July 22, 2025

Machine Learning Prediction of MACE in Older Chinese Adults Integrating Traditional and Geriatric-Specific Risk Factors: A CHARLS Cohort Analysis

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Machine learning models that include both traditional and non-traditional risk factors predict MACE effectively.
The LR model achieved a mean AUC of 0.649, outperforming other models and the FRS benchmark.
Significant predictors of MACE include hypertension history, diabetes, age, and central obesity.
A practical nomogram was developed for assessing cardiovascular risk in older adults, pending further validation.

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Machine learning predicts major adverse cardiovascular events in older adults, highlighting crucial geriatric risk factors.

Li et al. (2025) studied this question.

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