Development of a Machine-Learning Model for Anterior Knee Pain After Total Knee Arthroplasty With Patellar Preservation Using Radiological Variables.

Background: Anterior knee pain (AKP) following total knee arthroplasty (TKA) with patellar preservation is a common complication that significantly affects patients' quality of life. This study aimed to develop a machine-learning model to predict the likelihood of developing AKP after TKA using radiological variables.

Methods: A cohort of 131 anterior stabilized TKA cases (105 patients) without patellar resurfacing was included.