Establishment and Validation of a Prognostic Risk Model for Cardiac Mortality in Patients With Severe Fever With...

Severe fever with thrombocytopenia syndrome (SFTS), an emerging tick-borne infectious disease, is associated with significant mortality rates. Cardiovascular complications are frequently observed in fatal cases of SFTS. However, the potential risk factors contributing to cardiac mortality in SFTS patients remain poorly characterized. This multicenter prospective cohort study was performed from August 2022 to June 2024. Comprehensive clinical data, including demographic characteristics, clinical manifestations, laboratory parameters, therapeutic interventions, and disease complications, were systematically collected and analyzed. The primary endpoints were defined as all-cause mortality and cardiac-specific mortality within 30 days following hospital admission. To identify optimal predictors of cardiac mortality, we employed a rigorous analytical approach combining univariate logistic regression, Boruta algorithm, and LASSO regression for feature selection. Subsequently, multivariate logistic regression analysis was performed to determine independent risk factors, which were then incorporated into a prognostic prediction model. The model's clinical utility was evaluated through multiple validation methods, including receiver operating characteristic (ROC) curve analysis, calibration plots, decision curve analysis (DCA), and clinical impact curve (CIC) assessment. The study cohort comprised 203 SFTS patients with a median age of 66 years (IQR: 58.0-72.0), including 87 male patients (42.86%). The overall 30-day all-cause mortality rate was 31.53% (64/203), with cardiac mortality (shock and fatal arrhythmia storms) accounting for 92.19% of these fatalities. We identified four independent risk factors for cardiac mortality as lymphocyte count, activated partial thromboplastin time (APTT), N-terminal pro-brain natriuretic peptide (NT-proBNP), and interleukin-6 (IL-6) levels. The prognostic nomogram, named as SFTS-Card, developed from these predictors demonstrated excellent discriminatory ability, with an area under the receiver operating characteristic curve (AUC) of 0.990 (95% confidence interval: 0.981-0.999), indicating high predictive accuracy for cardiac mortality risk. Shock and fatal arrhythmia storms are major cardiac complications associated with the mortality of SFTS. Nomogram SFTS-Card provides a favorable prediction tool for 30-day cardiac mortality of SFTS.