ResearchValidating 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☆
Section snippets
Methods
Only de-identified data were used for this study. The Office of Research Compliance at the University determined that this study was exempt from the protection of human subject’s regulations. All information from the paper medical records of the 198 patients seen in the emergency department at the local hospital within 24 hours of the chlorine incident were abstracted (146 patients were exposed to chlorine, and 52 patients were not exposed to chlorine). Ten years later, in the same hospital and
Results
Table 1 shows actual patient signs and symptoms that mapped to WISER and CHEMM-IST.
Table 2, Table 3 show sensitivity, specificity, positive predictive value, negative predictive value, false-positive probability, false-negative probability, and 95% confidence interval for WISER and CHEMM-IST.
The results showed good sensitivity for both WISER and CHEMM-IST, from 0.84 to 0.94 and 0.92 to 0.97, respectively, and poor specificity for both WISER and CHEMM-IST, from 0.31 to 0.47 and 0.29 to 0.33,
Discussion
Clinical signs and symptoms of an IGSA exposure depend upon the route of exposure (inhalation, skin/eye contact, or ingestion).15 The Graniteville 2005 incident related primarily to inhalational exposures; therefore, this study validated signs and symptoms based on such an exposure. During a chemical MCI, when patient needs outstrip resources, patients must be triaged with particular emphasis given to the chemical’s impact on the respiratory system—an impact that may not be evident until after
Conclusion
This study is the first known study that uses actual patient data from a chemical incident to characterize the signs and symptoms of an IGSA syndrome. The characterization of signs and symptoms related to an IGSA syndrome is the first step in the development of a triage algorithm specifically designed for IGSA incidents. Once the IGSA triage algorithm is fully developed and tested, it will be incorporated into a computer informatics tool that is being designed to help emergency nurses
Joan M. Culley is Associate Professor, College of Nursing, University of South Carolina, Columbia, SC.
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Cited by (0)
Joan M. Culley is Associate Professor, College of Nursing, University of South Carolina, Columbia, SC.
Jane Richter is Co-Investigator, College of Nursing, University of South Carolina, Columbia, SC.
Sara Donevant is Co-Investigator, College of Nursing, University of South Carolina, Columbia, SC.
Abbas Tavakoli is Biostatistician, College of Nursing, University of South Carolina, Columbia, SC.
Jean Craig is Systems Architect and Database Warehouse, Office of Biomedical Informatics Systems/Health Sciences South Carolina, Medical University of South Carolina, Charleston, SC.
Salvatore DiNardi is Co-Investigator, College of Nursing, University of South Carolina, Columbia, SC.
Earn Up to 5.5 CE Hours. See page 381.
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This study was funded by National Library of Medicine grant 1R01LM011648.