Attributes and predictors of long Covid | Hacker News Reader

Attributes and predictors of long Covid

nature.com

81 pointsluu76 comments

A related article about the long-term effects of any viral infection, including COVID: [Long Covid isn’t as unique as we thought](https://www.vox.com/22298751/long-term-side-effects-covid-19...)

> Long COVID was characterized by symptoms of fatigue, headache, dyspnea and anosmia and was more likely with increasing age and body mass index and female sex. Experiencing more than five symptoms during the first week of illness was associated with long COVID.

A bit disappointing information. So, first week severity indicates risk for long covid? Or is it multiorgan involvement independent from severity?

It's surprising how long it takes to draw solid conclusions, considering the amount of "live" cases to draw from.

Why is that surprising? The whole descriptor 'long Covid' suggests that there is an element of time involved that is rather longer than the initial round of the disease itself.

Many diseases take years to run their course, I would expect the real damage toll from long Covid to not be visible for years to come rather than that we would somehow be able to predict the course of the disease before we have real world data showing what it can be like.

The number of cases has no effect on that at all.

I think they probably mean that, if there’s lots of cases, then there’s (in principle) lots of available information to study, regarding whatever mechanisms are behind the long covid effects we’ve seen so far.

Indeed, also taking into consideration that the pandemic is the most pressing issue in many countries. It can't be a budgetary issue. Could someone shed some light on why these questions are so hard?

Ironically, an excessively large amount of raw data can make study harder, at least at first, since it can be difficult to scientifically discern what is a real case of long covid and what is the result of other external factors.

Raw data abundance may seem like a good thing for study, but when people have time to build their own lore and superstitions, it can make scientific inquiry that much more difficult.

Many severe long covid cases are benign in the acute phase. Multiorgan involvement seems to me like it 1) doesn't occur in the first week 2) doesn't occur in benign cases.

Also, from the abstract: This model could be used to identify individuals at risk of long COVID for trials of prevention or treatment and to plan education and rehabilitation services. So this is not about "first week of illness indicates COVID severity" per se, this is about creating a prediction model to triage cases. It makes sense to focus on early symptoms for that.

You could get over the 5-symptom limit in this study just with knackered lungs.

If you do, you might have more pressing concerns that Long Covid if you are in the first week of an infection, and yet you might also be at higher risk for that as well.

It's amount of symptoms, not severity.

Looking at the symptoms of long covid, I wonder how much of it is depression vs covid?

One of the biggest risk factors for COVID and especially for poor outcomes is Vitamin D deficiency, but this study apparently didn't even check Vitamin D levels. That seems like a serious oversight.

My new PCP doctor threw shade on why I was taking 5000 IU of Vitamin D3 per day. I asked him why he wasn't considering Fauci and others take it for COVID outcome prophylaxis.

Note that very high levels of vitamin D supplements are possibly linked to reduction of volumetric bone density[0]. Low levels make sense given most people are more housebound during the pandemic.

[0] https://pubmed.ncbi.nlm.nih.gov/31454046/

"Conclusions and relevance: Among healthy adults, treatment with vitamin D for 3 years at a dose of 4000 IU per day or 10 000 IU per day, compared with 400 IU per day, resulted in statistically significant lower radial BMD; tibial BMD was significantly lower only with the 10 000 IU per day dose. There were no significant differences in bone strength at either the radius or tibia. These findings do not support a benefit of high-dose vitamin D supplementation for bone health; further research would be needed to determine whether it is harmful."

> One of the biggest risk factors for COVID and especially for poor outcomes is Vitamin D deficiency.

Is it? How exactly is vitamin D deficiency measured and diagnosed? How much variance / tolerance is there between people. Most importantly does COVID impact Vitamin D levels?

This may be a serious oversight. Or it may be that the Vitamin D thing is pseudoscience.

I recommend you read through all the studies indexed on this page and then get back to us.

https://vitamin-d-covid.shotwell.ca/

> Is it?

Yes

> How exactly is vitamin D deficiency measured and diagnosed?

Usually with a blood test. It's diagnosed because the blood test comes back out of range which is usually below 30 ng/ml for insufficiency, and below 20 for a deficiency.

> How much variance / tolerance is there between people?

The std. deviation is 16.6 ng/ml

> Most importantly does COVID impact Vitamin D levels?

I don't think we know, it's hard to track this. You'd need to follow a huge cohort of people who you test for vitamin d often enough so that while they're getting the infection we see their vitamin d in real time.

> Is it?

