Comparing "people-like-me" and linear mixed model predictions of functional recovery following knee arthroplasty.

ABSTRACT:

Objective

Prediction models can be useful tools for monitoring patient status and personalizing treatment in health care. The goal of this study was to compare the relative strengths and weaknesses of 2 different approaches for predicting functional recovery after knee arthroplasty: a neighbors-based "people-like-me" (PLM) approach and a linear mixed model (LMM) approach.

Materials and methods

We used 2 distinct datasets to train and then test PLM and LMM prediction approaches for functional recovery following knee arthroplasty. We used the Timed Up and Go (TUG)-a common test of mobility-to operationalize physical function. Both approaches used patient characteristics and baseline postoperative TUG values to predict TUG recovery from days 1-425 following surgery. We then com

SUBMITTER: Graber J 

PROVIDER: S-EPMC10161535 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature