Monday, April 26, 2021

A Good Piece on "Long Covid"

Here is an excellent piece on "long covid" by Adam Gaffney, who describes himself as a pulmonary and critical care physician. He is remarking on the phenomenon of long-haul outcomes of a prior covid infection. The whole thing is worth reading. 

I've put down my thoughts on "long covid" repeatedly on this blog. I've said that this seems like the phenomenon often seen in policy advocacy. There is a technique for inflating the importance of a problem. It goes something like this. An advocate broadly defines the problem to include even minor instances of it, such that one gets the largest, scariest possible total. Then s/he offers the most extreme cases as examples of the problem being quantified (rather than offering, say, a typical example, or a random, representative sampling). I think that's what's going on with claims that long covid is a big deal. Yes, there are individuals with tragic long-haul symptoms. Scarring of the lungs, damage to the heart, and so on. We should supplement data on "death counts" with this information and provide useful context about how well survivors fare. But these severe outcomes just aren't typical. Read the piece. "Long haul" could simply mean someone is feeling "brain fog" for weeks or months after a covid infection. (As far as I know, I haven't had covid. But I've certainly felt "brain fog" in the past 13 months. Could this have anything to do with my regular working life being rearranged?)

Another point of caution is that some of these "long haul" health outcomes might have nothing to do with the prior covid infection. It's really difficult to assign a cause to something, whether it's a society-wide problem like rising crime rates or a personal one like chronic health issues. I've made the analogy before to doing an MRI for back pain. Often the doctor will look at such an image and find some insult, like a bulging disk, and use that to "explain" why the pain is occurring. But doctors find a comparable number of such insults on scans of completely normal people. It's weird to pick out some detail that's in the background of everyone's life and say, "This is the cause of your problem," given that the same condition fails to cause a problem for most individuals. Presumably some of these problems have something to do with people's lives being upended, their careers and futures wracked with uncertainty. It's going to be difficult to tease out whether long-term health outcomes that are caused by covid itself or the intense social isolation and traumatic shift in people's daily routines. (Anecdotally, I've been hearing about people taking up bad habits this past year. "The covid-15" anyone? I suspect we'll see some of this show up in official statistics.)

This seems really important:

First, a cause-and-effect relationship is typically unestablished in these articles.  The Times article contending that mild and resolved COVID-19 infections can lead to extreme psychosis months later left out some important context.  According to one international study, the incidence of psychotic disorders is around 27 per 100,000 persons per year, which would suggest that in the US, there are tens of thousands of new diagnoses of psychosis every year.  In 2020, a solid proportion of those new diagnoses will have occurred in individuals with a prior coronavirus infection.  Obviously, although the temporal link will no doubt feel powerfully suggestive to patients and their doctors, this does not establish causality.

Another reason to question the causal link between the virus and some “Long COVID” symptoms stems from the fact that some, and perhaps many labelled with long COVID appear to never have been infected with the SARS-CoV-2 virus.  For instance, in his August Atlantic article, Yong cites a survey of COVID “long-haulers” that found that some two-thirds of these individuals had negative coronavirus antibody tests, which are blood tests that reveal prior infection.  Meanwhile, the aforementioned study published on a pre-print server, organized by a group of Long COVID patients named Body Politic that recruited participants from online long COVID support groups, similarly found that some two-thirds of the long-hauler study participants who had undergone serological testing reported negative results.

[Read the piece. He goes on to acknowledge that serology can be negative for people who in fact were infected, but argues that it's implausible that all of these "long-haulers" who tested negative actually had covid.]

This issue is an epistemic nightmare for me. For all I know, the "long covid" alarmists are absolutely correct. But I can't trust anything they're saying. The public health establishment has not been an honest broker of useful information (and that observation predates 2020). It's been marshaling whatever arguments and "evidence" it can find in favor of extreme caution and official government lockdowns. Should I treat "long covid" as a serious concern? Or should I treat it like so many strands of half-cooked spaghetti that have been flung in my face over the past year? Is this narrative being picked up and repeated because of it's inherent plausibility? Or is there a media-government complex that creates a demand for this kind of terror-porn? As Bret Weinstein likes to say, our sense-making apparatus is broken. The tragedy is that we really do need useful and accurate information to navigate a public health emergency like the present one. 

1 comment:

  1. You should read the paper he referenced.

    "In this study, we analysed responses from 3,762 participants with confirmed (diagnostic/antibody positive; 1,020) or suspected (diagnostic/antibody negative or untested; 2,742) COVID-19, from 56 countries, with illness duration of at least 28 days."

    "The most frequent symptoms reported after month 6 were fatigue, post-exertional malaise, and cognitive dysfunction."

    "Except for loss of smell and taste, the prevalence and trajectory of all symptoms were similar between groups with confirmed and suspected COVID-19."

    You can't just had-wave that away as false negatives. Given the large sample size, there would be _some_ signal. And the fact that you _can_ detect a difference in the key differential symptom proves this.

    But, in a stunning tribute to social desirability bias, their Implications section says:

    "This research demonstrates how expansive and debilitating this prolonged illness can be, with profound impacts to people’s livelihoods and ability to care for themselves and their loved ones. This research demonstrates the importance of slowing the spread of COVID-19 through validated public health measures and vaccinations..."
    If you're a stats wonk, here are those paragraphs about the details of their analysis by test result:

    "Among respondents who received a diagnostic test (RT-PCR or antigen) for SARS-CoV-2 at any point during their illness, 1,730 tested negative and 600 tested positive. The primary difference between these two groups was the time elapsed between symptom onset and testing, with a median of 6 days for those who tested positive and 43 days for those who tested negative (p < 0.001, Mann-Whitney U test) (Supplemental Figure S6). Symptoms were remarkably similar between the two groups. We compared symptom prevalence among positively and negatively tested respondents, stratified by test time. Out of 205 symptoms, 203 showed no significant difference at the 5% level(Fisher test, Bonferroni corrected). The loss of smell and taste were the only exceptions (loss of smell: 22.2% (negative) vs 60.8% (positive), p < 0.0001; 21.5% loss of taste: 21.5% (negative) vs. 54.9% (positive), p < 0.0001; Fisher test, Bonferroni corrected). In addition, 683 participants tested positive for SARS-CoV-2 antibodies (either IgG, IgM, or both). Similarly, the loss of smell and taste were the only significantly different symptoms when comparing prevalence among respondents who tested negative (diagnostic and antibody, 21.6% loss of smell, 25.3% loss of taste) versus positive (diagnostic or antibody, 60.0% loss of smell, 52.5% loss of taste), stratified by test time (p < 0.0001, Fisher test, Bonferroni corrected).

    Furthermore, respondents experienced similar variation in symptoms over time, despite differences in testing status. For 65 out of 66 symptoms, time courses overlapped substantially between participants with confirmed COVID-19 (n=1,020, positive RT-PCR, antigen, or antibody test atany point) and participants with no positive test result (n=2,742, Figure 7). As above, change in smell/taste was the lone exception. Similar overlap was observed when separately comparing positively tested participants to negatively tested and untested participants (Supplemental Figures S7 and S8)."

    That is about as clear statistical evidence as you could hope for that you should be skeptical about causality. Except for loss of smell and taste.

    https://www.medrxiv.org/.../2020.12.24.20248802v3.full.pdf

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