Development of an Outcome Score for Patients With Knee Osteoarthritis and Knee Joint Endoprosthesis Using an App

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 dataset to predict patient satisfaction after TKA/THA.

Endpoints Primary endpoint: Overall patient satisfaction Secondary endpoints: Age, height, weight, step count, step length, gait asymmetry, gait speed, double support phase, knee joint ROM, walk test, KOOS, SF-36, EQ5d, satisfaction with the app, and satisfaction with app use.

Study Population App-Group: Inclusion criteria are patients ≥18 years before or after TKA/THA. Exclusion criteria include missing consent, ineligible diagnosis, lack of smartphone, age <18 years, or insufficient German language skills (as no English version of the app is currently available). Planned enrollment: 450 patients.

Non-App-Group: Inclusion criteria are patients ≥18 years before or after TKA/THA. Exclusion criteria include missing consent, ineligible diagnosis, age <18 years, or insufficient German language skills (as no English version of the app is currently available). Planned enrollment: 450 patients.

Healthy-group: Inclusion criteria are healthy proband ≥18 years with no lower limb conditions. The overall procedure is identical to that of the AppGroup. Exclusion criteria include missing consent, ineligible diagnosis, no smartphone, age <18 years, or insufficient German language skills (as no English version of the app is currently available). Planned enrollment: 450 patients.

Methods Design: Single-center, prospective pilot study. The app collects patient-authorized movement data already stored on smartphones as well as future data. Participants choose which data to share. In addition, they are prompted to complete gait tests and knee function tests. PROMs (KOOS, SF-36, satisfaction) are administered at regular intervals.