Yes, in the usual sense medical researchers use the term "risk factor", e.g., having a heart attack is a risk factor for having one of your great-grandparents die of a heart attack. Taking vitamin D probably won't reduce your covid risk, but it might, and it's a low-risk intervention that probably isn't harmful, so you should do it anyway unless you have some contraindication such as a high risk of kidney stones. The best review I've seen of the research literature is this post:

https://astralcodexten.substack.com/p/covidvitamin-d-much-mo...

(That post isn't medical advice, but this comment clearly is.)

Not a lot of people seem to know, but in the UK VitD supplements are recommended by the NHS for practically everyone in Winter.

AIUI, VitD is involved in T-cell production and so is needed to maintain our immune systems.

This is our course not medical advice.

It's not an oversight, it's a limitation of how the study was conducted - you can't check for Vitamin D levels through an app.

But what you can do in this study, is have a dataset with a good size (4m people from the UK!) which allows for much broader analysis than would be possible through other means.

Blood testing 4m people during a pandemic is impractical, and widescale self-reporting will provide insights not otherwise available (as this paper shows).

> Blood testing 4m people during a pandemic is impractical

On at least two occasions China has swab-tested 10 million people in a single city within a week, when covid re-occurred in a city where it had been thought to be extirpated. I don't think blood testing is twice as difficult as swab testing. So, I don't think it's impractical per se. It's just impractical in the UK.

You know what's impractical? 2.7 million people dying and an unknown fraction of the survivors suffering disabilities and injuries such as diabetes, heart attacks, and cerebrovascular attacks.

In your example in China they were swab testing for the virus in an attempt to measure/control its spread.

That’s different to focusing resources on doing vitamin D testing for a speculative study to determine if there is a link between vitamin D and long Covid.

I’m just saying that given limited resources during this global pandemic, the best use of resources at present probably isn’t monitoring 4 million people’s vitamin D levels for this specific study.

I’m also saying that not every study has to study every possible factor - in fact this is almost impossible to do! This is a brilliant dataset of millions of people self reporting, and there are things that you can find with self reporting that you can’t find with blood testing (and visa versa). This is why other papers will do a literature review to compile together the results of multiple studies to understand the impact.

That's a fair point: in China they weren't screening for unknown risk factors like hypovitaminosis D either. And if hypovitaminosis D is a large risk factor (it is, though the causal relationship is unclear—it may just be a comorbidity stemming from some other underlying cause that increases covid risk) studies with much less power should be able to find it (and they did).

Agreed, there are also other limitations with self reporting like you can’t assess the genetic impact and the data will be messier as people misinterpret questions.

Low levels of Vitamin D are correlated with a lot of bad things, but only for a few of them vitamin D supplementation seems to lead to betterment.

https://en.wikipedia.org/wiki/Vitamin_D#Use_of_supplements

Because Vitamin D is involved in so much physiology there are many related factors. Low sleep and sleep debt are common and getting enough sleep is associated with higher Vitamin D levels. Stress is common and finding ways handle stress is associated with increased Vitamin D levels. Vitamin D is present in eggs, oily fish, and organ meats. One of the most effective ways of increasing Vitamin D is to get some sun close to mid day. This is another example of cascading factors as making time to be outside at mid day tends to result in a range of other changes opening up diet options, increasing exercise, improving mood, and so on.

So your knee jerk reaction is strictly speaking true yet also a distraction.

Something I've noticed: when people in my surroundings bring up worries of long-term effects of the fast-tracked vaccines, they somehow tend to not consider the unknown long-term effects of covid. Even though the argument that we cannot know the long term effects yet should apply equally.

When I bring this up they do seem receptive to this argument though, provided I'm not dismissive of their own skepticism. I'm not trying to convince them to get vaccinated, but I do wish that my friends stay safe until the pandemic is over at least, so I ask them to please be consistent and be worried about the unknown long-term effects of getting covid. Especially given that for the latter we do know that it's an actual disease that has already taken lots of lives and given lots of people long-term symptoms.

You can't neglect the prior. In most European countries, somewhere around 5% of the population might have been infected with covid. Up to around 10% in the US. Therefore, to have comparable posterior probabilities for long-term side effects, you would need the side effects argument not to merely "apply equally", but to favour the vaccine over the disease by a factor of about 10.

You're not wrong, but my priority is to ensure that my friends who rely on emotion-based arguments (fear of the unknown regarding the vaccines, dismissing the risks of covid and taking too few precautions as a result) to be safe and to not contribute to keeping the pandemic going. Going this deep into statistics would just lose them, because I'd come across as trying to intimidate them into taking my viewpoint on how to reason about these things.

edit: apparently none of you have ever been accused of being an ivory tower jerk in their lives, explicitly or implicitly, ever? We're not talking about a discussion between people trying to weigh uncertainties based on what they do and do not know and working it out on a paper napkin. We're talking about people being overwhelmed by the complexity of it all and as a result starting from what they're most scared of and reasoning backwards from there. Which is how most people out there function, like it or not.

