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Development and external validation of a risk stratification model for stroke-associated pneumonia
1Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing 100053, China.
Iscience
|August 9, 2026
Summary
A new SENTRY model predicts stroke-associated pneumonia (SAP) risk using routine data and early CT scans. This tool improves early risk stratification for better patient outcomes and clinical trial design.
Area of Science:
- Neurology
- Pulmonology
- Medical Informatics
Background:
- Stroke-associated pneumonia (SAP) is a frequent complication following acute stroke.
- SAP significantly worsens patient prognosis and clinical outcomes.
- Accurate early prediction of SAP is crucial for timely intervention.
Purpose of the Study:
- To develop and validate SENTRY, an early prediction model for stroke-associated pneumonia.
- To integrate routine admission variables with ultra-early chest CT findings.
- To enhance risk stratification for patients post-stroke.
Main Methods:
- Development and external validation of the SENTRY prediction model across eight stroke centers.
- Inclusion of variables: age, dysphagia, NIHSS score, neutrophil-to-lymphocyte ratio, and chest CT abnormalities.
- Comparison with existing scores (A²DS² and ISAN) and base models using AUC and Brier score.
Main Results:
- The SENTRY model, incorporating chest CT, significantly improved prediction accuracy (AUC: 0.886) compared to the base model (AUC: 0.811).
- SENTRY demonstrated superior discrimination to established scores (A²DS² and ISAN) in validation cohorts.
- Decision curve analysis confirmed SENTRY's greater net benefit across clinical thresholds, stratifying patients into distinct risk groups.
Conclusions:
- The SENTRY model provides accurate and reliable early risk prediction for stroke-associated pneumonia.
- Integration of ultra-early chest CT findings enhances predictive performance.
- SENTRY facilitates risk-stratified patient management and supports targeted clinical trial enrollment.