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August 22, 2025Journal of the American Heart AssociationOpen Access

Development and Internal Validation of a Clinical Imaging–Based Stroke Prediction Model in a Community Cohort

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Authors

YWYiqing WangDZDingding ZhangFZFei‐Fei Zhai

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Overview

Prospective cohort study developed a stroke prediction model using neuroimaging data, indicating clinical benefits for risk management.

Key Points

  • The predictive model accurately estimates 5-year and 7-year stroke risk in a community cohort with 54 incident strokes observed over 8 years.
  • Key predictors in the model include neuroimaging factors like silent cerebral small-vessel disease and clinical factors like diabetes and smoking.
  • Methodology involved a prospective cohort design and Cox proportional hazards model validated through bootstrap resampling techniques.
  • Findings emphasize the importance of targeted management of key predictors for effective primary stroke prevention in community populations.

Cite This Study

Wang et al. (2025) studied this question.

synapsesocial.com/papers/68af76b27567bf4f94fef5a6https://doi.org/10.1161/jaha.125.041413
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Validation and Refinement of Scores to Predict Stroke Risk: Prospective Cohort Study2025
  2. 2Abstract 520: STRIKE: A Machine Learning Model for 10‐Year Stroke Risk Estimation2025
  3. 3Abstract 204: Machine Learning for Young Stroke Risk Prediction: An Analysis of Clinical and Biochemical Predictors2025
  4. 4Evaluating machine learning models for stroke prediction based on clinical variables2025 · 22 citations
  5. 5Predicting Stroke Risk Based on an Optimized Machine Learning Model2025