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Improved ischemic stroke outcome prediction using model estimation of outcome probability: the THRIVE-c calculation
Alexander C Flint1, Vivek A Rao1, Sheila L Chan1
1Department of Neuroscience, Kaiser Permanente, Redwood City, CA, USA.
Summary
The new THRIVE-c calculation offers more accurate ischemic stroke outcome predictions than the traditional THRIVE score. This tool uses patient-specific data for improved risk estimation at the point of care.
Area of Science:
- Neurology
- Clinical Prediction Models
- Stroke Medicine
Background:
- The Totaled Health Risks in Vascular Events (THRIVE) score is a validated tool for predicting ischemic stroke outcomes.
- Simplified scoring systems are useful but may lack patient-specific accuracy.
Purpose of the Study:
- To develop and validate a more accurate, patient-specific ischemic stroke outcome prediction model.
- To leverage continuous variables for enhanced probability estimation.
Main Methods:
- Developed the THRIVE-c model using logistic regression on data from 12,207 subjects.
- Included THRIVE score predictors: age, NIH Stroke Scale, and chronic disease status.
- Assessed model performance using receiver operator characteristics analysis.
Main Results:
- The THRIVE-c model demonstrated consistent performance in development and validation cohorts (AUC ≈ 0.786).
- THRIVE-c significantly outperformed the traditional THRIVE score (AUC 0.785 vs. 0.746, P < 0.001).
- The model showed similar performance in external validation cohorts.
Conclusions:
- The THRIVE-c calculation provides more accurate, individualized outcome estimations for ischemic stroke patients.
- This model can be easily implemented using readily available computing devices at the point of care.
