Evidence map›Paper›PMID 32075827›Full record

ArticleBMJ open2020

Comparison of emergency department trauma triage performance of clinicians and clinical prediction models: a cohort study in India.

Ludvig Wärnberg Gerdin, Monty Khajanchi, Vineet Kumar, Nobhojit Roy, Makhan Lal Saha, Kapil Dev Soni, Anurag Mishra, Jyoti Kamble, Nitin Borle, Chandrika Prasad Verma and 1 more

Registry-linked trialOpen access · goldAbstract readComparative Study
In one paragraph

Article in BMJ open, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT02838459 (Can Prediction Models Triage Trauma Patients More Accurately Than Clinicians?), which is not on this map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
2.2field-weighted citation impact, top 12% 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.

NCT02838459 completednot on this map

Can Prediction Models Triage Trauma Patients More Accurately Than Clinicians?

TypeobservationalSponsorKarolinska InstitutetRan2016 to 2018Enrolled5,155ConditionsTrauma
3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 16 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

11 authors at 9 institutions in 2 countries.

Ludvig Wärnberg GerdinDepartment of Industrial Economics and Management, KTH Royal Institute of Technology, Stockholm, Sweden.
Monty KhajanchiDepartment of Surgery, Seth Gowardhandas Sunderdas Medical College and King Edward Memorial Hospital, Mumbai, India.
Vineet KumarDepartment of Surgery, Lokmanya Tilak Municipal General Hospital, Mumbai, India.
Nobhojit RoySurgical Unit, WHO Collaborating Centre for Research on Surgical Care Delivery in LMICs, BARC Hospital (Government of India), Mumbai, India.
Makhan Lal SahaDepartment of Surgery, Institute of Post-Graduate Medical Education and Research and Seth Sukhlal Karnani Memorial Hospital, Kolkata, India.
Kapil Dev SoniCritical and Intensive Care, JPN Apex Trauma Centre, All India Institute of Medical Sciences, New Delhi, India.
Anurag MishraDepartment of General Surgery, Maulana Azad Medical College, New Delhi, India.
Jyoti KambleDoctors for You, Mumbai, India.
Nitin BorleDepartment of General Surgery, KB Bhabha Municipal General Hospital Mumbai, Mumbai, India.
Chandrika Prasad VermaDoctors for You, Mumbai, India.
Martin Gerdin WärnbergDepartment of Global Public Health, Karolinska Institutet, Stockholm, Sweden martin.gerdin@ki.se.ORCID 0000-0001-6069-4794
All India Institute of Medical Sciences · INBhabha Hospital · INGovernment of India · INInstitute of Post Graduate Medical Education and Research · INKarolinska Institutet · SEKing Edward Memorial Hospital and Seth G.S. Medical College · INKTH Royal Institute of Technology · SELokmanya Tilak Municipal General Hospital and Lokmanya Tilak Municipal Medical College · INMaulana Azad Medical College · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThe aim of this study was to evaluate and compare the abilities of clinicians and clinical prediction models to accurately triage emergency department (ED) trauma patients. We compared the decisions made by clinicians with the Revised Trauma Score (RTS), the Glasgow Coma Scale, Age and Systolic Blood Pressure (GAP) score, the Kampala Trauma Score (KTS) and the Gerdin

designProspective cohort study.

settingThree hospitals in urban India.

participantsIn total, 7697 adult patients who presented to participating hospitals with a history of trauma were approached for enrolment. The final study sample included 5155 patients. The majority (4023, 78.0%) were male.

main outcome measureThe patient outcome was mortality within 30 days of arrival at the participating hospital. A grid search was used to identify model cut-off values. Clinicians and categorised models were evaluated and compared using the area under the receiver operating characteristics curve (AUROCC) and net reclassification improvement in non-survivors (NRI+) and survivors (NRI-) separately.

resultsThe differences in AUROCC between each categorised model and the clinicians were 0.016 (95% CI -0.014 to 0.045) for RTS, 0.019 (95% CI -0.007 to 0.058) for GAP, 0.054 (95% CI 0.033 to 0.077) for KTS and -0.007 (95% CI -0.035 to 0.03) for Gerdin

conclusionThe findings of this study suggest that there are no substantial differences in discrimination and net reclassification improvement between clinicians and all four clinical prediction models when using 30-day mortality as the outcome of ED trauma triage in adult patients. TRIAL REGISTRATION NUMBER: ClinicalTrials.gov Registry (NCT02838459).

Indexed as

Emergency Service, HospitalHospital MortalityModels, BiologicalPhysiciansAdultArea Under CurveBlood PressureClinical Decision-MakingFemaleGlasgow Coma ScaleHospitalsHumansIndiaMaleMiddle AgedProspective Studiesaccident & emergency medicineepidemiologytrauma management

Identifiers

PMID32075827
PMCPMC7044989
OpenAlexW3008868916

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

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.