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Analyzing prehospital delays in recurrent acute ischemic stroke: Insights from interpretable machine learning
Youli Jiang1, Qingshi Zhao1, Jincheng Guan1
1Department of Neurology, People's Hospital of Longhua, 38 Jinglong Jianshe Road, Longhua District, Shenzhen 518109, China.
Patient Education and Counseling
|March 8, 2024
Summary
Prehospital delays in recurrent Acute Ischemic Stroke (AIS) are common, similar to first-time AIS. Lack of stroke knowledge and living situation significantly impact these delays, necessitating targeted public health education.
Area of Science:
- Neurology
- Public Health
- Emergency Medicine
Background:
- Prehospital delays in Acute Ischemic Stroke (AIS) impact patient outcomes.
- Understanding factors contributing to delays in recurrent AIS is crucial for timely intervention.
Purpose of the Study:
- To investigate prehospital delays in recurrent AIS patients.
- To identify key factors contributing to these delays.
- To inform targeted interventions for improving stroke response times.
Main Methods:
- Retrospective cohort analysis of 1419 AIS patients (December 2021 - August 2023).
- Utilized Extreme Gradient Boosting (XGBoost) and SHapley Additive exPlanations (SHAP) for determinant analysis.
Main Results:
- Living situation and stroke knowledge deficits are significant risk factors for delayed hospital presentation in recurrent AIS.
- Key influencing factors include residential status, symptom awareness, comorbidities (diabetes, coronary artery disease), and stroke type.
Conclusions:
- Prehospital delay patterns in recurrent AIS are comparable to first-time AIS, indicating a knowledge gap.
- Enhanced stroke education and public health initiatives are essential to reduce delays and improve outcomes for all AIS patients.
