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.
Adults aged 18 years or older
Patients underwent elective hip or knee arthroplasty.
Patients for whom postoperative physiotherapy was initiated.
Patients who underwent surgery for oncologic disease, femoral fracture, or revision joint arthroplasty.
Patients for whom postoperative physiotherapy was not provided due to postoperative complications
clinical data are unavailable.
Istituto Ortopedico Rizzoli
Lead sponsor
Azienda U.S.L. - IRCCS di Reggio Emilia
Collaborator