Evidence map›Paper›PMID 29799609›Full record

ArticleAmerican journal of disaster medicine2018

Validation of a novel irritant gas syndrome triage algorithm.

Joan M Culley, Sara Donevant, Jean Craig, Jane Richter, Abbas S Tavakoli, Erik Svendsen, Salvatore DiNardi

Abstract read
In one paragraph

Article in American journal of disaster medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Observational
  2. Designing and executing a functional exercise to test a novel informatics tool for mass casualty triage.Journal of the American Medical Informatics Association : JAMIA · 2019
    Article
  3. Article
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

7 authors.

Joan M CulleyAssociate Professor, College of Nursing, University of South Carolina, Columbia, South Carolina.
Sara DonevantCollege of Nursing, University of South Carolina, Columbia, South Carolina.
Jean CraigDatabase Architect, Honest Broker, Office of Biomedical Informatics Center, Medical University of South Carolina, Charleston, South Carolina.
Jane RichterCollege of Nursing, University of South Carolina, Columbia, South Carolina.
Abbas S TavakoliCollege of Nursing, University of South Carolina, Columbia, South Carolina.
Erik SvendsenDepartment of Public Health Sciences, Medical University of South Carolina, Charleston, South Carolina.
Salvatore DiNardiCollege of Nursing, University of South Carolina, Columbia, South Carolina.

Funding

Validating Triage for Chemical Mass Casualty Incidents - A First StepR01LM011648 · NLM · UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA · PI CULLEY, JOAN MARIE · 2014 to 2017
$2.2M
NLM NIH HHS R01 LM011648
6 · The paper itself

Abstract

objectiveOur objective was to validate a novel irritant gas syndrome agent (IGSA) triage algorithm for use in an emergency department (ED). We assessed efficiency, accuracy, and precision of our IGSA triage algorithm based on signs/symptoms of actual patients.

designAfter characterizing the signs/symptoms of an actual IGSA exposure event, we developed and validated the IGSA triage algorithm using a simulated computer exercise to compare the IGSA triage algorithm to the preferred hospital triage algorithm, the Emergency Severity Index (ESI).

settingThis study was a simulated computer exercise using surveys developed in Research Electronic Data Capture software. Nurse volunteers simulated triaging 298 patients.

participantsPatient data included 146 patients treated during the disaster as well as 152 unexposed patients. Twenty-six nurse volunteers were assigned to triage the patients using one of the algorithms in the simulated computer exercise. MAIN OUTCOME MEASURE(S): The precision of the IGSA triage algorithm was 0.82 (confidence interval [CI] 0.78-0.85) and ESI 0.73 (CI 0.69-0.77). Weighted κ for ESI and IGSA accuracy for exposed patients was 0.32 (95% CI 0.26-0.37) and 0.81 (95% CI 0.77-0.85), respectively.

resultsThe IGSA triage algorithm was more accurate and precise than the ESI algorithm for triaging patients exposed to an irritant gas.

conclusionsThis study validates the IGSA triage algorithm as the basis for the development of a prototype software application to quickly identify victims of a chemical disaster and triage patients efficiently and accurately with the potential to dramatically improve the processing of patients in EDs.

Indexed as

AlgorithmsCase-Control StudiesDisaster PlanningEmergency Medical ServicesEmergency Service, HospitalHumansIrritantsTriageIrritants

Identifiers

PMID29799609
PMCPMC6783806

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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.