ArticleBMC infectious diseases2025
Prognostic nutritional index as an early predictor of mortality in patients with severe fever with thrombocytopenia syndrome: multicenter retrospective study in South Korea.
Article in BMC infectious diseases, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.
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Who cites it
3 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Prognostic value of the prognostic nutritional index in sepsis, pneumonia, and tuberculosis: a systematic review and meta-analysis.Frontiers in medicine · 2026Pooled it
- Commentary on "Low Thoracic Muscle Mass: A Novel Indicator of Poor Prognosis in Patients With Severe Fever With Thrombocytopenia Syndrome".Immunity, inflammation and disease · 2026Article
- A novel prognostic nomogram for elderly patients with severe fever with thrombocytopenia syndrome.BMC geriatrics · 2025Article
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Authors and funding
19 authors.
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Abstract
BACKGROUND AND
aimSevere fever with thrombocytopenia syndrome (SFTS) is a fatal tick-borne infectious disease lacking effective treatments or vaccines. Early identification of prognostic factors is essential for optimizing clinical management. This study investigated the predictors for mortality in SFTS patients.
methodsWe conducted a retrospective multicenter cohort study of 413 SFTS patients hospitalized in South Korea from 2013 to 2024. Clinical and laboratory data were comprehensively analyzed to evaluate associations between in-hospital mortality and various inflammatory, immune, and nutritional biomarkers. Cox regression and time-dependent receiver operating characteristic (ROC) analyses were performed to identify risk factors.
results413 patients diagnosed with SFTS were included and In-hospital mortality was 17% (70/413). Multivariate Cox regression identified older age (HR: 1.042; 95% CI: 1.014-1.071), elevated PT(INR) (HR: 109.57; 95% CI: 19.79-606.57), and lower prognostic nutritional index (PNI) (HR: 0.937; 95% CI: 0.886-0.990) as early predictors of mortality. Time-dependent ROC analysis demonstrated predictive accuracy, with AUCs of 0.512 for age, 0.857 for PT(INR), and 0.694 for PNI at 30 days. Kaplan-Meier analysis revealed significant survival differences for patients stratified by PNI (< 40.75), PT(INR) (≥ 0.97), and age (≥ 59 years).
conclusionsPNI, PT(INR), and age were identified as key early predictors of mortality in SFTS. PNI, as a novel biomarker, was found to be a useful index for risk level and treatment strategies in SFTS patients. CLINICAL TRIAL NUMBER: Not applicable.
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