Evidence map›Paper›PMID 39088404›Full record

ArticlePLOS digital health2024

Comparison between the Smart Triage model and the Emergency Triage Assessment and Treatment guidelines in triaging children presenting to the emergency departments of two public hospitals in Kenya.

Stephen Kamau, Joyce Kigo, Paul Mwaniki, Dustin Dunsmuir, Yashodani Pillay, Cherri Zhang, Brian Nyamwaya, David Kimutai, Mary Ouma, Ismael Mohammed and 5 more

Abstract read
In one paragraph

Article in PLOS digital health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

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

4 citing papers in PubMed.

  1. Emergency triage in coastal Kenya: a survey of public Emergency Departments.African journal of emergency medicine : Revue africaine de la medecine d'urgence · 2026
    Article
  2. Article
  3. Article
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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.

Stephen KamauHealth Service Unit, KEMRI-Wellcome Trust Research Programme, Nairobi, Kenya.
Joyce KigoHealth Service Unit, KEMRI-Wellcome Trust Research Programme, Nairobi, Kenya.
Paul MwanikiHealth Service Unit, KEMRI-Wellcome Trust Research Programme, Nairobi, Kenya.
Dustin DunsmuirAnesthesiology, Pharmacology and Therapeutics, University of British Columbia, Vancouver, Canada.
Yashodani PillayAnesthesiology, Pharmacology and Therapeutics, University of British Columbia, Vancouver, Canada.ORCID https://orcid.org/0000-0002-5814-7975
Cherri ZhangInstitute for Global Health, British Columbia's Children's and Women's Hospital, Vancouver, Canada.ORCID https://orcid.org/0000-0001-7059-4922
Brian NyamwayaHealth Service Unit, KEMRI-Wellcome Trust Research Programme, Nairobi, Kenya.
David KimutaiDepartment of Paediatrics, Mbagathi County Hospital, Nairobi, Kenya.
Mary OumaDepartment of Paediatrics, Mbagathi County Hospital, Nairobi, Kenya.
Ismael MohammedDepartment of Paediatrics, Mbagathi County Hospital, Nairobi, Kenya.
Keziah GachuhiDepartment of Paediatrics, Mbagathi County Hospital, Nairobi, Kenya.
Mary ChegeDepartment of Paediatrics, Kiambu County Referral Hospital, Kiambu, Kenya.
Lydia ThuraniraDepartment of Paediatrics, Kiambu County Referral Hospital, Kiambu, Kenya.
J Mark AnserminoAnesthesiology, Pharmacology and Therapeutics, University of British Columbia, Vancouver, Canada.
Samuel AkechHealth Service Unit, KEMRI-Wellcome Trust Research Programme, Nairobi, Kenya.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Several triage systems have been developed, but little is known about their performance in low-resource settings. Evaluating and comparing novel triage systems to existing triage scales provides essential information about their added value, reliability, safety, and effectiveness before adoption. This study included children aged < 15 years who presented to the emergency departments of two public hospitals in Kenya between February and December 2021. We compared the performance of Emergency Triage Assessment and Treatment (ETAT) guidelines and Smart Triage (ST) models (ST model with independent triggers, and recalibrated ST model with independent triggers) in categorizing children into emergency, priority, and non-urgent triage categories. Sankey diagrams were used to visualize the distribution of children into similar or different triage categories by ETAT and ST models. Sensitivity, specificity, negative and positive predictive values for mortality and admission were calculated. 5618 children were enrolled, and the majority (3113, 55.4%) were aged between one and five years of age. Overall admission and mortality rates were 7% and 0.9%, respectively. ETAT classified 513 (9.2%) children into the emergency category compared to 1163 (20.8%) and 1161 (20.7%) by the ST model with independent triggers and recalibrated model with independent triggers, respectively. ETAT categorized 3089 (55.1%) children as non-urgent compared to 2097 (37.4%) and 2617 (46.7%) for the respective ST models. ETAT classified 191/395 (48.4%) admitted patients as emergencies compared to more than half by all the ST models. ETAT and ST models classified 25/49 (51%) and 39/49 (79.6%) deceased children as emergencies. Sensitivity for admission and mortality was 48.4% and 51% for ETAT and 74.9% and 79.6% for the ST models, respectively. Smart Triage shows potential for identifying critically ill children in low-resource settings, particularly when combined with independent triggers and performs comparably to ETAT. Evaluation of Smart Triage in other contexts and comparison to other triage systems is required.

Identifiers

PMID39088404
PMCPMC11293692

What OpenQuestion holds

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Registered trials

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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.