Validation of China's 2025 high-risk criteria in RT-PCR-confirmed chikungunya inpatients: a single-centre retrospective cohort

2025年中国基孔肯雅热住院患者高危人群标准的验证:一项单中心回顾性队列研究

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Abstract

BACKGROUND: China’s 2025 clinical guideline designates age ≥ 65 years, pregnancy, and chronic comorbidity as patient categories requiring prioritized monitoring; quantitative validation in inpatients is lacking. METHODS: We conducted a single‑centre retrospective cohort including 131 consecutive RT‑PCR-confirmed patients admitted during an imported outbreak (1 August−30 September 2025). Patients meeting any high‑risk criterion were classified as high‑risk. The primary endpoint was length of stay (LOS). Secondary endpoints were prolonged hospitalisation (≥ 7 days), prolonged fever (≥ 3 days), and an acute laboratory‑injury composite at admission defined as at least one abnormality among seven routine tests. LOS was modelled using a Gamma generalised linear model (log link). Binary endpoints used robust Poisson regression adjusted for prespecified covariates. For the composite endpoint, available‑case analysis provided the primary estimate (missing D‑dimer values were treated as normal). Multiple imputation (MI; m = 10) and inverse‑probability weighting (IPW) analyses were prespecified sensitivity checks. RESULTS: Fifty‑three of 131 patients (40.5%) were high‑risk. High‑risk status was associated with longer LOS (time ratio 1.15; adjusted mean + 0.69 days; 95% CI 0.06–0.28). Under MI, high‑risk patients had a higher probability of acute laboratory injury at admission (aRR 1.37; 95% CI 0.87–2.17; P = 0.174). Sensitivity analyses yielded attenuated and method‑dependent estimates; the IPW model gave an aRR of 1.19 (95% CI 0.88–1.61; P = 0.253), indicating sensitivity to missing‑data assumptions. No patients required ICU admission or died (0/131). CONCLUSION: China’s 2025 high‑risk criteria identify chikungunya inpatients with longer LOS, supporting targeted early monitoring and resource planning. The admission laboratory‑injury signal was sensitive to missing‑data modelling and should be interpreted cautiously pending external validation. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12879-025-12421-0.

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