Association of the endothelial activation and stress index with cognitive function in older adults: a cross-sectional study with machine learning

内皮激活和应激指数与老年人认知功能的相关性:一项基于机器学习的横断面研究

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Abstract

BACKGROUND: Age-associated memory impairment (AAMI) is a predementia state linked to endothelial dysfunction. The endothelial activation and stress index (EASIX) quantifies endothelial injury, yet its association with cognitive function remains unvalidated in population studies. This study aimed to evaluate the relationship between EASIX and cognitive performance. METHODS: Data from adults aged ≥ 60 years in the NHANES 2011-2014 were analyzed. Multiple linear regression assessed associations between EASIX and cognitive function scores. LASSO regression selected variables, and six machine learning models (e.g., Random Forest and XGBoost) were developed. SHAP values interpreted feature importance. RESULTS: Among 2,763 participants, EASIX showed a significant negative correlation with all cognitive scores (P < 0.05). The ElasticNet model outperformed other models. SHAP analysis identified EASIX as one of the top four influential variables, with cognitive function levels demonstrating a declining trend as EASIX score increased, particularly among older adults. CONCLUSIONS: EASIX is significantly negatively associated with cognitive function, especially in advanced age. Although the cross-sectional design precludes causal inference, it shows promise as a blood-based biomarker for early screening and risk assessment of cognitive decline, supporting its potential clinical utility.

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