Evidence map›Paper›PMID 38065678›Full record

ArticleAnnals of medicine2023

Head-to-head comparison of 19 prediction models for short-term outcome in medical patients in the emergency department: a retrospective study.

Paul M E L van Dam, Sien Lievens, Noortje Zelis, William P T M van Doorn, Steven J R Meex, Jochen W L Cals, Patricia M Stassen

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Article in Annals of medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Paul M E L van DamDepartment of Internal Medicine, Division of General Internal Medicine, Section Acute Medicine, Maastricht University Medical Center, Maastricht, the Netherlands.ORCID 0000-0002-5172-2500
Sien LievensDepartment of Internal Medicine, Division of General Internal Medicine, Section Acute Medicine, Maastricht University Medical Center, Maastricht, the Netherlands.
Noortje ZelisDepartment of Internal Medicine, Division of General Internal Medicine, Section Acute Medicine, Maastricht University Medical Center, Maastricht, the Netherlands.ORCID 0000-0003-0015-5240
William P T M van DoornCentral Diagnostic Laboratory, Department of Clinical Chemistry, Maastricht University Medical Center, Maastricht, the Netherlands.ORCID 0000-0003-2676-7448
Steven J R MeexCentral Diagnostic Laboratory, Department of Clinical Chemistry, Maastricht University Medical Center, Maastricht, the Netherlands.ORCID 0000-0001-8147-9006
Jochen W L CalsDepartment of Family Medicine, Care and Public Health Research Institute (CAPHRI), Maastricht University, the Netherlands.ORCID 0000-0001-9550-5674
Patricia M StassenDepartment of Internal Medicine, Division of General Internal Medicine, Section Acute Medicine, Maastricht University Medical Center, Maastricht, the Netherlands.ORCID 0000-0003-0864-1542

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionPrediction models for identifying emergency department (ED) patients at high risk of poor outcome are often not externally validated. We aimed to perform a head-to-head comparison of the discriminatory performance of several prediction models in a large cohort of ED patients.

methodsIn this retrospective study, we selected prediction models that aim to predict poor outcome and we included adult medical ED patients. Primary outcome was 31-day mortality, secondary outcomes were 1-day mortality, 7-day mortality, and a composite endpoint of 31-day mortality and admission to intensive care unit (ICU).The discriminatory performance of the prediction models was assessed using an area under the receiver operating characteristic curve (AUC). Finally, the prediction models with the highest performance to predict 31-day mortality were selected to further examine calibration and appropriate clinical cut-off points.

resultsWe included 19 prediction models and applied these to 2185 ED patients. Thirty-one-day mortality was 10.6% (231 patients), 1-day mortality was 1.4%, 7-day mortality was 4.4%, and 331 patients (15.1%) met the composite endpoint. The RISE UP and COPE score showed similar and very good discriminatory performance for 31-day mortality (AUC 0.86), 1-day mortality (AUC 0.87), 7-day mortality (AUC 0.86) and for the composite endpoint (AUC 0.81). Both scores were well calibrated. Almost no patients with RISE UP and COPE scores below 5% had an adverse outcome, while those with scores above 20% were at high risk of adverse outcome. Some of the other prediction models (i.e. APACHE II, NEWS, WPSS, MEWS, EWS and SOFA) showed significantly higher discriminatory performance for 1-day and 7-day mortality than for 31-day mortality.

conclusionsHead-to-head validation of 19 prediction models in medical ED patients showed that the RISE UP and COPE score outperformed other models regarding 31-day mortality.

Indexed as

Emergency Service, HospitalAdultAPACHEHospital MortalityHumansPrognosisRetrospective StudiesROC Curveemergency departmentmortalityPredictionprognosis

Identifiers

PMID38065678
PMCPMC10786429

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.