[timr]

> This one scared me since it was a large, relatively unbiased sample, with before-and-after imaging. It also showed brain damage even in mild cases of COVID19 in >10% of cases.

It shows no such thing. It's an analysis of MRIs where the authors infer loss of gray matter in specific regions of the brain. This is in no way "brain damage", and representing it this way is leaping to wild conclusions.

Lest you not believe me, here is a randomized controlled trial, showing that "excessive online video gaming" reduces orbitofrontal gray matter:

https://pubmed.ncbi.nlm.nih.gov/29057579/

(...so your Mom was right: gaming is turning your brain to mush!)

Here is a review that shows that similar losses in gray matter are associated with anxiety and sleep loss (two problems that I'm sure didn't affect anyone in 2020):

https://pubmed.ncbi.nlm.nih.gov/29244642/

Similarly: "Profound and reproducible patterns of reduced regional gray matter characterize major depressive disorder"

https://pubmed.ncbi.nlm.nih.gov/31341158/

Just for fun: here's a paper that shows that "tooth loss was a causal factor for volume reduction in brain areas related to memory, learning and cognition"

https://pubmed.ncbi.nlm.nih.gov/29475808/

(bonus points: can you spot the missing correlate?)

The fact is, you can find research literature associating "loss of gray matter" with pretty much anything. And if a reliable trend does exist across this literature, it seems to be that gray matter changes are often seen in...wait for it: depressed people and the aged.

But I'm sure that Covid has done nothing to depress people or affect the aged, so we can probably safely ignore that little detail.

[gibba999]

I think a lot of this comes down to replication, effect size, and sample size.

Yes, there are studies which show virtually everything, but in this case, we have:

- >10% of mild cases reporting long COVID brain fog (without MRIs)

- Visible correlations on MRIs with large n (cited study)

- Lots of small-scale studies / looking at specific cases

- Some understanding of a relevant mechanism-of-action (see: olfactory loss)

Together, that's about as strong evidence as you'd expect after 15 months. We have effect, we have correlation, we have case studies, and we understand why it's plausible.

The big question is whether it strikes vaccinated mild / asymptomatic cases. We don't know. There are a lot of cases like this.

[timr]

> >10% of mild cases reporting long COVID brain fog (without MRIs)

"Brain fog" is not a diagnosis. It has no definition. It has no test. Literally anyone could say they have it, and not be wrong.

It also overlaps substantially with "fatigue"...which we all know comes along with a lot of other common issues. Such as depression.

> Visible correlations on MRIs with large n (cited study)

The size of n doesn't matter if the thing you're reporting is not a meaningful metric. Here, we have a paper that has gone on a fishing expedition for a quasi-subjective metric with unknown levels of noise, which is widely "shown" to be associated with many common and uncommon issues across the research literature.

This is a low-quality data set. But yes, it is a larger low-quality data set.

> Lots of small-scale studies / looking at specific cases

Collections of anecdotes are not data.

> Some understanding of a relevant mechanism-of-action (see: olfactory loss)

...for a single symptom (loss of smell). But no, we don't know why that happens, and to the extent we do, the current best hypothesis has nothing to do with neurons, but rather, the scaffolding around those neurons.

> Together, that's about as strong evidence as you'd expect after 15 months.

Nonsense. We've been debating this "long covid" for more than a year now. There are apparently many sufferers. We could have easily conducted randomized, longitudinal, controlled trials. We have not.

The total evidence for "long covid" continues to be anecdotes and self-reported "symptoms", of indeterminate duration, amongst populations that are mostly self-selected for having "long covid". I believe that we'll eventually find out that some of these things are real, but right now, this is just hysteria.

[gibba999]

My hypothesis is that COVID leads to a Gaussian distribution in reduction in general neurological function, and that we will see a bell curve distribution reduction in e.g. general IQ.

Can you please propose a "randomized, longitudinal, controlled trials" one might conduct to figure that out?

Preferably, one which would pass an IRB review. We can't randomly infect 10,000 ethnic minorities with COVID19 anymore, which I think what you're suggesting. The Tuskegee Syphilis Study and the Nuremberg Trials took care of that for us.

Short of something like that, we work from mixed methods evidence.

As a footnote, a year isn't a long time in the world of research. That's sometimes quite literally how long it takes from when you apply for a grant to when funding lands in your account. And you're asking about a phenomenon which often occurs months later.

[timr]

> Can you please propose a "randomized, longitudinal, controlled trials" one might conduct to figure that out?

This is not a herculean problem. It's essentially the definition of any halfway decent medical study:

* pick a set of measurable endpoints from the pantheon of "long covid" symptoms that are likely to be real. Objectively measurable endpoints should be mixed in with subjective ones (e.g. "fatigue", "loss of smell", "reduced lung capacity", "heart inflammation").

* pre-register these endpoints, so that you can't go back on a fishing expedition later, when your first choices don't pan out.

* pick a set of participants at random (balancing for demographics of interest: age, co-morbidities, weight, gender, etc.)

* measure those endpoints at the start of the study so that you have a pre-trial baseline.

* follow those people over time for the endpoints of interest.

* some percentage will get infected with SARS-CoV2. verify this via testing.

* at the end of the study, compare the group that caught SARS-CoV2 with the ones who did not along the endpoints of interest. compare both groups with their own pre-trial baselines.

This is not the ONLY way of doing such a study, but it would be vastly better than any data currently reported. The biggest challenge is that it has to be done before the pandemic passes, and the number of cases drops too low to get a significant result in a reasonable period of time. The window on this is rapidly closing.

> As a footnote, a year isn't a long time in the world of research. That's sometimes quite literally how long it takes from when you apply for a grant to when funding lands in your account. And you're asking about a phenomenon which often occurs months later.

