Development and validation of a novel mortality risk stratification simplified scoring scale for severe fever with thrombocytopenia syndrome.

Objectives: The global incidence of severe fever with thrombocytopenia syndrome (SFTS) has markedly increased over the past decade. There is an urgent need to establish a reliable scoring system for predicting the mortality of patients with SFTS.

Methods: In this ambispective study, 714 patients with SFTS were recruited from 11 sites in China. Among these, 544 patients hospitalized for SFTS from May 2012 to June 2022 were included retrospectively in the training cohort, and 170 were prospectively enrolled between April 2021 and November 2023 in the validation cohort. Logistic regression analysis was performed to identify risk factors for 30-day mortality. A nomogram model (SFTS-logistic model) and a simplified scoring system (SFTS-Wuhan model) were established for predicting mortality. The performance of these models in terms of calibration, discrimination, and clinical utility was evaluated and validated.

Results: The 30-day mortality rate was 12.89% (92/714). The mean age was 65 years old (interquartile range, 57-71), and 322 (45.10%) patients were male. The SFTS-logistic model and SFTS-Wuhan model were developed based on seven independent risk factors, including age (adjusted OR [AOR], 1.062; 95% CI, 1.019-1.106), temperature at admission (AOR, 1.599; 95% CI, 1.095-2.336), white blood cell count (AOR, 0.799; 95% CI, 0.653-0.978), platelet count (AOR, 0.977, 95% CI, 0.959-0.996), aspartate aminotransferase (AOR, 1.001, 95% CI, 1.000-1.003), creatinine (AOR, 1.006; 95% CI, 1.001-1.011), and vasopressors use (AOR, 6.270; 95% CI, 1.397-28.146). Both models demonstrated good discrimination with areas under the receiver operating characteristic curve above 0.84, satisfactory calibration, and comparable clinical net benefit in the training and validation cohorts.

Discussion: The prognostic scoring model and its simplified surrogate can serve as robust tools for mortality risk stratification in SFTS, allowing the early identification of high-risk patients.