Literature DB >> 27215928

External model validation of binary clinical risk prediction models in cardiovascular and thoracic surgery.

Graeme L Hickey1, Eugene H Blackstone2.   

Abstract

Clinical risk-prediction models serve an important role in healthcare. They are used for clinical decision-making and measuring the performance of healthcare providers. To establish confidence in a model, external model validation is imperative. When designing such an external model validation study, thought must be given to patient selection, risk factor and outcome definitions, missing data, and the transparent reporting of the analysis. In addition, there are a number of statistical methods available for external model validation. Execution of a rigorous external validation study rests in proper study design, application of suitable statistical methods, and transparent reporting.
Copyright © 2016 The American Association for Thoracic Surgery. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  calibration; discrimination; external validation; risk prediction model; statistics

Mesh:

Year:  2016        PMID: 27215928     DOI: 10.1016/j.jtcvs.2016.04.023

Source DB:  PubMed          Journal:  J Thorac Cardiovasc Surg        ISSN: 0022-5223            Impact factor:   5.209


  1 in total

1.  External validation of the improving partial risk adjustment in surgery (PRAIS-2) model for 30-day mortality after paediatric cardiac surgery.

Authors:  Lucia Cocomello; Massimo Caputo; Rosie Cornish; Deborah Lawlor
Journal:  BMJ Open       Date:  2020-11-27       Impact factor: 2.692

  1 in total

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