KCL: New study identifies those most at risk from 'long COVID' Oct 2020

Sly Saint

Senior Member (Voting Rights)
A new analysis by researchers at King’s, using data from the COVID Symptom Study app, shows that one in 20 people with COVID-19 are likely to suffer symptoms for 8 weeks or more (so-called ‘long COVID’), potentially adding up to many hundreds of thousands in the UK and millions worldwide.

Led by Dr Claire Steves and Professor Tim Spector at King’s, this study focused on data from 4,182 COVID Symptom Study app users who had been consistently logging their health and tested positive for COVID-19 through swab PCR testing.

The team found that older people, women and those with a greater number of different symptoms in the first week of their illness were more likely to develop long COVID.

The researchers have used this information to develop a model that can predict who is most at risk of long COVID based on their age, gender, and count of early symptoms. Statistical tests showed that this simple prediction was able to detect more than two thirds (69%) of people who went on to get Long-Covid (sensitivity), and 73% effective at avoiding false alarms (specificity).

The team then tested this model against an independent dataset of 2,472 people who reported a positive coronavirus antibody test result with a range of symptoms and found that it gave similar predictions of risk.

The research could be used to help target early interventions and research aimed at preventing and treating this condition.
https://www.kcl.ac.uk/news/study-identifies-those-most-risk-long-covid

eta:
"The findings are due to be published as a pre-print on Medrxiv and have not yet been peer-reviewed."
 
Looks interesting.

If age and gender are predictive of developing long COVID, perhaps that means that those patients tend to be young and female while those at risk of developing a severe form of acute COVID-19 tend to be older and male. Have to wait until the preprint is out, but that would be an interesting result.
 
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Important to keep in mind that this could be biased in various ways.

The way that covid was initially viewed could influence which age group was tested, which symptoms were considered to be sufficient to justify a test, what symptoms were tracked.

The same biases would also affect the control group.
 
As was pointed out, this is likely an undercount because of the number of Long Covid patients who stopped logging on the app because it doesn't fit their symptomology:



Also unclear whether they consider all symptoms or drop some they don't consider relevant.

Honestly just give money to patient groups instead, they do a much better job at this. This whole effort is hindered by the fact that people don't know what questions to ask yet always restrict their studies to questions they can think of.
 
Female, over 55 and overweight were, I think, the 3 most likely qualifying criteria as stated on the news this evening. Still doesn't explain the preponderance of women who suffer from ME, though.
 
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The language used suggests this will be badly misused in the same way medicine has anchored for months (and ongoing for the most part) on the picture of old man with shortness of breath and fever, excluding those who don't fit those criteria rather than those criteria being used simply as a guide. Which itself created the problem of so many who should have had a test taken were denied and now face discrimination because of something that was refused to them as if they themselves were responsible for that decision.

It's like a weird game of not-learning-from-lessons.
 
This whole effort is hindered by the fact that people don't know what questions to ask yet always restrict their studies to questions they can think of.

Can we insist that anyone, anywhere who ever considers writing a health questionnaire first has to have this tattooed backwards on their forehead so they have to read it every morning in the mirror?
 
I think this research is potentially interesting. I haven't read the paper, but I am participating, along with over 4 million others, in filling in the daily app questions 'Have you had a Covid test' and 'Do you feel physically normal'.
If you answer that you've had a test, or that you have symptoms, you get more boxes to tick.

It has been running from early in the pandemic, so they have data for millions of people over months, and can see patterns of things like what symptoms are most common, and how long they last. I think that is a valuable source of research data.
 
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