Clinical Trial Details
— Status: Completed
Administrative data
NCT number |
NCT06157190 |
Other study ID # |
PXLuc |
Secondary ID |
|
Status |
Completed |
Phase |
|
First received |
|
Last updated |
|
Start date |
September 1, 2020 |
Est. completion date |
October 30, 2023 |
Study information
Verified date |
November 2023 |
Source |
PXL University College |
Contact |
n/a |
Is FDA regulated |
No |
Health authority |
|
Study type |
Observational
|
Clinical Trial Summary
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.
Description:
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.