Health

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We have a false-positive problem and even the New York Times noticed! The number of active COVID cases has been vastly exaggerated and still is, but there is more than one fix.

COVID PCR tests, which are designed to detect coronavirus RNA from a nasal swab, have a “specificity” of about 97%, and perhaps much less in the field. That means at least 3% of tests on uninfected subjects are falsely positive. But the total number of false positive tests can be as large or larger than the total number of true positives identified. Let’s say 3% of the tested population is truly infected. Then out of every 100 individuals tested, three individuals are actively infected and 97 are not. Yet about 3 of those 97 will test positive anyway! So in this example, for every true infection identified, the test also falsely flags an uninfected individual. The number of active infections is exaggerated by 100%.

But again, it’s suspected to be much worse than that. The specificity of PCR tests depends on the number of DNA replications, or amplification cycles, to which a test sample is subjected. That process is illustrated through three cycles in the graphic above. It’s generally thought that 20 – 30 cycles is sufficient to pick-up DNA from a live virus infection. If a sample is subjected to more than 30 cycles, the likelihood that the test will detect insignificant dead fragments of the virus is increased. More than 35 cycles prompts real concern about the test’s reliability. But in the U.S., PCR tests are regularly subjected to upwards of 35 and even 40-plus cycles of amplification. This means the number of active cases is exaggerated, perhaps by several times. If you don’t believe me, just ask the great Dr. Anthony Fauci:

“It’s very frustrating for the patients as well as for the physicians … somebody comes in, and they repeat their PCR, and it’s like [a] 37 cycle threshold, but you almost never can culture virus from a 37 threshold cycle. So, I think if somebody does come in with 37, 38, even 36, you got to say, you know, it’s just dead nucleotides, period.“

Remember, the purpose of the test is to find active infections, but the window during which most COVID infections are active is fairly narrow, only for 10 – 15 days after the onset of symptoms, and often less; those individuals are infectious to others only up to about 10 days, and most tests lag behind the onset of symptoms. In fact, infected but asymptomatic individuals — a third or more of all those truly infected at any given time — are minimally infectious, if at all. So the window over which the test should be sensitive is fairly narrow, and many active infections are not infectious at all.

PCR tests are subject to a variety of other criticisms. Many of those are discussed in this external peer-review report on an early 2020 publication favorable to the tests. In addition to the many practical shortfalls of the test, the authors of the original paper are cited for conflicts of interest. And the original paper was accepted within 24 hours of submission to the journal Eurosurveillance (what a name!), which should raise eyebrows to anyone familiar with a typical journal review process.

The most obvious implication of all the false positives is that the COVID case numbers are exaggerated. The media and even public health officials have been very slow to catch onto this fact. As a result, their reaction has sown a panic among the public that active case numbers are spiraling out of control. In addition, false positives lead directly to mis-attribution of death: the CDC changed it’s guidelines in early April for attributing death to COVID (and only for COVID, not other causes of death). This, along with the vast increase in testing, means that false positives have led to an exaggeration of COVID as a cause of death. Even worse, false positives absorb scarce medical resources, as patients diagnosed with COVID require a high level of staffing and precaution, and the staff often requires isolation themselves.

Many have heard that Elon Musk tested positive twice in one day, and tested negative twice in the same day! The uncomfortable reality of a faulty test was recently recognized by an Appeals Court in Portugal, and we may see more litigation of this kind. The Court ruled in favor of four German tourists who were quarantined all summer after one of them tested positive. The Court said:

“In view of current scientific evidence, this test shows itself to be unable to determine beyond reasonable doubt that such positivity corresponds, in fact, to the infection of a person by the SARS-CoV-2 virus.” 

I don’t believe testing is a bad thing. The existence of diagnostic tests cannot be a bad thing. In fact, I have advocated for fast, cheap tests, even at the sacrifice of accuracy, so that individuals can test themselves at home repeatedly, if necessary. And fast, cheap tests exist, if only they would be approved by the FDA. Positive tests should always be followed-up immediately by additional testing, whether those are additional PCR tests, other molecular tests, or antigen tests. And as Brown University epidemiologist Andrew Bostom says, you should always ask for the cycle threshold used when you receive a positive result on a PCR test. If it’s above 30 and you feel okay, the test is probably not meaningful.

PCR tests are not ideal because repeat testing is time consuming and expensive, but PCR tests could be much better if the number of replication cycles was reduced to somewhere between 20 and 30. Like most flu and SARS viruses, COVID-19 is very dangerous to the aged and sick, so our resources should be focused on their safety. However, exaggerated case counts are a cause of unnecessary hysteria and cost, especially for a virus that is rather benign to most people.

