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Current Anesthesiology Reports
Erschienen in: Current Anesthesiology Reports 3/2016

01.09.2016 | Research Methods and Statistical Analyses (Y Le Manach, Section Editor)

Risk Prediction Models in Perioperative Medicine: Methodological Considerations

verfasst von: Gary S. Collins, Jie Ma, Stephen Gerry, Eric Ohuma, Lang’O Odondi, Marialena Trivella, Jennifer De Beyer, Maria D. L. A. Vazquez-Montes

Erschienen in: Current Anesthesiology Reports | Ausgabe 3/2016

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Abstract

Purpose of Review

Risk prediction models hold enormous potential for assessing surgical risk in a standardized, objective manner. Despite the vast number of risk prediction models developed, they have not lived up to their potential. The aim of this paper is to provide an overview of the methodological issues that should be considered when developing and validating a risk prediction model to ensure a useful, accurate model.

Recent Findings

Systematic reviews examining the methodological and reporting quality of these models have found widespread deficiencies that limit their usefulness.

Summary

Risk prediction modelling is a growing field that is gaining huge interest in the era of personalized medicine. Although there are no shortcuts and many challenges are faced when developing and validating accurate, useful prediction models, these challenges are surmountable, if the abundant methodological and practical guidance available is used correctly and efficiently.
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Metadaten
Titel
Risk Prediction Models in Perioperative Medicine: Methodological Considerations
verfasst von
Gary S. Collins
Jie Ma
Stephen Gerry
Eric Ohuma
Lang’O Odondi
Marialena Trivella
Jennifer De Beyer
Maria D. L. A. Vazquez-Montes
Publikationsdatum
01.09.2016
Verlag
Springer US
Erschienen in
Current Anesthesiology Reports / Ausgabe 3/2016
Elektronische ISSN: 2167-6275
DOI
https://doi.org/10.1007/s40140-016-0171-8

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