Dynamic evolution of key laboratory parameters predicts clinical outcomes in severe fever with thrombocytopenia syndrome (SFTS) patients: a cohort study

关键实验室参数的动态变化可预测重症发热伴血小板减少综合征(SFTS)患者的临床结局:一项队列研究

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Abstract

BACKGROUND: We explored laboratory marker patterns in patients diagnosed with severe fever with thrombocytopenia syndrome (SFTS) and evaluated their relationships with disease severity and clinical outcomes. METHODS: This retrospective cohort study included 41 patients with laboratory-confirmed SFTS at Chizhou People's Hospital (May 2020-September 2024). Stratification into severe (n = 21) and non-severe (n = 20) groups followed the 2023 Diagnosis and Treatment Protocol for Fever with Thrombocytopenia Syndrome. Demographic data, epidemiological history, baseline laboratory parameters, and serial measurements of 16 key indicators were extracted from electronic medical records. Mann-Whitney U test, chi-squared test, and Fisher's exact test were used for intergroup comparisons. Multivariate logistic regression was used to identify independent severity predictors, whereas receiver operating characteristic curves were used to evaluate the predictive efficacy. RESULTS: AST peaked on day 5 post-admission (> 10 × upper limit of normal), remaining significantly elevated throughout hospitalization in the severe group (P < 0.001). PLT counts in the severe group declined progressively (minimum: day 5, < 50 × 10⁹/L) and was significantly lower than that in the non-severe group (P < 0.0001). RBC and Hb showed continuous decline in the severe group while gradually recovering in the non-severe group after initial decrease, although no significant differences were observed between groups. Multivariate analysis identified admission WBC (adjusted OR [aOR] = 0.021, 95% CI: 0.001-0.707, P = 0.031), PLT (aOR = 0.880, 95% CI: 0.777-0.997, P = 0.045), diarrhea (aOR = 12.929, 95% CI: 1.281-130.500, P = 0.030), and neurological symptoms (aOR = 31.237, 95% CI: 1.817-536.978, P = 0.018) as independent severity predictors. ROC curve analysis revealed optimal diagnostic cutoff values for identifying severe patients: WBC < 2.4 × 10⁹/L and PLT < 48.5 × 10⁹/L. The combined model (WBC and PLT) exhibited an area under the receiver operating characteristic curve of 0.888 (95% CI: 0.776-1.000), with 100% sensitivity and negative predictive value, demonstrating decent performance in accurately predicting disease severity. CONCLUSIONS: Dynamic deterioration of AST, PLT, and RBC/Hb in patients with severe SFTS is closely associated with poor outcomes. Combined assessment of admission WBC, PLT, diarrhea, and neurological symptoms is an effective early warning indicator system for severe disease.

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