Age in addition to RETTS triage priority substantially improves 3-day mortality prediction in emergency department patients: a multi-center cohort study.

Age factors Emergency Medical Service Emergency medicine Hospital Mortality Observational study Predictive value of tests Primary complaint RETTS Risk factors Triage

Journal

Scandinavian journal of trauma, resuscitation and emergency medicine
ISSN: 1757-7241
Titre abrégé: Scand J Trauma Resusc Emerg Med
Pays: England
ID NLM: 101477511

Informations de publication

Date de publication:
18 Oct 2023
Historique:
received: 18 02 2023
accepted: 25 09 2023
medline: 23 10 2023
pubmed: 19 10 2023
entrez: 18 10 2023
Statut: epublish

Résumé

Previous studies have shown varying results on the validity of the rapid emergency triage and treatment system (RETTS), but have concluded that patient age is not adequately considered as a risk factor for short term mortality. Little is known about the RETTS system's performance between different chief complaints and on short term mortality. We therefore aimed to evaluate how well a model including both RETTS triage priority and patient age (TP and age model) predicts 3-day mortality compared to a univariate RETTS triage priority model (TP model). Secondarily, we aimed to evaluate the TP model compared to a univariate age model (age model) and whether these three models' predictive performance regarding 3-day mortality varies between patients with different chief complaints in an unsorted emergency department patient population. This study was a prospective historic observational cohort study, using logistic regression on a cohort of patients seeking emergency department care in Stockholm during 2012-2016. Patient visits were stratified into the 10 chief complaint categories (CCC) with the highest number of deceased patients within 3 days of arrival, and to "other chief complaints". Patients with priority 1 were excluded. The studied cohort contained 1,690,981 visits by 788,046 different individuals. The TP and age model predicted 3-day mortality significantly and substantially better than both univariate models in the total population and in each studied CCC. The age model predicted 3-day mortality significantly and substantially better than the TP model in the total population and for all but three CCCs and was not inferior in any CCC. There were substantial differences between the studied CCCs in the predictive ability of each of the three models. Adding patient age to the RETTS triage priority system significantly and substantially improves 3-day mortality prediction compared to RETTS priority alone. Age alone is a non-inferior predictor of 3-day mortality compared to RETTS priority. The impact on 3-day mortality prediction of adding patient age to RETTS priority varies between CCCs but is substantial for all CCCs and for the total population. Including age as a variable in future revisions of RETTS could substantially improve patient safety.

Sections du résumé

BACKGROUND BACKGROUND
Previous studies have shown varying results on the validity of the rapid emergency triage and treatment system (RETTS), but have concluded that patient age is not adequately considered as a risk factor for short term mortality. Little is known about the RETTS system's performance between different chief complaints and on short term mortality. We therefore aimed to evaluate how well a model including both RETTS triage priority and patient age (TP and age model) predicts 3-day mortality compared to a univariate RETTS triage priority model (TP model). Secondarily, we aimed to evaluate the TP model compared to a univariate age model (age model) and whether these three models' predictive performance regarding 3-day mortality varies between patients with different chief complaints in an unsorted emergency department patient population.
METHODS METHODS
This study was a prospective historic observational cohort study, using logistic regression on a cohort of patients seeking emergency department care in Stockholm during 2012-2016. Patient visits were stratified into the 10 chief complaint categories (CCC) with the highest number of deceased patients within 3 days of arrival, and to "other chief complaints". Patients with priority 1 were excluded.
RESULTS RESULTS
The studied cohort contained 1,690,981 visits by 788,046 different individuals. The TP and age model predicted 3-day mortality significantly and substantially better than both univariate models in the total population and in each studied CCC. The age model predicted 3-day mortality significantly and substantially better than the TP model in the total population and for all but three CCCs and was not inferior in any CCC. There were substantial differences between the studied CCCs in the predictive ability of each of the three models.
CONCLUSIONS CONCLUSIONS
Adding patient age to the RETTS triage priority system significantly and substantially improves 3-day mortality prediction compared to RETTS priority alone. Age alone is a non-inferior predictor of 3-day mortality compared to RETTS priority. The impact on 3-day mortality prediction of adding patient age to RETTS priority varies between CCCs but is substantial for all CCCs and for the total population. Including age as a variable in future revisions of RETTS could substantially improve patient safety.

