Objective  To explore the risk factors for the prognosis of patients with severe fever with thrombocytopenia syndrome (SFTS), and establish and validate a nomogram prediction model.

Methods  A retrospective analysis was conducted on the clinical data of adult patients with SFTS admitted to the Second Hospital of Anhui Medical University from April 2019 to May 2024. Patients were divided into the survival group and death group according to their survival status in the hospital. Binary Logistic regression analysis was used to determine independent influencing factors for poor prognosis in SFTS patients, and then a nomogram prediction model was constructed. The differentiation, calibration and clinical applicability of the nomogram prediction model were evaluated using the receiver operating characteristic (ROC) curve, area under curve (AUC), calibration curve, and decision curve.  

Results  A total of 271 SFTS patients were included, of which 215 were in the survival group and 56 in the death group. Binary Logistic regression analysis showed that age [OR=1.089, 95%CI(1.018, 1.166)], viral load [OR=2.047, 95%CI(1.192, 3.514)], gastrointestinal bleeding [OR=5.368, 95%CI(1.635, 17.625)], pulmonary fungal infection [OR=6.446, 95%CI(2.115, 19.645)], and serum ferritin [OR=8.198, 95%CI(1.850, 36.340)] were independent influencing factors for the poor prognosis of SFTS patients. The AUC value of the nomogram prediction model was 0.936[95%CI(0.906, 0.965)], and the AUC of the Bootstrap method after repeated sampling 1,000 times was 0.928[95%CI(0.898, 0.960)]. The calibration curve and decision curve showed that the model had good consistency and net returns.

Conclusion  Age, viral load, gastrointestinal bleeding, pulmonary fungal infection, and serum ferritin are the influencing factors for the poor prognosis of SFTS. The nomogram prediction model for the prognosis of SFTS patients constructed in this study can assist in clinical identification of high-risk patients, showing certain clinical value.

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