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Construction of a Risk Prediction Model for Stroke Occurrence in Septic Shock Patients: A Combined Analysis Using
Zhenhuang Lai1,2, Haihong Zhang1,2
1Emergency Department, Affiliated Dongyang Hospital of Wenzhou Medical University, Dongyang, People's Republic of China.
International Journal of General Medicine
|April 15, 2026
Summary
A new stroke risk model for septic shock patients was developed and validated. This tool helps identify high-risk individuals for timely intervention, potentially reducing mortality and disability.
Area of Science:
- Critical Care Medicine
- Neurology
- Biostatistics
Background:
- Septic shock poses a significant risk for stroke.
- Early identification of stroke risk in septic shock is crucial for patient outcomes.
Purpose of the Study:
- To develop and validate a predictive model for 90-day stroke risk in septic shock patients.
- To identify independent risk factors for stroke in this population.
Main Methods:
- Retrospective single-center study of 2127 septic shock patients.
- LASSO regression for variable selection and multivariate logistic regression for model development.
- Internal validation using nomogram, calibration curves, ROC curves, and decision curve analysis (DCA).
Main Results:
- Seven variables (age, hypertension, ALB, TC, Cr, TBIL, WBC) were initially screened.
- Age, hypertension, ALB, TC, and TBIL were identified as independent risk factors.
- The model demonstrated good predictive performance (AUCs 0.754-0.76) with satisfactory calibration and clinical utility.
Conclusions:
- The developed prediction model is effective for stroke risk stratification in septic shock.
- Early identification of high-risk patients can facilitate timely interventions.
- This model may help reduce stroke-related mortality and disability in septic shock patients.