Using clinical risk models to predict outcomes: what are we predicting and why?


Journal

Emergency medicine journal : EMJ
ISSN: 1472-0213
Titre abrégé: Emerg Med J
Pays: England
ID NLM: 100963089

Informations de publication

Date de publication:
Oct 2023
Historique:
received: 23 12 2022
accepted: 05 07 2023
medline: 29 9 2023
pubmed: 20 7 2023
entrez: 19 7 2023
Statut: ppublish

Résumé

Clinical risk prediction models can support decision making in emergency medicine, but directing intervention towards high-risk patients may involve a flawed assumption. This concepts paper examines prognostic clinical risk prediction and specifically describes the potential impact of treatment effects in model development studies. Treatment effects may lead to models failing to achieve the aim of identifying the patients most likely to benefit from intervention, and may instead identify patients who are unlikely to benefit from intervention. The paper provides practical advice to help clinicians who wish to use clinical prediction scores to assist clinical judgement rather than dictate clinical decision making.

Identifiants

pubmed: 37468227
pii: emermed-2022-213057
doi: 10.1136/emermed-2022-213057
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

728-730

Informations de copyright

© Author(s) (or their employer(s)) 2023. No commercial re-use. See rights and permissions. Published by BMJ.

Déclaration de conflit d'intérêts

Competing interests: SG was the Chief Investigator for the PRIEST Study.

Auteurs

Steve Goodacre (S)

School of Health and Related Research, The University of Sheffield, Sheffield, S10 2TN, UK s.goodacre@sheffield.ac.uk.

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Classifications MeSH