Prediction model for an early revision for dislocation after primary total hip arthroplasty.

ABSTRACT: Dislocation is one of the most common complications after primary total hip arthroplasty (THA). Several patient-related risk factors for dislocation have been reported in the previous literature, but only few prediction models for dislocation have been made. Our aim was to build a prediction model for an early (within the first 2 years) revision for dislocation after primary THA using two different statistical methods. The study data constituted of 37 pre- or perioperative variables and postoperative follow-up data of 16 454 primary THAs performed at our institution in 2008-2021. Model I was a traditional logistic regression model and Model II was based on the elastic net method that utilizes machine learning. The models' overall performance was measured using the pseudo R2 values. The dis

SUBMITTER: Pakarinen O 

PROVIDER: S-EPMC9462822 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature