Developing af prediction model for early revision of total knee arthroplasty
Development of a multivariable prediction model for early revision of total knee arthroplasty – The effect of incorporating patient-reported outcome measures
Authors: J.D. Andersen, S. Hangaard, A.A.Ø. Buus, M. Laursen, O.K. Hejlesen, A. El-Galaly
Summary
In this study we aimed to identify the most important factors of early revision in 538 patients undergoing total knee arthroplasty (TKA) and use these factors to develop a prediction model for early revision TKA using multivariate logistic regression as a prediction model. In addition, we assessed the effect of incorporating patient-reported outcome measures (PROMs) in the model and compared it to one without. We found that adding PROMs to the model seems to improve the quality of the predictions.