Condition: Knee Osteoarthritis · Knee Arthroplasty · Hip Osteoarthritis · Sponsor: Technical University of Munich
Total knee arthroplasty (TKA) and total hip arthroplasty (THA) is one of the most frequent orthopedic procedures. Over 50% of patients report higher expectations than their surgeons, and 10-50% remain dissatisfied postoperatively. Persistent pain, functional limitations, and unmet expectations are key drivers. Identifying risks pre- and early postoperatively is essential, alongside empowering patients through self-management. Existing scoring systems integrate PROMs, demographics, and sometimes imaging but within limited timeframes. They rarely capture functional deficits or long-term trajectories. Digital health solutions for TKA (pre-)rehabilitation exist, yet most focus on physiotherapy and education rather than predictive outcome modeling. To address this gap, the study team has developed a novel mobile application that enables the documentation and analysis of movement data up to 10 years before surgery and throughout long-term follow-up. These data are combined with PROMs and functional test results, providing a unique basis for outcome prediction and risk stratification in TKA/THA. Primary Objective The aim of this pilot study is to develop a composite outcome score for TKA/THA patients. This score will integrate demographic variables, PROMs, and objective functional measures (knee joint angles, gait parameters, walk tests) to identify risk factors for dissatisfaction and support predictive modeling. A machine learning algorithm will be trained using the collected d…
This description comes directly from the study's public registry record.
Christina Valle, Dr. med · +498941406508 · christina.valle@tum.de
Florian Hinterwimmer, Dr. rer. nat. · florian.hinterwimmer@tum.de
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| Department of Orthopaedics and Sports Orthopaedics TUM University Hospital Rechts der Isar | Munich, Bavaria, Germany | Recruiting |
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Source record: clinicaltrials.gov/study/NCT07212699