ArticleAmerican journal of disaster medicine2013
Gleaning data from disaster: a hospital-based data mining method to study all-hazard triage after a chemical disaster.
Article in American journal of disaster medicine, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
What it found
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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.
Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it, 16 citations in OpenAlex.
- Application of artificial intelligence in triage in emergencies and disasters: a systematic review.BMC public health · 2024Pooled it
- Lessons learned from reviewing a hospital's disaster response to the hydrofluoric acid leak in Gumi city in 2012.BMC emergency medicine · 2021Observational
- Exposure of neonatal mice to bromine impairs their alveolar development and lung function.American journal of physiology. Lung cellular and molecular physiology · 2018Article
- Validation of a novel irritant gas syndrome triage algorithm.American journal of disaster medicine · 2018Article
- Data Capture and Analysis of Signs and Symptoms in a Chemically Exposed Population.Journal of informatics nursing · 2018Article
- Clinical Data Reuse or Secondary Use: Current Status and Potential Future Progress.Yearbook of medical informatics · 2017Review
- Validating Signs and Symptoms From An Actual Mass Casualty Incident to Characterize An Irritant Gas Syndrome Agent (IGSA) Exposure: A First Step in The Development of a Novel IGSA Triage Algorithm.Journal of emergency nursing · 2017Article
- The Necessity of Data Mining in Clinical Emergency Medicine; A Narrative Review of the Current Literatrue.Bulletin of emergency and trauma · 2017Review
- Differences in Practices Between Rural and Urban First Responders: Examining how First Responders Handle Irritant Gas Syndrome Agent (IGSA) Disasters in Rural Versus Urban Settings.Carolina fire rescue EMS journal · 2016Article
- A validation study of 5 triage systems using data from the 2005 Graniteville, South Carolina, chlorine spill.Journal of emergency nursing · 2014Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
objectiveTo describe the methods of evaluating currently available triage models for their efficacy in appropriately triaging the surge of patients after an all-hazards disaster.
designA method was developed for evaluating currently available triage models using extracted data from medical records of the victims from the Graniteville chlorine disaster.
settingOn January 6, 2005, a freight train carrying three tanker cars of liquid chlorine was inadvertently switched onto an industrial spur in central Graniteville, SC. The train then crashed into a parked locomotive and derailed. This caused one of the chlorine tankers to rupture and immediately release ~60 tons of chlorine. Chlorine gas infiltrated the town with a population of 7,000.
participantsThis research focuses on the victims who received emergency care in South Carolina.
resultsWith our data mapping and decision tree logic, the authors were successful in using the available extracted clinical data to estimate triage categories for use in our study.
conclusionsThe methodology outlined in this article shows the potential use of well-designed secondary analysis methods to improve mass casualty research. The steps are reliable and repeatable and can easily be extended or applied to other disaster datasets.
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What OpenQuestion holds
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.