European Journal of Emergency Medicine最新文献

Background and importance: Lactate is an already recognized biomarker for short-term mortality. However, how glycemia and diabetes affect the predictive ability of lactate needs to be revealed.

Objective: To determine how hypoglycemia, normoglycemia, and hyperglycemia modify the predictive ability of lactate for short-term mortality (3 days). The secondary objective was to evaluate the predictive ability of lactate in diabetic patients.

Design, settings and participants: Prospective, observational study performed between 26 October 2018 and 31 December 2022. Multicenter, EMS-delivery, ambulance-based study, considering 38 basic life support units and 5 advanced life support units referring to four tertiary care hospitals (Spain). Eligible patients were adults recruited from among all phone requests for emergency assistance who were later evacuated to emergency departments.

Outcomes measure and analysis: The primary outcome was in-hospital mortality from any cause within the third day following EMS attendance. The main predictors considered were lactate, blood glucose levels and previous diabetes.

Main results: A total of 6341 participants fulfilled the inclusion criteria. 68 years (IQR: 51-80); 41.4% were female. The 3-day in-hospital mortality rate was 3.5%. The predictive capacity of lactate for 3-day mortality was only significantly different between normo-glycemia and hyperglycemia. The best predictive result was for normo-glycemia - AUC = 0.897 (95% CI: 0.881-0.913) - then hyperglycemia - AUC = 0.819 (95% CI: 0.770-0.868) and finally, hypoglycemia - AUC = 0.703 (95% CI: 0.422-0.983). The stratification according to diabetes presented no statistically significant difference, and the predictive results were AUC = 0.924 (95% CI: 0.892-0.956), AUC = 0.906 (95% CI: 0.884-0.928), and AUC = 0.872 (95% CI: 0.817-0.927) for nondiabetes, uncomplicated cases, and end-organ damage diabetes, respectively.

Conclusion: Our results demonstrated that glycemia, but not diabetes, alters the predictive ability of lactate. Therefore, hyperglycemia should be considered when interpreting lactate, since this could improve screening to detect cryptic shock conditions.

Background and importance: There seems to be evidence of gender and ethnic bias in the early management of acute coronary syndrome. However, whether these differences are related to less severe severity assessment or to less intensive management despite the same severity assessment has not yet been established.

Objective: To show whether viewing an image with characters of different gender appearance or ethnic background changes the prioritization decision in the emergency triage area.

Methods: The responders were offered a standardized clinical case in an emergency triage area. The associated image was randomized among eight standardized images of people presenting with chest pain and differing in gender and ethnic appearance (White, Black, North African and southeast Asian appearance).

Outcome measures and analysis: Each person was asked to respond to a single clinical case, in which the priority level [from 1 (requiring immediate treatment) to 5 (able to wait up to 2 h)] was assessed visually. Priority classes 1 and 2 for vital emergencies and classes 3-5 for nonvital emergencies were grouped together for analysis.

Results: Among the 1563 respondents [mean age, 36 ± 10 years; 867 (55%) women], 777 (50%) were emergency physicians, 180 (11%) emergency medicine residents and 606 (39%) nurses. The priority levels for all responses were 1-5 : 180 (11%), 686 (44%), 539 (34%), 131 (9%) and 27 (2%). There was a higher reported priority in male compared to female [62% vs. 49%, difference 13% (95% confidence interval; CI 8-18%)]. Compared to White people, there was a lower reported priority for Black simulated patients [47% vs. 58%, difference -11% (95% CI -18% to -4%)] but not people of southeast Asian [55% vs. 58%, difference -3% (95% CI -10-5%)] and North African [61% vs. 58%, difference 3% (95% CI -4-10%)] appearance.

Conclusion: In this study, the visualization of simulated patients with different characteristics modified the prioritization decision. Compared to White patients, Black patients were less likely to receive emergency treatment. The same was true for women compared with men.