The Favored Cause of Death

19 Monday Oct 2020

Posted by in Coronavirus, Public Health

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The CDC changed its guidelines on completion of death certificates on April 5th of this year, and only for COVID-19 (C19), just as infections and presumed C19 deaths were ramping up. The substance of the change was to broaden the definition under which death should be attributed to C19. This ran counter to CDC guidelines followed over the previous 17 years, and the change not only makes the C19 death counts suspect: it also makes comparisons of C19 deaths to other causes of death unreliable, since only C19 is subject to the new CDC guidance. That’s true for concurrent and historical comparisons. The distortions are especially bad relative to other respiratory diseases, but also relative to other conditions that are common in mortality data.

The change in the CDC guidelines was noted in a recent report prepared for the Florida House of Representatives. It was brought to my attention by a retweet by Justin Hart linked to this piece on Andrew Bostom’s site. Death certificates are divided into two parts: Part 1 provides four lines in which causes of death are listed in reverse clinical order of events leading to death. Thus, the first line is the final clinical condition precipitating death. Prior clinical events are to be listed below that. The example shown above indicates that an auto accident, listed on the fourth line, initiated the sequence of events. Part 2 of the certificate is available for physicians or examiners to list contributing factors that might have played a role in the death that were not part of the sequence of clinical events leading to death.

The CDC’s change in guidelines for C19, and C19 only, made the criteria for inclusion in Part 1 less specific, and it essentially eliminated the distinction between Parts 1 and 2. The following appears under “Vital Records Criteria”:

“A death certificate that lists COVID-19 disease or SARS-CoV-2 as a cause of death or a significant condition contributing to death.”

How much difference does this make? For one thing, it opens the door to C19-attributed deaths in cases of false-positive PCR tests. When large cohorts are subject to testing — for example, all patients admitted to hospitals — there will always be a significant number of false positives even when test specificity is as high as 98 – 99%.

The elimination of any distinction between Parts 1 and 2 causes other distortions. A review of the Florida report is illustrative. The House staff reviewed almost 14,000 certificates for C19-19 attributed deaths. Over 9% of those did not list C19 among the clinical conditions leading to death. Instead, in those cases, C19 was listed as a contributing factor. Under the CDC’s previous guidelines, those would not have been counted as C19 deaths. The Florida House report is conservative in concluding that the new CDC guidelines inflated C19 deaths by only those 9% of the records examined.

There are reasons to think that the exaggeration was much greater, however. First, the Florida House report noted that nearly 60% of the certificates contained information “recorded in a manner inconsistent with state and national guidance”. In addition, almost another 10% of the fatalities were among patients already in hospice! Do we really believe the deaths of all those patients whose diseases had reached such an advanced stage should be classified as C19 fatalities? And another 1-2% listed non-C19 conditions as the immediate and underlying causes.

Finally, more than 20% of the certificates listed C19 alone as a cause of death despite a range of other contributing conditions or co-morbidities. This in itself may have been prompted by the change in the CDC’s guidelines, as the normal standards often involve a “comorbidity” as the initial reason for hospitalization — in that case a clinical event ordinarily listed in Part 1. The high rate of errors and the fact that roughly two-thirds of the deaths reviewed occurred in the hospital, where patients are all tested and often multiple times, raises the specter that up to 20% more of the C19 deaths were either erroneous and/or misclassified due to false positives.

(An exception may have occurred in New York, where an order issued in March by Governor Andrew Cuomo to return C19-positive residents of nursing homes (including suspected C19 cases) back to those homes, The order was made before the change in CDC guidelines and wasn’t rescinded until later in April. There is reason to believe that some of the C19 deaths among nursing home residents in New York were undercounted.)

All told, in the Florida data we have potential misclassification of deaths of 9% + 9% + 2% + 20% = 40%, or inflation relative to actual C19 deaths of up to 40%/60% = 67%! I strongly doubt it’s that high, but I would not consider a range of 25% – 50% exaggeration to be unreasonable.

We know that reports of C19 deaths lag actual dates of death by anywhere from 1 to 8 weeks, sometimes even more. This is misleading when no effort is made to explain that difference, which I’ve never heard out of a single journalist. We also know that false positive tests inflate C19 deaths. The Florida report gives us a sense of how large that exaggeration might be. In addition, the Florida data show that the CDC guidelines inflate C19 deaths in other ways: as a mere contributing factor, it can now be listed as the cause of death, unlike the treatment of pneumonia as a contributing factor, for instance. The same kind of distortion occurs when patients contract C19 (or have a false positive test) while in hospice.

There is no doubt that C19 led to “excess deaths” relative to all-cause mortality. However, many of these fatalities are misclassified, and it’s likely that a large share were and are lockdown deaths as opposed to C19 deaths. That’s tragic. The CDC has done the country a massive disservice by creating “special rules” for attributing cause-of-death to C19. If reported C19 fatality rates reflected the same rules applied to other conditions, our approach to managing the pandemic surely would have inflicted far less damage to health and economic well being.