Machine Learning Analysis Reveals Novel Neuroimaging and Clinical Signatures of Frailty in HIV

Abstract

Data-driven algorithms built from highly dimensional clinical and brain imaging features implicate disruption to the visuomotor system in older PLWH designated as frail individuals. Interactions between lower CD4 count, female sex, depressive symptoms, and neuroimaging features suggest potentiation of risk mechanisms. Longitudinal data-driven studies are needed to guide clinical strategies capable of preventing the development of frailty as PLWH reach advanced age.