Assessing the precision of artificial intelligence in ED triage decisions: Insights from a study with ChatGPT.

BACKGROUND: The rise in emergency department presentations globally poses challenges for efficient patient management. To address this, various strategies aim to expedite patient management. Artificial intelligence's (AI) consistent performance and rapid data interpretation extend its healthcare applications, especially in emergencies. The introduction of a robust AI tool like ChatGPT, based on GPT-4 developed by OpenAI, can benefit patients and healthcare professionals by improving the speed and accuracy of resource allocation. This study examines ChatGPT's capability to predict triage outcomes based on local emergency department rules. METHODS: This study is a single-center prospective observational study. The study population consists of all patients who presented to the emergency department with any symptoms and agreed to participate. The study was conducted on three non-consecutive days for a total of 72 h. Patients' chief complaints, vital parameters, medical history and the area to which they were directed by the triage team in the emergency department were recorded. Concurrently, an emergency medicine physician inputted the same data into previously trained GPT-4, according to local rules. According to this data, the triage decisions made by GPT-4 were recorded. In the same process, an emergency medicine specialist determined where the patient should be directed based on the data collected, and this decision was considered the gold standard. Accuracy rates and reliability for directing patients to specific areas by the triage team and GPT-4 were evaluated using Cohen's kappa test. Furthermore, the accuracy of the patient triage process performed by the triage team and GPT-4 was assessed by receiver operating characteristic (ROC) analysis. Statistical analysis considered a value of p < 0.05 as significant. RESULTS: The study was carried out on 758 patients. Among the participants, 416 (54.9%) were male and 342 (45.1%) were female. Evaluating the primary endpoints of our study - the agreement between the decisions of the triage team, GPT-4 decisions in emergency department triage, and the gold standard - we observed almost perfect agreement both between the triage team and the gold standard and between GPT-4 and the gold standard (Cohen's Kappa 0.893 and 0.899, respectively; p < 0.001 for each). CONCLUSION: Our findings suggest GPT-4 possess outstanding predictive skills in triaging patients in an emergency setting. GPT-4 can serve as an effective tool to support the triage process.

Examination of the Effects of 4-Hour Nonvalved Filtering Facepiece Respirator Use on Blood Gas Values of Health Care Professionals: A Before and After Study.

INTRODUCTION: The use of personal protective equipment increased rapidly during the COVID-19 pandemic that began in 2019. The purpose of this study was to examine the effects of uninterrupted 4-hour use of internationally certified nonvalved filtering facepiece respirators on venous blood gas in health care workers during the COVID-19 pandemic. METHODS: A before-after design included venous blood gas analyses collected at the beginning of shifts before nonvalved filtering facepiece respirator had been put on and after 4-hour uninterrupted use of nonvalved filtering facepiece respirator. RESULTS: In this study, 33 volunteer health care workers took part. In terms of blood gas values, mean pCO2 values were 47.63 (SD = 5.16) before and 47.01 (SD = 5.07) after nonvalved filtering facepiece respirator use, mean HCO3 values were 23.68 (SD = 1.10) in first blood gas analysis and 24.06 (SD = 1.31) in second blood gas analysis, and no significant difference was observed between before and after the use of nonvalved filtering facepiece respirator (t = 0.67, P = .50, t = -2.0, P = .054, respectively). The only significant difference in parameters investigated between the groups was in pH levels, at pH = 7.35 (SD = 0.29) before and pH = 7.36 (SD = 0.20) after nonvalved filtering facepiece respirator use (t = -2.26, P = .03). CONCLUSION: Continuous nonvalved filtering facepiece respirator use for 4 hours was not associated with clinician impairment in blood gas and peripheral SpO2 levels during nonexertional clinical ED work.