Predictors of chronic arthralgia after chikungunya virus infection: a systematic review and meta-analysis

BACKGROUND: Chikungunya is an expanding global health threat, with chronic arthralgia representing the main long-term driver of disability. Although many studies have assessed post-chikungunya outcomes, evidence remains fragmented and contradictory. We aimed to identify reproducible predictors of chronic arthralgia (≥3 months) after laboratory-confirmed chikungunya and to distinguish stable prognostic signals from context-dependent associations. METHODS: We searched PubMed, Embase, Cochrane Library, and BVS/LILACS from inception to Feb 6, 2026, without restrictions. Eligible studies compared participants with and without chronic arthralgia at follow-up and reported extractable baseline or acute-phase factors. Two reviewers independently screened records, extracted data, and assessed risk of bias using QUIPS. Random-effects restricted maximum likelihood meta-analyses pooled odds ratios and mean differences, with subgroup analyses by follow-up window. PROSPERO: CRD420251169320. RESULTS: Of 1784 records, 29 studies were included, comprising 4108 participants: 1838 with chronic arthralgia and 2230 without. After harmonization, 22 predictors were meta-analyzed. The most consistent associations were female sex (OR 2.08, 95% CI 1.77-2.46; I2=8.3%), comorbidity presence (1.99, 1.55-2.55; I2=0%), and high blood pressure (1.52, 1.13-2.04; I2=33.4%). In contrast, several acute-phase manifestations and treatment-related markers showed less stable, timing-dependent, or study-sensitive associations. Overall risk of bias was high in most studies and moderate in the remainder. CONCLUSIONS: Chronic post-chikungunya arthralgia was most reproducibly associated with readily identifiable baseline host factors, rather than with a uniform acute-severity phenotype. These findings suggest that risk stratification should not rely only on acute symptom burden, and that pre-existing vulnerability may define a clinically important high-risk group. Point-of-care identification of patients with these characteristics could support prioritization of follow-up and resource allocation during outbreaks, inform post-outbreak surveillance and guideline development, and may guide future burden-based vaccination strategies in endemic settings.