Prognostic nutritional index as an early predictor of mortality in patients with severe fever with thrombocytopenia syndrome: multicenter retrospective study in South Koreaopen access
- Authors
- Woo, Hyun Ji; Kwon, Tae-Kyu; Heo, Sang Taek; Yoo, Jeong Rae; Kim, Misun; Oh, Jaeseong; Bae, In-Gyu; Bae, Sohyun; Yoon, Young-Ran; Hyun, Miri; Kim, Hyun ah; Jung, Sook In; Kwon, Ki Tae; Hwang, Soyoon; Kim, Uh Jin; Kang, Gaeun; Kim, Young Jun; Hwang, Jeong-Hwan; Kim, Min-Gul
- Issue Date
- Feb-2025
- Publisher
- BioMed Central
- Keywords
- Biomarker; Early predictor; Prognostic nutritional index; Severe fever with thrombocytopenia syndrome
- Citation
- BMC Infectious Diseases, v.25, no.1
- Indexed
- SCIE
SCOPUS
- Journal Title
- BMC Infectious Diseases
- Volume
- 25
- Number
- 1
- URI
- https://scholarworks.gnu.ac.kr/handle/sw.gnu/77376
- DOI
- 10.1186/s12879-025-10661-8
- ISSN
- 1471-2334
1471-2334
- Abstract
- Background and aim: Severe 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. Methods: We 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. Results: 413 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). Conclusions: PNI, 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. © The Author(s) 2025.
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