CJEM最新文献

Background: Language barriers in pediatric emergency medicine discharge instructions can impact patient safety, leading to poorer post-discharge outcomes. Google Translate has been widely used clinically as an alternative to professional translations but is prone to errors. ChatGPT-4 is a large language model that has been shown to offer improved translation abilities in various domains. This study compares ChatGPT-4 and Google Translate for translating discharge instructions into Arabic and Simplified Chinese.

Methods: 15 standardized pediatric emergency department discharge instructions from our institution were translated from English to both Simplified Chinese and Arabic, using both ChatGPT-4 and Google Translate. Eight bilingual medical professionals (four per language group) were recruited as participants and presented with the English and the translated discharge instructions in a blinded manner. Participants rated the translations on a 5-point Likert scale for accuracy, safety, and understandability, followed by their overall translation preference.

Results: In Arabic, ChatGPT-4 was found to be more accurate than Google Translate, (mean 4.1 vs. 3.7, mean difference = 0.43, 95% CI 0.15, 0.72, p = 0.003). Similarly for Simplified Chinese, ChatGPT-4 was found to be more accurate than Google Translate (mean 4.4 vs. 4.2; mean difference = 0.28, 95% CI 0.07, 0.50, p = 0.010). There were no significant differences in safety or understandability between ChatGPT-4 and Google Translate in either language. ChatGPT-4-generated translations were consistently preferred over Google Translate in both languages.

Conclusion: Overall, ChatGPT-4 is a more accurate alternative to Google Translate in translating written pediatric discharge instructions from English to Simplified Chinese and Arabic. ChatGPT-4 could be a particularly valuable translation tool in healthcare settings with limited access to translation resources such as professional interpreters.

Background: Patients with symptoms of acute coronary syndrome make up a significant proportion of emergency department (EDs) presentations. High-sensitivity troponin testing is a standard component of evaluating patients with suspected symptomatic coronary disease. We sought to synthesize the evidence of the accuracy of 0/2-h and 0/3-h algorithms using the Beckman Access high-sensitivity cardiac troponin I (hs-cTnI) assay.

Methods: We developed an electronic search strategy retrieving research from three electronic databases (Medline, Embase, and Wiley Cochrane Library). Relevant research studies were screened and data extracted by a team of reviewers. Study quality and risk assessment were appraised using the QUADAS-2 tool. Findings were reported according to PRISMA guidelines.

Results: Five studies met inclusion criteria. No studies directly compared the 0 h/2 h and 0 h/3 h algorithms using the Beckman Coulter Access hs-cTnI assay, and heterogeneity in study design precluded meta-analysis. Included studies variably used 2-h, 3-h, or intermediate timepoints for serial troponin measurement. All studies reported consistently high sensitivity (> 97.7%) and NPV (> 98.9%) for ruling out acute myocardial infarction, supporting the reliability of both 0/2 h and 0/3 h hs-cTnI algorithms in the ED.

Conclusions: Of the five studies included, two studies suggest that a two-hour hs-TnI algorithm can effectively rule out myocardial infarction with similar accuracy to a longer three-hour protocol. Use of a 2-h hs-cTnI algorithm may lead to operational gains compared to a 3-h serial testing algorithm.

Purpose: The cultural mosaic within Canadian emergency department patient populations remains underrepresented in the medical workforce, yet minimal data exist on emergency medicine trainee demographics. This raises questions about recruitment practices and how equity, diversity, inclusion, Indigeneity, and accessibility are being advanced. This study evaluates the current state of diversity and inclusion among Royal College emergency medicine residents to identify key areas of underrepresentation.

Methods: A national cross-sectional survey was conducted across all programs. An online Qualtrics® questionnaire, adapted from the Canadian Resident Matching Service self-identification tool, was distributed to residents (PGY 1-5) by program directors and administrators. The survey captured gender identity, sexual orientation, racialized background, teenage household income, and disability. It was translated into French by a French-speaking author. Ethics approval was granted by the University of British Columbia research ethics board. Descriptive statistics were applied and responses were compared with 2021 Canadian Census data.

Results: We received 227/418 responses (54.3%) from residents across all programs. Emergency medicine residents were significantly less likely to report teenage household income under $100,000 (36.1% vs. 59.6% in the Canadian population). Disability was reported by 10.1% of residents, compared to 27.0% nationally. Indigenous representation was slightly lower overall (4.0% vs. 5.0%), with the largest regional gap in the Prairies (2.5% vs. 10.6%). Visible minority representation was comparable nationally (27.4% vs. 26.5%) but varied geographically, with lower proportions in the Prairies and Ontario. Representation was higher among junior trainees, suggesting recent progress in admissions inclusivity.

Conclusion: This is the first national description of the demographic and socioeconomic profile of Canadian emergency medicine residents. While some national-level metrics were encouraging, significant underrepresentation was observed in income, disability, and Indigenous identity, with notable regional disparities. Establishing this baseline enables ongoing monitoring and informs equity-focused reforms in admissions and residency training. Query ID="Q3" Text="As per the instruction, other language abstracts like ……….. are required, but are not provided. Could you please provide the other language abstracts?"