>my friends who rely on emotion-based arguments

Isn’t every argument based in emotion? Do unpalatable facts have a strong track record of success in arguments?

No. A lot of modern physics for example still seems objectively wrong when hearing about it as a student. Physical experiments and math has converted a lot of skeptics into believing some very “strange” things about how our universe works.

Are you saying that over a time period longer than a conversation or argument people who committed to learning a topic in depth were able to alter prior beliefs that were based in their lived experiences?

An argument isn’t some specific length of time. A 20 year bet on some outcome is a single argument that takes decades.

>Going this deep into statistics would just lose them

The comment’s text quoted above leads me to believe “argument” in this context refers to a shorter length of time rather than a longer one spent in deliberate study of the argument’s topic. Do you have a different interpretation of the comment to which this particular thread is devoted?

Acceptance of some of those strange observations relied on the older generation - with strong emotional attachment to the old way of looking at things - dying off.

That’s extremely overstated.

Einstein for example complained about spooky action at a distance, but didn’t disagree with the results. “Quantum mechanics is very worthy of respect. But an inner voice tells me this is not the genuine article after all. The theory delivers much but it hardly brings us closer to the Old One's secret. In any event, I am convinced that He is not playing dice.”

So, he was completely on board with the results of the single photon double slit experiment and other observable results which are very odd. But, he may have favored non local hidden variable theories which are indispensable from QM and all it’s observable oddities.

It's a dynamic not entirely confined to quantum physics in the 1930s, and there's a range of graciousness involved. It's a side effect of the paradigm shifts described by Kuhn: What happens to the old guard? Some will adapt to the new paradigm, some will enjoy tenure and let their students carry the new torch, and some will join the church in denouncing these heretics who deny the primacy of the earth. (And will happily say as much in their grant reviews!)

Also keep in mind that the stakes are higher when it's the academic's core area of contribution which is under attack. Einstein's contributions to large scale physics were secure. If instead good we're playing dice at the scale of solar systems, threatening to obviate his primary contributions and consign his name to the dustbin of history, the reaction may have been a bit different.

Not to completely disagree, but Einstein won the 1921 Nobel prize for photoelectric effect which demonstrates the quantum nature of light. I was using him as one of those pioneers which where faced with the universe acting strangely rather than anything to do with relativity.

So, yes some people will object long term, but it’s important to keep their objections in context. Plate tectonics is a slightly more recent revolutionary idea that actually converted most skeptics, but the early objections where reasonable and the actual conversion was quick once the idea approached it’s modern form.

"I was using him as one of those pioneers which where faced with the universe acting strangely rather than anything to do with relativity."

Yeah, all I'm saying is that his total collection of contributions wasn't at stake here, so it was probably a bit easier to back down.

FWIW, my 'motivating anecdote' in this discussion is an old prof describing the earlier years of algebraic topology, which he had been very active in. There were apparently a number of older topologists who were pretty resistant to algebraization of the field. Which possibly had a lot to do with Poincare's attitudes about logic and proof.

https://en.wikipedia.org/wiki/Henri_Poincar%C3%A9#Character

Depends on the setting. Among educated professionals - it's how science gets done. So even though the process is flawed, it's still more consistently fact-based than emotion-based.

But some people's arguments are based exclusively on emotion.

And they tend to be very bad at estimating risk, because they literally can't tell the difference between one specific tragedy which triggers their emotions because it's reported in great deal, and millions of tragedies which don't trigger their emotions because they're reported as dry statistics.

If we were being less polite, we'd call this a form of cognitive handicap.

https://www.eurekalert.org/pub_releases/2020-04/ttu-pra04092...

Is your claim that people whose “arguments are based exclusively on emotion” are “very bad at estimating risk?”

Do you use the term “argument” as meaning a decision making process or an advocacy method?

Is there a significant population of people who base a decision making process “exclusively” on emotion or is that a straw person? (And how do you know that?)

If there were a significant population of people whose decision making process was based on emotion, how would one falsify the premise that they are “bad at estimating risk?”

Given the causality claim that emotion based decision making poorly estimates risk due to availability cognitive bias, could the same causality claim be made that “educated professionals” are often bad at estimating wholistic risk because tunnel vision is also a product of their specialization?

