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Is joint hypermobility linked to self-reported non-recovery from COVID-19? Case–control evidence from the British COVID Symptom Study Biobank

Jessica Eccles, Dorina Cadar, Lisa Quadt, Alan J. Hakim, Nicholas Gall, Vicky Bowyer, Nathan J. Cheetham, Claire J. Steves, Hugo Critchley, Kevin A Davies

2024BMJ Public Health15 citationsDOIOpen Access PDF

Abstract

Objectives: This study sought to explore whether generalised joint hypermobility (GJH, a common marker of variant connective tissue) was a risk factor for self-reported non-recovery from COVID-19 infection. Design: Prospective observational study. Setting: COVID Symptom Study Biobank (https://cssbiobank.com/) UK. Participants: Participants were surveyed in August 2022. 3064 (81.4%) reported at least one infection with COVID-19. These individuals self-reported on recovery and completed a self-report questionnaire to detect GJH (Hakim and Grahame 5-part questionnaire, 5PQ). Main outcome measures: The primary outcome was the presence of self-reported non-recovery from COVID-19 infection at the time of the survey. Additional outcomes included scores on 5PQ and self-reported fatigue level (Chalder Fatigue Scale). Results: The presence of GJH was not specifically associated with reported COVID-19 infection risk per se. However, it was significantly associated with non-recovery from COVID-19 (OR 1.43 (95% CI 1.20 to 1.70)). This association remained after sequential models adjusting for age, sex, ethnic group, education level and index of multiple deprivation (OR 1.33 (95% CI 1.10 to 1.61)) and further adjustment for vaccination status and number of vaccinations (OR 1.33 (95% CI 1.10 to 1.60)). Additionally, including in a model adjusting for all covariates, hypermobility significantly predicted higher fatigue levels (B=0.95, SE=0.25, t=3.77, SE, p=0.002). Fatigue levels mediated the link between GJH and non-recovery from COVID-19 (estimate of indirect effect=0.18, 95% bootstrapped CI 0.08 to 0.29). Conclusions: Individuals with GJH were approximately 30% more likely not to have recovered fully from COVID-19 infection at the time of the questionnaire, and this predicted the fatigue level. This observation is clinically important through its potential impact for understanding and identifying sub-phenotypes of long COVID for screening and personalised targeted interventions. More generally, greater awareness of GJH and its extra-articular associations is needed for effective patient stratification and implementation of personalised medicine.

Topics & Concepts

Coronavirus disease 2019 (COVID-19)BiobankHypermobility (travel)2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)MedicineJoint (building)Coronavirus InfectionsPsychologyPhysical therapyVirologyOutbreakInternal medicineBioinformaticsDiseaseBiologyEngineeringArchitectural engineeringInfectious disease (medical specialty)Connective tissue disorders researchSpondyloarthritis Studies and TreatmentsFibromyalgia and Chronic Fatigue Syndrome Research