Escribir un comentario

Summary

The study examines whether connective tissue variation, measured through joint hypermobility, is associated with Long COVID. The authors used a retrospective online survey of 1,816 participants from the United States and United Kingdom. Of these, 352 reported Long COVID and 1,464 reported full recovery.

Hypermobility was assessed with the 5-part questionnaire and with a new measure that identifies the top 10 percent of respondents in age- and sex-adjusted hypermobility scores. Logistic regression models that controlled for sex, age, number of infections, and vaccination found that generalized joint hypermobility increased the odds of Long COVID (OR 1.29, 95 percent CI 1.00 to 1.65). The new extreme hypermobility measure showed a stronger association (OR 2.12, 95 percent CI 1.43 to 3.16).

The authors conclude that connective tissue variation may be an underrecognized risk factor for Long COVID.

Discussion

Strengths

• The topic is timely and relevant.

• The sample size is large and includes participants from two countries.

• The study evaluates both standard and newly developed hypermobility measures.

• The statistical models control for several important variables.

• The mediation analysis adds useful context about possible pathways.

Limitations

• Both hypermobility and Long COVID status are self-reported. This increases the risk of misclassification and recall bias.

• The extreme hypermobility measure is new and has not been validated outside this dataset.

• The online survey design introduces selection bias, because individuals with chronic symptoms may be more likely to participate.

• Hypermobility often overlaps with conditions such as dysautonomia, chronic pain, and chronic fatigue. These conditions were not controlled for and may confound the findings.

• The cross-sectional design prevents strong conclusions about causality.

• Proposed biological pathways are speculative and not directly tested.

• The clinical relevance of the findings is uncertain, especially for the modest effect size of generalized hypermobility.

Results and Critical Appraisal

• The association between generalized joint hypermobility and Long COVID is statistically marginal, showing that any increased risk in this group may be small or sensitive to residual confounding.

• The stronger association for extreme hypermobility is more compelling and suggests a possible gradient of risk.

• Sensitivity analyses show similar results, which supports the main findings within the constraint of the study design.

• Mediation analysis is informative but should be interpreted cautiously because both exposure and outcomes are self-reported.

Conclusions and Recommendations

This study presents an interesting early finding that hypermobility traits may increase the risk of Long COVID. The work is valuable as exploratory research. To strengthen the manuscript, the authors should:

• Expand the discussion of limitations related to self-report and sample selection.

• Clarify how the extreme hypermobility metric was constructed and discuss plans for validation.

• Consider additional confounders that are common in people with hypermobility, such as chronic pain and other pre-existing conditions.

• Provide more detail on potential biological mechanisms, specifying how and what.

• Outline future research using prospective designs and clinical hypermobility assessments.

Competing interests

The author declares that they have no competing interests.

Use of Artificial Intelligence (AI)

The author declares that they used generative AI to come up with new ideas for their review.