Not sure why you were downvoted because what you are talking about is the reality on the ground for a lot of people. I'm dealing with this with some family members now. "I heard everyone in Europe is getting blood clots from their vaccine." is a common statement even though it's factually untrue. It's not coming from a place of logic, but emotion and has to be handled appropriately, otherwise you lose them.

If your friends accuse you of being an ivory tower jerk for adding nuance to a conversation, you should probably get better friends.

Without vaccination, the chance of eventually catching the disease is just about 100%. Yes, any single person may try and hope to be protected by herd immunity. But there are serious doubts that can be achieved given some variants' higher virulence and expected levels of eventual vaccine uptake considering justifiable reasons.

Meanwhile, long-term harms from vaccination are entirely speculative. There isn't even a real theory as to any mechanism to cause any such effects: all components of the vaccines are well-known, except the COVID-specific parts which are a strict subset of the actual virus.

"Meanwhile, long-term harms from vaccination are entirely speculative."

I don't think this is a safe thing to say about mRNA vaccines, which are brand new. IIRC one of the vaccines is essentially an old-style vaccine made for COVID, and for that one you may be able to reasonably say that, but not the new stuff that has never been mass-deployed before.

Nor does this mean they're automatically bad either. There's always a first time for something new. I'm just saying that it isn't really justified to apply decades of experience with one type of vaccine to another blindly.

The other US approved vaccine is a live viral carrier that has only been used fairly recently in experimental treatments (I think maybe an Ebola vaccine using it got approved recently?).

The CDC estimates around 25% of the US population has been infected so far.

https://www.cdc.gov/coronavirus/2019-ncov/cases-updates/burd...

It'll probably settle around 33-35% since that number is just for 2020.

Roughly 37% of the US population was infected. A large fraction of Americans never took it seriously. Does that sound familiar? Oh yeah, climate change.

Well one pretty big side effect of the disease is death, which is very long term and we know the vaccines prevent way above 10x. So that should probably count for more.

That the vaccine is better than the disease seems a ridiculously low bar to me. I'd be much more reassured if they listed the side effects with their likelihoods (1 in ??) subdivided this with age groups if appropriate, I've seen this in NHS prescriptions in the past and its always been very reassuring.

Every medication publishes this information and must include it in every box shipped. It has been available since approval if you Google “vaccine name” + prescribing information.

The fact that I have yet to see it discussed in 1000s of news articles shows how ineffective news is as an information source.

> fast-tracked vaccines

It would be accurate to say that these vaccines have been developed in the optimal time, and vaccines are usually 'slow-tracked'. Nothing has been rushed here in the sense of cutting clinical corners. The development of these vaccines has gone through the same phases of testing that every other vaccine has.

Things that slow down all vaccine development: funding, finding volunteers for testing groups, committee approval for the development of vaccines, submission and resubmission of proposals to name but a few.

All of these barriers were removed by governments throwing cash at the various companies, and the companies and universities themselves removing barriers.

> Nothing has been rushed here in the sense of cutting clinical corners. The development of these vaccines has gone through the same phases of testing that every other vaccine has.

They were approved for emergency use, which means skipping tests for long-term side-effects, because those usually take around two years. Every other vaccine has been around for a while and gone through this.

Not to mention this is these are the very first mRNA vaccines deployed in this scale.

We’re going to be honest about long-term risks, and possibilities, we can’t just hand waive this away.

It’ll be fine. But pretending that long term risk isn’t there because we don’t want it to be isn’t very sciencey.

It’s wrong to equate these to previous vaccines in multiple ways.

In the past "long term" side effects meant within weeks after the fact. This includes things like autoimmune disease. However, the statistical signal may only appear years later. The mRNA vaccines also don't "infect" the whole body, but only the injection site, and they are metabolized quickly. There really is no reason to assume any late effects say 5 years later.

If they were frequent late side effects, we would totally know by now.

By the way, they are a brilliantly less complex system, much easier to reason about, than traditional vaccines.

> because those usually take around two years

As I said in my parent comment, COVID vaccines appear 'fast tracked' because all the bureaucracy was removed to expedite them.

Every phase of clinical trials have been followed otherwise the MHRA (and the EMA) would not have approved them.

https://www.nhs.uk/conditions/clinical-trials/

All vaccines have been through phases 1-3.

> skipping tests for long-term side-effect

That would be the standard phase 4 being "The safety, side effects and effectiveness of the medicine continue to be studied while it's being used in practice." "Only carried out on medicines that have passed all the previous stages and have been given marketing licences – a licence means the medicine is available on prescription."

