Clinical Research Directory

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.

Inter- and Intra-Observer Reliability of the Iowa Level of Assistance Scale and the Effect of Staff Retraining

The aim of this study is to evaluate, in routine clinical practice, the inter- and intra-observer reliability of the Iowa Level of Assistance (ILoA) scale, which is regularly used to assess functional recovery in orthopedic patients. A secondary objective is to investigate the impact of a structured retraining program for healthcare staff on the use of the ILoA scale and to determine whether this intervention influences the reliability indices of the scale.

MCJR Joint Replacement Clinical Outcomes Database

The purpose of this research study is to develop a database of information regarding the diagnosis, treatment, and outcome of participants who have had a joint replacement. The more information gathered, the better the investigators will be able to treat future patients who need a joint replacement. For example the investigators learn what works well to help design implants and treatment protocols for the future. The investigators publish manuscripts and present research findings around the world to help other investigators and clinicians learn what is discovered. Furthermore, implant manufacturers may be able to use this information in the database to evaluate the success rates of specific joint replacement products.