Evidence map›Paper›PMID 35140074›Full record

Observational studyEmergency medicine journal : EMJ2022

Prognostic accuracy of triage tools for adults with suspected COVID-19 in a prehospital setting: an observational cohort study.

Carl Marincowitz, Laura Sutton, Tony Stone, Richard Pilbery, Richard Campbell, Benjamin Thomas, Janette Turner, Peter A Bath, Fiona Bell, Katie Biggs and 5 more

Open access · hybridAbstract readObservational Study
In one paragraph

Observational study in Emergency medicine journal : EMJ, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
4.6field-weighted citation impact, top 5% 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

10 citing papers in PubMed, 18 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

15 authors at 2 institutions in 1 country.

Carl MarincowitzCentre for Urgent and Emergency Care Research (CURE), Health Services Research School of Health and Related Research (ScHARR), The University of Sheffield, Sheffield, UK.ORCID http://orcid.org/0000-0003-3043-7564
Laura SuttonClinical Trials Research Unit (CTRU), Health Services Research School of Health and Related Research (ScHARR), The University of Sheffield, Sheffield, UK.
Tony StoneCentre for Urgent and Emergency Care Research (CURE), Health Services Research School of Health and Related Research (ScHARR), The University of Sheffield, Sheffield, UK.
Richard PilberyYorkshire Ambulance Service NHS Trust, Wakefield, UK.ORCID http://orcid.org/0000-0002-5797-9788
Richard CampbellCentre for Urgent and Emergency Care Research (CURE), Health Services Research School of Health and Related Research (ScHARR), The University of Sheffield, Sheffield, UK.
Benjamin ThomasClinical Trials Research Unit (CTRU), Health Services Research School of Health and Related Research (ScHARR), The University of Sheffield, Sheffield, UK b.d.thomas@sheffield.ac.uk.ORCID http://orcid.org/0000-0002-6659-6930
Janette TurnerCentre for Urgent and Emergency Care Research (CURE), Health Services Research School of Health and Related Research (ScHARR), The University of Sheffield, Sheffield, UK.ORCID http://orcid.org/0000-0003-3884-7875
Peter A BathCentre for Urgent and Emergency Care Research (CURE), Health Services Research School of Health and Related Research (ScHARR), The University of Sheffield, Sheffield, UK.
Fiona BellYorkshire Ambulance Service NHS Trust, Wakefield, UK.
Katie BiggsClinical Trials Research Unit (CTRU), Health Services Research School of Health and Related Research (ScHARR), The University of Sheffield, Sheffield, UK.
Madina HasanCentre for Urgent and Emergency Care Research (CURE), Health Services Research School of Health and Related Research (ScHARR), The University of Sheffield, Sheffield, UK.
Frank HopfgartnerCentre for Health Information Management Research (CHIMR) and Health Informatics Research Group, Information School, University of Sheffield, Sheffield, UK.
Suvodeep MazumdarCentre for Health Information Management Research (CHIMR) and Health Informatics Research Group, Information School, University of Sheffield, Sheffield, UK.
Jennifer PetrieClinical Trials Research Unit (CTRU), Health Services Research School of Health and Related Research (ScHARR), The University of Sheffield, Sheffield, UK.
Steve GoodacreCentre for Urgent and Emergency Care Research (CURE), Health Services Research School of Health and Related Research (ScHARR), The University of Sheffield, Sheffield, UK.ORCID http://orcid.org/0000-0003-0803-8444
University of Sheffield · GBYorkshire Ambulance Service NHS Trust · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTools proposed to triage patient acuity in COVID-19 infection have only been validated in hospital populations. We estimated the accuracy of five risk-stratification tools recommended to predict severe illness and compared accuracy to existing clinical decision making in a prehospital setting.

methodsAn observational cohort study using linked ambulance service data for patients attended by Emergency Medical Service (EMS) crews in the Yorkshire and Humber region of England between 26 March 2020 and 25 June 2020 was conducted to assess performance of the Pandemic Respiratory Infection Emergency System Triage (PRIEST) tool, National Early Warning Score (NEWS2), WHO algorithm, CRB-65 and Pandemic Medical Early Warning Score (PMEWS) in patients with suspected COVID-19 infection. The primary outcome was death or need for organ support.

resultsOf the 7549 patients in our cohort, 17.6% (95% CI 16.8% to 18.5%) experienced the primary outcome. The NEWS2 (National Early Warning Score, version 2), PMEWS, PRIEST tool and WHO algorithm identified patients at risk of adverse outcomes with a high sensitivity (>0.95) and specificity ranging from 0.3 (NEWS2) to 0.41 (PRIEST tool). The high sensitivity of NEWS2 and PMEWS was achieved by using lower thresholds than previously recommended. On index assessment, 65% of patients were transported to hospital and EMS decision to transfer patients achieved a sensitivity of 0.84 (95% CI 0.83 to 0.85) and specificity of 0.39 (95% CI 0.39 to 0.40).

conclusionUse of NEWS2, PMEWS, PRIEST tool and WHO algorithm could improve sensitivity of EMS triage of patients with suspected COVID-19 infection. Use of the PRIEST tool would improve sensitivity of triage without increasing the number of patients conveyed to hospital.

Indexed as

COVID-19Emergency Medical ServicesAdultCohort StudiesHumansPrognosisRetrospective StudiesTriageCOVID-19emergency ambulance systemsemergency care systemsrisk managementtriage

Identifiers

PMID35140074
PMCPMC8844966
OpenAlexW4221100948

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.