Key result
Adding resting heart rate improves CAIDE model prediction of 3-year cognitive decline to AUC 0.65.
Why the study?
Accurate and accessible risk assessment tools for dementia are essential, and enhancing the CAIDE model with resting heart rate and machine learning may improve prediction accuracy.
Does incorporating resting heart rate and machine learning into the CAIDE model improve the prediction of 3-year cognitive decline in aging adults?
Cohort (n=27,768)
Does incorporating resting heart rate and machine learning into the CAIDE model improve the prediction of 3-year cognitive decline in aging adults?
Incorporating resting heart rate into the CAIDE model using machine learning significantly improves the predictive accuracy for 3-year cognitive decline.
No takes yet. Share an insight, caveat, or question.
May support refined midlife cognitive risk stratification; extends CAIDE but leaves open prospective validation.
Alaka et al. (2025) conducted a cohort in Cognitive decline (n=27,768). Resting heart rate (RHR) incorporated into the CAIDE model vs. CAIDE model without RHR was evaluated on 3-year cognitive decline. Incorporating resting heart rate into the CAIDE model using machine learning improved predictive accuracy for 3-year cognitive decline, achieving an AUC of 0.65 in test data.
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