There have been multiple RCTs conducted during the pandemic, despite the bureaucratic inertia of the academy, and "long covid" is one of the biggest remaining controversies. There's no universe in which you couldn't get funding and approval for such a study in short order.

[gibba999]

>> Can you please propose a "randomized, longitudinal, controlled trials" one might conduct to figure that out?

> This is not a herculean problem. It's essentially the definition of any halfway decent medical study:

You're running in circles. That's not a randomized control trial. You'll get biases since the set of people infected with COVID19 isn't random.

This is not much better than existing studies. They're not preregistered, but that's the only upside of your methodology.

> There have been multiple RCTs conducted during the pandemic, despite the bureaucratic inertia of the academy, and "long covid" is one of the biggest remaining controversies. There's no universe in which you couldn't get funding and approval for such a study in short order.

IRBs are set up to prevent subject harm. An RCT, in this case, would involve randomly infecting people with COVID19 to eliminate the bias above. That will never fly.

[ianlevesque]

Denial is quite a river these days. Where else are you going to get a brain imaging study with before and after data on thousands of people? If that's not persuasive and concerning to you I don't think anything will be.

[native_samples]

Why should a "study" in the abstract automatically be persuasive and concerning? Scientists get paid to publish studies, so the literature is full of nonsensical studies that show correlations between anything and everything. User timr just explained to you why this specific study cannot be used to conclude anything, but you're saying he's the one in denial?

[gibba999]

A study in isolation should not be persuasive. There's a pipeline from idea to hypothesis the theory to fact, which includes many studies with many methodologies.

On the other hand, a handful of studies, one correlational with large n, a few causal, a good theoretical basis, etc. do move us up that pipeline quite a bit.

Mild and asymptomatic cases of COVID19 due seem to cause brain damage leading to brain fog.

- Reports of brain fog in isolation? Psychosomatic.

- Correlational studies? Correlation is not causation.

- Case studies? Anecdotal.

- Extrapolation from olfactory symptoms? Theoretical.

And so on.

Put together, though, it's a pretty strong case. It's not airtight, but it's well into the well-supported theory range.

[timr]

> brain damage leading to brain fog.

Define "brain fog". Tell me what the diagnostic criteria are, and how one might make an objective measurement of its presence and magnitude.

Bonus question: tell me how your stated criteria differs from the pre-established diagnostic criteria for depression.

One can survey a random sample of the population, ask them if they have ever "felt the presence of God", and find a strong signal confirming this. It does not make God a diagnostic factor in a medical study.

[cloverich]

> tell me how your stated criteria differs from the pre-established diagnostic criteria for depression.

If the person lacks dysphoria or anhedonia, would that satisfy the question? I understand your angle (I think), but for comparison, the last time I had a serious flu I found that even after I felt better, it was extremely difficult to focus at work. For about 3 days, gradually improving each. I suspect that is what people refer to as "brain fog", and I could distinguish it from depression by (among other things) a lack of dysphoria / anhedonia (and generally speaking, other depression signs).

I remember in medical school that when we were interviewing patients receiving chemo they would have us do a neuro exam, and very distinctly remember when one guy got angry at me when he couldn't answer some of my questions. He didn't seem to have depression and nobody told me I was doing it wrong when I said he had "chemo brain". So its certainly a real thing in the general sense, and can certainly be caused by a variety of medical conditions.

I guess a more constructive question would be -- assuming a long term cognitive impact, what (practical) research should these researchers be doing instead? Or what if when they asked about brain fog they _also_ asked about depressive symptoms?

[timr]

> If the person lacks dysphoria or anhedonia, would that satisfy the question?

No. That is certainly more specific than ~all of what you hear in the media surrounding "brain fog", but you can't define something by what it isn't.

Example: I have the wiggles. I'm not itchy though, and my muscles don't hurt.

OK, great. What are the wiggles?

> the last time I had a serious flu I found that even after I felt better, it was extremely difficult to focus at work. For about 3 days, gradually improving each. I suspect that is what people refer to as "brain fog"

Could be! The problem is, until there's a definition (and ideally some kind of objective measure), all of these self-reports are blind people describing different parts of an elephant.

> I guess a more constructive question would be -- assuming a long term cognitive impact, what (practical) research should these researchers be doing instead? Or what if when they asked about brain fog they _also_ asked about depressive symptoms?

We could start by simply using established terminology and testing. What percentage of patients reporting "brain fog" show up as depressed using a standard screen?

It's literally the easiest thing in the world to do...why isn't it done?

[timr]

> Where else are you going to get a brain imaging study with before and after data on thousands of people?

Why does the size of the study matter so much if the endpoint of the study is absurd, the gathering process was a fishing expedition, and the whole thing is subject to confirmation bias?

Even if you believe that these researchers are finding real signals in these MRI scans (which I don't automatically grant; even they admit that some of the "pathologies" they've identified aren't significant, and they didn't pre-declare the endpoints anyway, so you can't rely on conventional statistical significance thresholds), the fact that they know the outcome for each subject hopelessly poisons the data.

> Denial is quite a river these days.

People have a habit of inventing fictions they believe wholeheartedly in order to ignore a truth they cannot accept.

[elcomet]

> bonus points: can you spot the missing correlate?)

Concussions ?

[marton78]

Poverty, drug use, poor life choices.

[timr]

I was thinking of all of the lifestyle factors that might make one susceptible to tooth loss for >10 years prior to the study (this was a selection criteria for the participants): lack of education, nutrition, medical care, etc. The paper never controls for why these people lost their teeth.

(To be fair to the researchers of this paper, they do discuss some of this, but they focus on a causal relationship between tooth loss and the other factors. They never really consider that the relationship between these factors and tooth loss could be reversed.)