How to Develop and Validate Prediction Models for Orthopedic Outcomes

Isabella Zaniletti, Dirk R. Larson, David G. Lewallen, Daniel J. Berry, Hilal Maradit Kremers

Research output: Contribution to journalReview articlepeer-review

Abstract

Prediction models are common in medicine for predicting outcomes such as mortality, complications, or response to treatment. Despite the growing interest in these models in arthroplasty (and orthopaedics in general), few have been adopted in clinical practice. If robustly built and validated, prediction models can be excellent tools to support surgical decision making. In this paper, we provide an overview of the statistical concepts surrounding prediction models and outline practical steps for prediction model development and validation in arthroplasty research. Please visit the following https://www.youtube.com/watch?v=9Yrit23Rkic for a video that explains the highlights of the paper in practical terms.

Original languageEnglish (US)
Pages (from-to)627-633
Number of pages7
JournalJournal of Arthroplasty
Volume38
Issue number4
DOIs
StatePublished - Apr 2023

Keywords

  • arthroplasty
  • machine learning
  • model validation
  • orthopedics
  • predictors
  • risk prediction

ASJC Scopus subject areas

  • Orthopedics and Sports Medicine

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