Predicting Unplanned Intensive Care Unit Admission for Trauma Patients: The CRASH Score.
Risk calculator
TQIP
Trauma triage
Unplanned ICU admission
Journal
The Journal of surgical research
ISSN: 1095-8673
Titre abrégé: J Surg Res
Pays: United States
ID NLM: 0376340
Informations de publication
Date de publication:
11 2022
11 2022
Historique:
received:
27
02
2022
revised:
10
05
2022
accepted:
11
06
2022
pubmed:
18
7
2022
medline:
24
9
2022
entrez:
17
7
2022
Statut:
ppublish
Résumé
Unplanned transfer of trauma patients to the intensive care unit (ICU) carries an associated increase in mortality, hospital length of stay, and cost. Trauma teams need to determine which patients necessitate ICU admission on presentation rather than waiting to intervene on deteriorating patients. This study sought to develop a novel Clinical Risk of Acute ICU Status during Hospitalization (CRASH) score to predict the risk of unplanned ICU admission. The 2017 Trauma Quality Improvement Program database was queried for patients admitted to nonICU locations. The group was randomly divided into two equal sets (derivation and validation). Multiple logistic regression models were created to determine the risk of unplanned ICU admission using patient demographics, comorbidities, and injuries. The weighted average and relative impact of each independent predictor were used to derive a CRASH score. The score was validated using area under the curve. A total of 624,786 trauma patients were admitted to nonICU locations. From 312,393 patients in the derivation-set, 3769 (1.2%) had an unplanned ICU admission. A total of 24 independent predictors of unplanned ICU admission were identified and the CRASH score was derived with scores ranging from 0 to 32. The unplanned ICU admission rate increased steadily from 0.1% to 3.9% then 12.9% at scores of 0, 6, and 14, respectively. The area under the curve for was 0.78. The CRASH score is a novel and validated tool to predict unplanned ICU admission for trauma patients. This tool may help providers admit patients to the appropriate level of care or identify patients at-risk for decompensation.
Identifiants
pubmed: 35842975
pii: S0022-4804(22)00403-6
doi: 10.1016/j.jss.2022.06.039
pii:
doi:
Types de publication
Journal Article
Randomized Controlled Trial
Langues
eng
Sous-ensembles de citation
IM
Pagination
505-510Informations de copyright
Copyright © 2022 The Author(s). Published by Elsevier Inc. All rights reserved.