Incorporating Wearable Technology for Enhanced Rehabilitation Monitoring After Hip and Knee Replacement

Overview

This study focuses on the impact of osteoarthritis (OA), a leading cause of disability among older adults, with the hip and knee joints being particularly affected. The rise in OA prevalence is attributed to factors such as aging and increasing obesity rates. Post-surgery rehabilitation, especially after total hip or knee replacement, traditionally relies on supervised clinical assessments, which have limitations in capturing real-world experiences. The study aims to explore the integration of technology-assisted rehabilitation, utilizing wearable sensors and mobile health technologies, for unsupervised, real-world assessments. The use of digital biomarkers collected from these technologies offers continuous, objective measurements of patients' biological and physiological data. The research employs a dataset from moveUP digital therapies, including patients who underwent total knee arthroplasty, utilizing a digital application for at least six weeks post-surgery. Key objectives include evaluating the potential of automated unsupervised assessments in providing a holistic understanding of patient progression during rehabilitation. The study utilizes mixed models for statistical analysis, examining outcomes such as steps per day, 6-minute walk test, and peak 1 minute. Results indicate differences in recovery trajectories between hip and knee patients, with variations based on gender and type of prosthesis.

Data Source: This retrospective observational study utilized anonymized and depersonalized data from the moveUP digital therapies database (moveUP solution, Brussels, Belgium). The database encompasses information from patients who underwent hip and knee arthroplasty across Belgium, France, and the Netherlands. A cohort of 1144 patients who underwent elective total knee arthroplasty was selected based on their use of the digital application for a minimum of 6 weeks post-surgery, with completion of preoperative patient-reported outcome measures. Written informed consent for the scientific use of anonymized data was obtained from each patient. Regulatory guidelines were adhered to, and no institutional review board (IRB) approval was required, given the use of anonymized patient-level data. Recording Device and Outcomes: All data collection occurred through the moveUP® application, a registered medical device operating on a smart virtual platform designed for digital monitoring. This platform comprises a patient-facing mobile application and a web-based dashboard utilized by care providers. Objective data, including the number of steps per day and steps per minute, were collected using a commercial activity tracker (Garmin Vivofit 4) worn 24/7 by patients throughout the rehabilitation period. Patient-reported outcomes, such as the Oxford Knee Score, Forgotten Joint Score (FJS), Hip Osteoarthritis Outcome score (KOOS), Knee Osteoarthritis Outcome score (KOOS), UCLA Activity Scale (UCLA), and the EuroQol 5-Dimension (EQ5D), were measured before surgery and at various intervals up to two years post-surgery through the app. Statistical Analysis: We analyzed outcomes using mixed models for both knee and hip patients, treating values from each day as repeated measures. The model incorporated fixed effects related to recovery, days after surgery, age, gender, and the interaction between recovery and days. Our analysis employed fixed effects for recovery, days after surgery, and their interaction, with baseline measures normalized for comparability. Time needed to differentiate between recovery statuses was computed along with associated 95% confidence intervals. Statistical analyses were conducted at a significance level of 0.05 using RStudio (version 2023.09.0) with R version 4.4.2 and the LME4 package for mixed effect models.