Developing a Prognostic Model for Predicting the Risk of Outcome in Patients With Novel Bunyavirus Infection: A Retrospective Study

Abstract

The study aims to investigate the key risk factors influencing the prognosis of patients with severe fever with thrombocytopenia syndrome (SFTS) and develop a prognostic warning model based on these factors. A total of 264 SFTS patients treated at Tongji Hospital from April 1, 2023, to July 30, 2024, were included as the research sample. Retrospective analysis was conducted based on the final prognostic status of the patients, dividing them into a survival group (n = 165) and a death group (n = 99). Univariate and multivariate analyses were performed along with LASSO and logistic regression on baseline information and the first laboratory indicators within 24 h after admission to identify independent risk factors affecting prognosis. A warning model was constructed based on these factors. The analysis revealed that age (OR = 1.098, 95% CI: 1.054–1.149, p < 0.001), presence of consciousness disorders (OR = 2.506, 95% CI: 1.042–6.187, p = 0.042), BUN (OR = 1.248, 95% CI: 1.154–1.369, p < 0.001), and viral load (OR = 3.598, 95% CI: 2.572–5.288, p < 0.001) were identified as independent risk factors significantly impacting the prognosis of SFTS patients. A nomogram warning model was developed incorporating these four risk factors, which demonstrated excellent predictive performance (ROC = 0.917, 95% CI: 0.882–0.948, p < 0.001). The prognostic risk prediction model successfully established for SFTS patients in this study exhibits robust predictive performance, and it is anticipated to serve as a practical clinical tool for predicting disease progression and prognosis in SFTS patients.