Evidence map›Paper›PMID 37101141›Full record

ArticleBMC emergency medicine2023

The utility of the Rapid Emergency Medicine Score (REMS) compared with three other early warning scores in predicting in-hospital mortality among COVID-19 patients in the emergency department: a multicenter validation study.

Onlak Ruangsomboon, Nutthida Phanprasert, Supawich Jirathanavichai, Chanokporn Puchongmart, Phetsinee Boonmee, Netiporn Thirawattanasoot, Thawonrat Dorongthom, Nattakarn Praphruetkit, Apichaya Monsomboon

Open access · goldAbstract readMulticenter Study
In one paragraph

Article in BMC emergency medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
2.8field-weighted citation impact, top 9% of its field
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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed, 13 citations in OpenAlex.

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4 · The record

Corrections and comments

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

9 authors at 4 institutions in 1 country.

Onlak RuangsomboonDepartment of Emergency Medicine, Faculty of Medicine, Siriraj Hospital, Faculty of Medicine, Siriraj Hospital, Mahidol University, Mahidol University, Bangkok, Thailand.
Nutthida PhanprasertDepartment of Emergency Medicine, Faculty of Medicine, Siriraj Hospital, Faculty of Medicine, Siriraj Hospital, Mahidol University, Mahidol University, Bangkok, Thailand.
Supawich JirathanavichaiDepartment of Emergency Medicine, Faculty of Medicine, Siriraj Hospital, Faculty of Medicine, Siriraj Hospital, Mahidol University, Mahidol University, Bangkok, Thailand.
Chanokporn PuchongmartDepartment of Emergency Medicine, Banphaeo General Hospital, Samutsakhon, Thailand.
Phetsinee BoonmeeDepartment of Emergency Medicine, Ratchaburi Hospital, Ratchaburi, Thailand.
Netiporn ThirawattanasootDepartment of Emergency and Forensic Medicine, Buddhachinaraj Hospital, Phitsanulok, Thailand.
Thawonrat DorongthomDepartment of Emergency Medicine and Forensic Medicine, Prachuap Khiri Khan hospital, Prachuap Khiri Khan, Thailand.
Nattakarn PraphruetkitDepartment of Emergency Medicine, Faculty of Medicine, Siriraj Hospital, Faculty of Medicine, Siriraj Hospital, Mahidol University, Mahidol University, Bangkok, Thailand.
Apichaya MonsomboonDepartment of Emergency Medicine, Faculty of Medicine, Siriraj Hospital, Faculty of Medicine, Siriraj Hospital, Mahidol University, Mahidol University, Bangkok, Thailand. apichaya.m107@gmail.com.
Siriraj Hospital · THBuddhachinaraj Hospital · THPhramongkutklao Hospital · THRatchaburi Hospital · TH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMany early warning scores (EWSs) have been validated to prognosticate adverse outcomes of COVID-19 in the Emergency Department (ED), including the quick Sequential Organ Failure Assessment (qSOFA), the Modified Early Warning Score (MEWS), and the National Early Warning Score (NEWS). However, the Rapid Emergency Medicine Score (REMS) has not been widely validated for this purpose. We aimed to assess and compare the prognostic utility of REMS with that of qSOFA, MEWS, and NEWS for predicting mortality in emergency COVID-19 patients.

methodsWe conducted a multi-center retrospective study at five EDs of various levels of care in Thailand. Adult patients visiting the ED who tested positive for COVID-19 prior to ED arrival or within the index hospital visit between January and December 2021 were included. Their EWSs at ED arrival were calculated and analysed. The primary outcome was all-cause in-hospital mortality. The secondary outcome was mechanical ventilation.

resultsA total of 978 patients were included in the study; 254 (26%) died at hospital discharge, and 155 (15.8%) were intubated. REMS yielded the highest discrimination capacity for in-hospital mortality (the area under the receiver operator characteristics curves (AUROC) 0.771 (95% confidence interval (CI) 0.738, 0.804)), which was significantly higher than qSOFA (AUROC 0.620 (95%CI 0.589, 0.651); p < 0.001), MEWS (AUROC 0.657 (95%CI 0.619, 0.694); p < 0.001), and NEWS (AUROC 0.732 (95%CI 0.697, 0.767); p = 0.037). REMS was also the best EWS in terms of calibration, overall model performance, and balanced diagnostic accuracy indices at its optimal cutoff. REMS also performed better than other EWSs for mechanical ventilation.

conclusionREMS was the early warning score with the highest prognostic utility as it outperformed qSOFA, MEWS, and NEWS in predicting in-hospital mortality in COVID-19 patients in the ED.

Indexed as

COVID-19Early Warning ScoreEmergency MedicineSepsisAdultEmergency Service, HospitalHospital MortalityHumansPrognosisRetrospective StudiesROC Curvecovid-19Early warning scoreRapid emergency medicine score

Identifiers

PMID37101141
PMCPMC10132401
OpenAlexW4367049172

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.