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

Area of Science:

• Infectious Diseases
• Clinical Medicine
• Epidemiology

Background:

• Severe fever with thrombocytopenia syndrome (SFTS) is a significant public health concern with a notable mortality rate.
• Identifying prognostic factors is crucial for timely intervention and improved patient management in SFTS cases.

Purpose of the Study:

• To investigate the independent risk factors associated with SFTS patient prognosis.
• To develop and validate a prognostic warning model for predicting SFTS patient outcomes.

Main Methods:

• Retrospective analysis of 264 SFTS patients, divided into survival and death groups.
• Univariate, multivariate, LASSO, and logistic regression analyses were performed on baseline and early laboratory data.
• A prognostic nomogram warning model was constructed using identified independent risk factors.

Main Results:

• Age, consciousness disorders, blood urea nitrogen (BUN), and viral load were identified as independent risk factors for SFTS prognosis.
• The developed nomogram warning model demonstrated excellent predictive performance with an AUC of 0.917.
• The model effectively differentiates between patients with different prognostic outcomes.

Conclusions:

• The established prognostic risk prediction model provides a robust and practical clinical tool for SFTS.
• Early identification of risk factors and application of the model can aid in predicting disease progression and prognosis.
• This model can support clinical decision-making and resource allocation for SFTS patients.