Exploring the Recovery Curves for Long-term Post-COVID Functional Limitations on Daily Living Activities..., 2022, Fernández-de-las-Peñas et al

Andy

Andy

Retired committee member
Full title: Exploring the Recovery Curves for Long-term Post-COVID Functional Limitations on Daily Living Activities: The LONG-COVID-EXP-CM Multicenter Study

To the Editor

Evidence supports that almost 60% of COVID-19 survivors will experience post-COVID symptoms during the first months after infection [1
These symptoms lead to a decrease in health-related quality of life and function [2]. One full-text [3] and three letters to the editor [4,5,6] published in Journal of Infection have evaluated the presence of functional limitations as post-COVID sequalae in individuals who had survived to COVID-19. Most of studies investigating post-COVID functional limitations are cross-sectional since they assessed related-disability just at one follow-up period. Understanding the longitudinal evolution of post-COVID functional limitations might have implications for optimizing patient care and public health outcomes. We present here two approaches for potentially analyzing the longitudinal recovery curves of post-COVID functional limitations in a sample of previously hospitalized COVID-19 survivors: 1) mosaic plots of the prevalence of functional limitations during the first year after hospitalization; and, 2) a bar plot of the evolution of functional limitations, fitted with an exponential decay model to help in its longitudinal interpretation.

The LONG-COVID-EXP-CM is a multicenter cohort study including individuals with a diagnosis of SARS-CoV-2 (ICD-10 code) by RT-PCR technique and radiological findings hospitalized during the first wave of the pandemic (from March 10 to May 31, 2020) in five urban hospitals of Madrid (Spain). From all patients hospitalized during the first wave, a sample of 400 individuals from each hospital was randomly selected. The Ethics Committees of all hospitals approved the study (HCSC20/495E, HSO25112020, HUFA 20/126, HUIL/092-20, HUF/EC1517). Informed consent was obtained from all participants.

Open access, https://www.journalofinfection.com/article/S0163-4453(22)00030-5/fulltext
 
That recovery curve is unbelievably stupid.

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On the basis of patients' responses at 2 points up to a year apart they have drawn exponential decay curves extending for over 4 years. Didn't anyone teach them in stats using real data not to extrapolate beyond the range known data?
Yet they confidently conclude:
In conclusion, our tendency analysis revealed that post-COVID functional limitations during daily living activities tend to slowly recover during the following five years after SARS-CoV-2 infection in previously hospitalized COVID-19 survivors.
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I think we all know that most people who recover from post viral illnesses so in the first year or 2 then if they haven't recovered they get diagosed with ME and very few recover. There's no reason to assume a simple exponential decay model is in any way appropriate.
 
Trish said:
That recovery curve is unbelievably stupid.

gr2.jpg

On the basis of patients' responses at 2 points up to a year apart they have drawn exponential decay curves extending for over 4 years. Didn't anyone teach them in stats using real data not to extrapolate beyond the range known data?
Yet they confidently conclude:

I think we all know that most people who recover from post viral illnesses so in the first year or 2 then if they haven't recovered they get diagosed with ME and very few recover. There's no reason to assume a simple exponential decay model is in any way appropriate.
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it is like a metaphor for the whole lives being wrecked by dead-headedness of medics with ME what they've done here. Some idiot not remembering that extrapolating forward and indeed inference is based on ASSUMPTIONS. Drawing the lines past this point of 'this is what happens when someone goes back to work, their PEM is ignored by those round them etc' onto the chart in a big thick bright pink line would be a picture-based demonstration of what they've been doing to us all for the last few decades. I'd love to somehow add in with a massive arrow that the more they stick to that 'but they should be following THIS line' mentality the WORSE they make the outcome on the big thick pink line. ie they are the cause.

I think we have some functional fixedness and lack of innate understanding of what people are actually working with or doing - just 'going through processes' to complete whatever project by ticking box.

What I find strange is how in A level physics I had to learn about copernicus and the realisation that theories can be disabused when one little bit of info comes through. I did some sort of history of science module in my degree. Are these people going through their entire career without being taught what science actually is - and instead thinking learning non-critical thinking and parrot-fashion rules as if they never change is science simply because of what they call themselves, or whether they've ever been in a lab - or is it the white coat?

I know philosophy has a whole area noting that medicine is based on inference and forgets that science involves deduction-inference and the constant shifting back and forth between the 2, and notes how little some medics seem to be aware that infererence isn't actually science by itself. This takes the biscuit where they have become so deluded they've even removed the assumptions knowledge and don't realise the lines they've drawn for the 'future' are just groundwork against which the 'real' should be plotted in order to be interested in what actually happens next vs 'expected'. The science bit is supposed to be studying the DIFFERENCE between those lines as the data happens and then using deduction to be interested in that, not just arbitrarily extending a line that anyone could do.
 
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Without having read the paper the curves seem to indicate a belief in a discrete disease or illness process that happens for a fixed period of time and then it’s real life implications disappear over time. This ignores the possibility of further active disease/illness process(es) continuing or re-emerging.

I personally would characterise my ME as involving two vectors, one involving the short term ups and downs involving PEM, OI, food intolerances and hypersensitivities that can be managed to varying degrees, and the other that I describe as my underlying ME which involves for me longer term relapses and remissions which possibly is triggered by new viruses or sustained increased exertion. I describe my personal experience as, if I manage the short term factors sufficiently, involving some spontaneous improvement in my underlying ME, though over the decades that improvement has become slower and to a lower ceiling but also that every five to eight years I have experienced relapses with each subsequent relapse involving additional symptoms and worse overall health.

In my simplistic model the current status of the underlying ME would set the perimeters of the shorter term variation (boom & bust, PEM, etc) which relate to activity patterns and environmental factors, but the underlying ME can also vary setting the overall ‘recovery curve’ which could see steady improvement as anticipated in this study’s projections, with possible ceiling or floor effects, or for some, like me, a pattern of relapses and remissions or in others steady deterioration.

Over the first few years of my ME I could have been fitted onto a similar recovery curve as anticipated by this paper, but I see no reason for some Long Covid sufferers at least seeing such varied patterns over longer time periods paralleling those experienced by people with ME.
 
Ah, well, I just looked at the temperature outside and it's below zero so climate change solved! According to these people and their methods anyway.

Honestly though explicitly studying the pattern of LC and not really noticing that it has several patterns and most cases are relapsing-remitting is impressive...ly bad.
 
Trish said:
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This profile looks very strange. The percentages seem to rise and fall on a sort of saw-tooth pattern every 3-4 months. I would have expected much less fluctuation with reasonably large numbers and random. I wonder if there were systematic factors affecting data or data collection.

Thinking about potential shifts in time profile I wonder whether it would be useful to compare a decent profile on a large cohort for each virus variant - alpha, delta, omicron mostly. If the decay curve (i.e. non-recovery percentage curve) is the same for all variants that would suggest that there original virus is gone and just a trigger of something with its own kinetics. If the curve is different for each variant the same might be true but shifts in curve half-life or shape might point to something important.

I also think that this might be something, with decent data, that could tell us more than the original ME Dubbo study. Maybe the curve really is exponential but I am not sure that from a path-biology point of vie that makes great sense. Post-trigger illnesses probably do not have exponential kinetics. In cases I can think of there tends to be a n early phase with rapid tail off followed by a proportion that last indefinitely. I think Dubbo may have given a false impression just because numbers were not huge.
 
For me the pandemic has strengthened the idea that there isn't an easily observable difference between people who recover and those who don't. It seems to be the same illness, except for some unknown factor that prevents recovery in a portion.

Also that graph is not reassuring despite the authors trying to make it so.
 
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