毛髪治療と移植
オープンアクセス

概要

Predictive Model and Web-based Calculator for the Oxford Hip Score After Total Hip Replacement

Talitha Koo Yen*, Adriano Stofel Bispo, Danilo Lopes Paiva, Lucas GG Tiago de Souza and Eloisio B Lopes Neto

Objective: Although previous studies have developed classical models predicting outcomes after hip replacement, no formal machine-learning based calculators have been designed to predict Oxford Hip Score based on a national sample. The aim of our study was to develop a series of machine-learning models and a web-based calculator to predict Oxford Hip Scores after total hip replacement.
Methods: We made use of the National Health Service Patient Reported Outcome Measures and Hospital Episode Statistics (NHS PROMS/HES) database, evaluating pre and post-operative data from patients aged over 50 years old undergoing total hip replacement from 2010 to 2015. Predictors of Oxford Hip Score were assessed using a combination of machine-learning and tree regression models.
Results: A total of 170,283 patients participated in the study. Most patients were female (60.7%), aged between 70 and 79 years, with a baseline Oxford Hip Score lower than 41. Across all machine learning models, the most significant predictors of Oxford Hip Scores were pre-operative EQ-5D index and self-perceived disability, problems while shopping, circulation diseases, and pre-operative problems while climbing stairs. The best performing models were Gradient Boosting Machines, Boosted Generalized Linear Model, and Multivariate Adaptive Regression Splines with R-Squared values of, respectively, 0.18, 0.18, and 0.18. A Web-based calculator was developed (https:// companionsite.sporedata.com/app/predicthip/).
Conclusion: Highly accurate models were developed to predict the Oxford Hip Scores, which can be used in both clinical decision-making and healthcare the management of healthcare resources.