Thread by @JeffLubell_C19

A new preprint confirms that generalized joint #hypermobility is a risk factor for #LongCOVID, while breaking new ground by examining risks of extreme hypermobility and whether hypermobility risk varies based on severity of initial COVID infection. 1/12 medrxiv.org/content/10.110…

Echoing prior research, this study found that, in a sample of 1,816, people w/ generalized joint hypermobility (GJH) were at higher risk of Long COVID. This comes from a regression that controlled for age, sex at birth, number of infections and number of vaccine doses. 2/12

One of the innovations of this research was to examine whether the severity of symptoms during the initial COVID infection affects the relationship between hypermobility and #LongCOVID. Answer: It does, at least in the sample studied. 3/12

Among those with mild or no symptoms during initial infection, GJH was a strong risk factor for #LongCOVID, but among those with severe initial symptoms, GJH was not a significant predictor of Long COVID. 4/12

At the same time, the study found that individuals with GJH were more likely to develop severe symptoms during the initial infection. This is one reason GJH leads to higher risk of #LongCOVID. The other is that GJH increases risk among those with mild/no initial symptoms. 5/12

The study also examines the extent to which people who were particularly hypermobility are as risk of #LongCOVID. Using 9 questions, the study identified as extremely hypermobile individuals in the top 10th percentile of hypermobility within their age and gender group. 6/12

While necessarily exploratory, this chart illustrates how the extent of hypermobility affects #LongCOVID risk. Regardless of whether they had no/mild or severe symptoms from initial infection, Long COVID spikes for people in the top 10th percentile of hypermobility. 7/12

In a discussion on pages 18-19, the article outlines several hypotheses that could help explain why hypermobility increases the risk of #LongCOVID. I will summarize these hypotheses in a subsequent thread. 8/12

The study is based on data collected in early 2024 from a sample of 1,816 respondents drawn from representative online panels in the US and UK, 352 (19.4%) who reported Long COVID and 1,464 (80.6%) who did not. 9/12

The study benefitted from a similar pilot study recruited from social media. Much thanks to everyone who completed that survey! While there were not enough non-Long-COVID respondents to analyze it separately, the pilot dataset will be included in a future metaanalysis. 10/12

Authors include @regina_anita_ @Rena_Rudy @LisaQuadt @BendyBrain and me. Deeply appreciate the ongoing collaboration! 11/12

Among other caveats: this is a preprint and has not yet been peer-reviewed; the study it limited in that it relies on a retrospective survey rather than prospective direct observation and measurement. 12/12