Phase 3 under normal circumstances from that link:

> Trials often last a year or more and involve several thousand patients.

Also this seems to be a US/UK difference, as over here phase 3 includes long-term safety before it's approved for use, with emergency use authorization to skip that being the exception: https://coronavirus.jhu.edu/vaccines/timeline

> Trials often last a year or more and involve several thousand patients.

Agreed. Though not all last a year, and the COVID trials had large numbers of volunteers.

I defer to someone that works in the industry to say whether vaccine trials last longer than regular medicine (e.g. Parkinsons or Alzheimers drugs).

But I suspect that vaccines need less time for trials because vaccines are made using standardised processes that are tweaked to produce the expected responses, vs. novel drugs that have never been synthesized before.

This one [0] in the UK famously went wrong: "The German company that developed the drug hoped it would revolutionise treatment of leukaemia and rheumatoid arthritis.

But within minutes of having the drug administered, all of the test subjects began feeling unwell."

0. https://www.bbc.co.uk/news/magazine-35766627#:~:text=When%20....

Normally you won't have an incidence rate this high, therefore you need to run the trails for longer to get enough people in the control group sick. Massive amounts of volunteers and a high prevalence made sound statistics possible in a relatively short amount of time.

"Long term" side effects mean weeks or few month later, not years as many people assume. In the past things like rare autoimmune disease associated with vaccination appeared within weeks after the dose, but it may take years to pick up the statistical signal, which may explain this belief. There is literally no reason to assume the mRNA vaccines will cause side effects 5 years later or something.

The known effects of LC are horrendous: permanent damage to the brain, heart, lung, kidneys, liver, and pancreas.

> The known effects of LC are horrendous: permanent damage to the brain, heart, lung, kidneys, liver, and pancreas.

None of these are "known effects". If you count "things that have happened to someone after contracting SARS-CoV2" as "long covid", then an entire universe of medical maladies is included in the set that may or may not be causally related.

There are specific examples of patients with severe cases of SARS-CoV2 infection who have had damage to particular organs. However, it is misleading to draw a connection from these to the broader phenomenon of "long covid", which is neither well-characterized, nor necessarily related to these acute situations.

The ambiguity in terminology here is being used to loop in everything from minor headaches to lung damage due to mechanical ventilation.

Look at the cadaver studies.

Cadavers from Covid 19 have (by definition) not had very much time to recover from long covid.

Strawman. That's not the point. The point is the permanent damage SARS-CoV-2 has on numerous organ systems. People also survive COVID-19 illness and die from other things.

If you pick a pile of dead bodies and look for things that killed them, you will find things.

> For the reduced logistic regression model, the score was given by the following formula: S = 0.259503 × NumberSymptoms + 0.055457 × age − 0.633310 × sex − 3.20 (where sex is encoded as 1 − female/2 − male) Where ‘NumberSymptoms’ corresponds to the sum of different symptoms experienced over the first week among the list of 14 symptoms reported on daily logs. This score was then transformed to a probability using the formula: 1/(1 + exp(−score))

> App users were disproportionately female, and those over 70 years of age were underrepresented, which could increase or decrease our estimate of the prevalence and duration of long COVID.

So basically if the patient is a 30 y.o man with 7 symptoms has almost twice more chance of having long covid than a woman on the same conditions ? Hmmmmmmmmmmm

Not an epidemiologist so don't weigh my opinion too highly, but as a data analyst, my first impression of this "model" is overfitted nonsense.

I checked the paper to try and defend it, but I was unable to find a table with significance testing or standard errors for this regression - it is just stated without justification.

This seems an unusual style of reporting results, to me. (Happy to be corrected)

I don't see a table but Fig 3 presents 95% confidence intervals for the odds ratios in the logistic model.

Gender differences wouldn't be unheard of. Also, in that model, being male reduces your predicted probably of long COVID.

This model does seem kinda wacky though. Just throwing in 1 symptom, age of 30, and female gives a probability of 13% which seems high. I'll have to read the paper more carefully to figure out what exactly that probability is supposed to mean.

GP is saying that the model appears to directly contradict the abstract, which says females are more affected.

No. A woman, at any age and number of symptoms, has twice the risk of a man. Which was already well-known before.

I find that particularly interesting considering that men are more at risk of dying from Covid.

Maybe women have a somehow weaker immune response, making it harder to clear the infection, but lowering the risk of a deadly overreation.

I wonder if there is serious research about that.

Women have a stronger immune system, which tends to lead to better resilience against dying from infections, but also greater susceptibility to autoimmune disease. Which long covid might well be.

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