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  1. Gan RK, Uddin H, Gan AZ, Yew YY, González PA
    Sci Rep, 2023 Nov 21;13(1):20350.
    PMID: 37989755 DOI: 10.1038/s41598-023-46986-0
    Since its initial launching, ChatGPT has gained significant attention from the media, with many claiming that ChatGPT's arrival is a transformative milestone in the advancement of the AI revolution. Our aim was to assess the performance of ChatGPT before and after teaching the triage of mass casualty incidents by utilizing a validated questionnaire specifically designed for such scenarios. In addition, we compared the triage performance between ChatGPT and medical students. Our cross-sectional study employed a mixed-methods analysis to assess the performance of ChatGPT in mass casualty incident triage, pre- and post-teaching of Simple Triage And Rapid Treatment (START) triage. After teaching the START triage algorithm, ChatGPT scored an overall triage accuracy of 80%, with only 20% of cases being over-triaged. The mean accuracy of medical students on the same questionnaire yielded 64.3%. Qualitative analysis on pre-determined themes on 'walking-wounded', 'respiration', 'perfusion', and 'mental status' on ChatGPT showed similar performance in pre- and post-teaching of START triage. Additional themes on 'disclaimer', 'prediction', 'management plan', and 'assumption' were identified during the thematic analysis. ChatGPT exhibited promising results in effectively responding to mass casualty incident questionnaires. Nevertheless, additional research is necessary to ensure its safety and efficacy before clinical implementation.
    Matched MeSH terms: Mass Casualty Incidents*
  2. Gan RK, Ogbodo JC, Wee YZ, Gan AZ, González PA
    Am J Emerg Med, 2024 Jan;75:72-78.
    PMID: 37967485 DOI: 10.1016/j.ajem.2023.10.034
    AIM: The objective of our research is to evaluate and compare the performance of ChatGPT, Google Bard, and medical students in performing START triage during mass casualty situations.

    METHOD: We conducted a cross-sectional analysis to compare ChatGPT, Google Bard, and medical students in mass casualty incident (MCI) triage using the Simple Triage And Rapid Treatment (START) method. A validated questionnaire with 15 diverse MCI scenarios was used to assess triage accuracy and content analysis in four categories: "Walking wounded," "Respiration," "Perfusion," and "Mental Status." Statistical analysis compared the results.

    RESULT: Google Bard demonstrated a notably higher accuracy of 60%, while ChatGPT achieved an accuracy of 26.67% (p = 0.002). Comparatively, medical students performed at an accuracy rate of 64.3% in a previous study. However, there was no significant difference observed between Google Bard and medical students (p = 0.211). Qualitative content analysis of 'walking-wounded', 'respiration', 'perfusion', and 'mental status' indicated that Google Bard outperformed ChatGPT.

    CONCLUSION: Google Bard was found to be superior to ChatGPT in correctly performing mass casualty incident triage. Google Bard achieved an accuracy of 60%, while chatGPT only achieved an accuracy of 26.67%. This difference was statistically significant (p = 0.002).

    Matched MeSH terms: Mass Casualty Incidents*
  3. Woodward CA, Hertelendy AJ, Hart A, Voskanyan A, Harutyunyan H, Virabyan A, et al.
    Prehosp Disaster Med, 2022 Dec;37(6):749-754.
    PMID: 36328971 DOI: 10.1017/S1049023X22002163
    INTRODUCTION: Emergency Medical Services (EMS) is a critical part of Disaster Medicine and has the ability to limit morbidity and mortality in a disaster event with sufficient training and experience. Emergency systems in Armenia are in an early stage of development and there is no Emergency Medicine residency training in the country. As a result, EMS physicians are trained in a variety of specialties.Armenia is also a country prone to disasters, and recently, the Armenian EMS system was challenged by two concurrent disasters when the 2020 Nagorno-Karabakh War broke out in the midst of the SARS-CoV-2/coronavirus disease 2019 (COVID-19) pandemic.

    STUDY OBJECTIVE: This study aims to assess the current state of disaster preparedness of the Armenian EMS system and the effects of the simultaneous pandemic and war on EMS providers.

    METHODS: This was a cross-sectional study conducted by anonymous survey distributed to physicians still working in the Yerevan EMS system who provided care to war casualties and COVID-19 patients.

    RESULTS: Survey response rate was 70.6%. Most participants had been a physician (52.1%) or EMS physician (66.7%) for three or less years. The majority were still in residency (64.6%). Experience in battlefield medicine was limited prior to the war, with the majority reporting no experience in treating mass casualties (52.1%), wounds from explosives (52.1%), or performing surgical procedures (52.1%), and many reporting minimal to no experience in treating gunshot wounds (62.5%), severe burns (64.6%), and severe orthopedic injuries (64.6%). Participants had moderate experience in humanitarian medicine prior to war. Greater experience in battlefield medicine was found in participants with more than three years of experience as a physician (z-score -3.26; P value

    Matched MeSH terms: Mass Casualty Incidents*
  4. Kamauzaman TH, Ahmad R, Latif KA, Hamzah MS, Kheng CP
    Malays J Med Sci, 2007 Jul;14(2):58-61.
    PMID: 22993493 MyJurnal
    Hand grenade explosion is a rare occasion in our local community. Most of us have seen or heard about the injuries only from the TV news or newspaper. We report two cases of bomb blast injury that occurred in an army camp in September 2000. These case studies illustrate the clinical presentations of hand grenade blast injures that present with multiple organ involvement. We would like to share our experience in managing such cases in a busy emergency department and highlight the outcome of those two cases. Certain issues pertaining to the complexity of the injuries and mass casualty management are also highlighted.
    Matched MeSH terms: Mass Casualty Incidents
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