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How to Develop and Validate Prediction Models for Orthopedic Outcomes.
Zaniletti, Isabella; Larson, Dirk R; Lewallen, David G; Berry, Daniel J; Maradit Kremers, Hilal.
Afiliação
  • Zaniletti I; Department of Quantitative Health Sciences, Mayo Clinic, Scottsdale, Arizona.
  • Larson DR; Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota.
  • Lewallen DG; Department of Orthopedic Surgery, Mayo Clinic, Rochester, Minnesota.
  • Berry DJ; Department of Orthopedic Surgery, Mayo Clinic, Rochester, Minnesota.
  • Maradit Kremers H; Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota; Department of Orthopedic Surgery, Mayo Clinic, Rochester, Minnesota.
J Arthroplasty ; 38(4): 627-633, 2023 04.
Article em En | MEDLINE | ID: mdl-36572235
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 followinghttps//www.youtube.com/watch?v=9Yrit23Rkicfor a video that explains the highlights of the paper in practical terms.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Ortopedia / Procedimentos Ortopédicos Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: J Arthroplasty Assunto da revista: ORTOPEDIA Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Ortopedia / Procedimentos Ortopédicos Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: J Arthroplasty Assunto da revista: ORTOPEDIA Ano de publicação: 2023 Tipo de documento: Article