Needle-Free Bedside and Anthropometric Measures Show Weak Discrimination of an Adverse Blood-Biomarker Profile in Middle-Aged and Older Mexican Adults: An Internally Validated Machine-Learning Study

Background/Objectives: Needle-free measures such as grip strength, gait speed, and anthropometry are attractive as potential substitutes for blood-based biomarkers in low-resource settings, yet whether they can predict an adverse blood-biomarker profile remains unknown. This study aimed to determine whether machine-learning algorithms can predict such a profile from a defined set of needle-free bedside and anthropometric measures in Mexican adults.