Predicting knee adduction moment response to gait retraining with minimal clinical data.

ABSTRACT: Knee osteoarthritis is a progressive disease mediated by high joint loads. Foot progression angle modifications that reduce the knee adduction moment (KAM), a surrogate of knee loading, have demonstrated efficacy in alleviating pain and improving function. Although changes to the foot progression angle are overall beneficial, KAM reductions are not consistent across patients. Moreover, customized interventions are time-consuming and require instrumentation not commonly available in the clinic. We present a regression model that uses minimal clinical data-a set of six features easily obtained in the clinic-to predict the extent of first peak KAM reduction after toe-in gait retraining. For such a model to generalize, the training data must be large and variable. Given the lack of large publi

SUBMITTER: Rokhmanova N 

PROVIDER: S-EPMC9135336 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature