Development and validation of a nomogram for predicting ADL outcomes in patients undergoing subacute stroke rehabilitation based on machine learning and standard bedside clinical data: a retrospective cohort study.

The simplified model constructed using routine bedside indicators (age, baseline Barthel Index score, and Braden score) effectively predicts the activities of daily living recovery of subacute stroke patients at 3 months post-rehabilitation.

This nomogram tool is intuitive and easy to use, providing clinical support for individualized rehabilitation plan development, patient prognosis communication, and resource allocation.