Development and Pre-validation of a Machine Learning-based Prediction Algorithm for Early Functional Recovery in Patients Undergoing Hip and Knee Replacement Surgery

The goal of this observational study is to develop and pre-validate a machine learning algorithm to predict early recovery of mobility in patients undergoing hip or knee joint replacement surgery. The primary research question is: Can a machine learning model accurately classify patients with faster versus slower recovery of autonomous mobility in the first days after joint replacement surgery? Patients who have undergone elective hip or knee arthroplasty and received post-operative physiotherapy will have their clinical and perioperative data collected retrospectively (2020-2023) and prospectively (March 2026-December 2027). The algorithm will be trained on retrospective data and tested prospectively to evaluate its predictive performance for early mobilization and length of hospital stay.

NCT Number	NCT07333560
Lead Sponsor	Istituto Ortopedico Rizzoli Collaborators: Azienda U.S.L. - IRCCS di Reggio Emilia
Conditions	Artificial Intelligence (AI), Machine Learning, Joint Replacement, Predictive Model
Enrollment	943 participants
Start Date	2026-03-09
Primary Completion	2027-12 (estimated)
Study Completion	2027-12 (estimated)
Updated on ClinicalTrials.gov	2026-06-01