Identifiants

pubmed: 37853463
doi: 10.1186/s13049-023-01123-8
pii: 10.1186/s13049-023-01123-8
pmc: PMC10585720
doi:

Types de publication

Observational Study Multicenter Study Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

55

Informations de copyright

© 2023. Norwegian Air Ambulance Foundation.

Références

Scand J Trauma Resusc Emerg Med. 2011 Jun 30;19:42
pubmed: 21718476
Ann Emerg Med. 2009 May;53(5):605-11
pubmed: 19027193
Scand J Trauma Resusc Emerg Med. 2020 Aug 17;28(1):81
pubmed: 32807224
Scand J Trauma Resusc Emerg Med. 2021 Jul 3;29(1):89
pubmed: 34217351
CJEM. 2017 Jul;19(S2):S18-S27
pubmed: 28756800
Am J Emerg Med. 2021 Aug;46:508-514
pubmed: 33191046
Medicine (Baltimore). 2017 Nov;96(44):e8457
pubmed: 29095294
Acad Emerg Med. 1995 Nov;2(11):990-5
pubmed: 8536127
Ann Emerg Med. 2007 Mar;49(3):275-81
pubmed: 17141139
Acad Emerg Med. 2011 Dec;18(12):1358-70
pubmed: 22168200
PLoS One. 2018 Aug 30;13(8):e0203316
pubmed: 30161242
Ann Emerg Med. 2012 Sep;60(3):317-25.e3
pubmed: 22401951
J Am Coll Emerg Physicians Open. 2020 Sep 12;1(6):1312-1319
pubmed: 33392538
Scand J Trauma Resusc Emerg Med. 2016 Mar 03;24:21
pubmed: 26940235
PLoS One. 2020 Feb 20;15(2):e0229210
pubmed: 32078640
Biometrics. 1988 Sep;44(3):837-45
pubmed: 3203132
Clin Epidemiol. 2021 Jul 19;13:533-554
pubmed: 34321928
BMC Geriatr. 2019 May 23;19(1):139
pubmed: 31122186
Health Informatics J. 2020 Mar;26(1):34-44
pubmed: 30488755
Scand J Trauma Resusc Emerg Med. 2011 Nov 03;19:68
pubmed: 22050641
Scand J Trauma Resusc Emerg Med. 2022 Apr 15;30(1):27
pubmed: 35428351
BMC Bioinformatics. 2011 Mar 17;12:77
pubmed: 21414208
Eur J Epidemiol. 2017 Sep;32(9):765-773
pubmed: 28983736
PLoS One. 2021 Mar 10;16(3):e0247881
pubmed: 33690653
Ann Emerg Med. 2019 Jul;74(1):140-152
pubmed: 30470513

Auteurs

G Malmer (G)

Karolinska Institutet Department of Clinical Sciences, Danderyd Hospital Division of Medicine, Stockholm, Sweden. gustav.malmer@gmail.com.

R Åhlberg (R)

Department of Emergency Medicine, Karolinska University Hospital, Solna, Stockholm, Sweden.

P Svensson (P)

Department of Clinical Science and Education, Södersjukhuset, Karolinska Institutet, Stockholm, Sweden.

B Af Ugglas (B)

Department of Medicine, Karolinska Institutet, Solna, Stockholm, Sweden.

E Westerlund (E)

Karolinska Institutet Department of Clinical Sciences, Danderyd Hospital Division of Medicine, Stockholm, Sweden.

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Classifications MeSH