Using clinical risk models to predict outcomes: what are we predicting and why?
clinical assessment
research
statistics
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
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
728-730Informations 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.