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Background: Stress may impair the success of procedures in emergency medicine. The aims were to assess residents' stress during simulated and clinical lumbar punctures (LPs) and to explore the correlation of stress and performance., Methods: A prospective study (2013-2016) was carried out in a pediatric emergency department. A mastery training and subsequently a just-in-time training were conducted immediately preceding each clinical LP. Stress was self-assessed by the Stress-O-Meter scale (0-10). Performance (checklist 0-6 points) and success rate (cerebrospinal fluid with <1000 red blood cells/mm3) were recorded by a trained supervisor. A survey explored self-confidence and potential causes of stress., Results: Thirty-three residents performed 35 LPs. There was no stress during simulation procedure. Stress levels significantly increased for clinical procedure (P < 0.0001). Performance was similar in simulation and in clinic (respectively, 5.50 ± 0.93 vs 5.42 ± 0.83; P = 0.75). Success significantly decreased during clinical LP (P < 0.0001). The 2 most reported stress-related factors were fear of technical errors and personal fatigue., Conclusions: Performance scores and success rates in simulation are insufficient to predict success in clinical situations. Stress level and stress-related factors (fear of technical errors and personal fatigue) might be different in simulated or real conditions and consequently impact success of a technical procedure even if a high-performance score is recorded., Competing Interests: Disclosure: The authors declare no conflict of interest., (Copyright © 2020 Wolters Kluwer Health, Inc. All rights reserved.)

Background: One of the primary goals of simulation-based education is to enable long-term retention of training gains. However, medical literature has poorly contributed to understanding the best timing for repetition of simulation sessions. There is heterogeneity in re-training recommendations., Objectives: This study assessed, through simulation-based training in different groups, the long-term retention of rare pediatric technical procedures., Methods: This multicenter observational study included 107 emergency physicians and residents. Eighty-eight were divided into four groups that were specifically trained for pediatric emergency procedures at different points in time between 2010 and 2015 (< 0.5 year prior for G1, between 0.5 and 2 years prior for G2, between 2 and 4 years prior for G3, and ≥ 4 years prior for G4). An untrained control group (C) included 19 emergency physicians. Participants were asked to manage an unconscious infant using a low-fidelity mannequin. Assessment was based on the performance at 6 specific tasks corresponding to airway (A) and ventilation (B) skills. The performance (scored on 100) was evaluated by the TAPAS scale (Team Average Performance Assessment Scale). Correlation between performance and clinical level of experience was studied., Results: There was a significant difference in performance between groups (p < 0.0001). For G1, 89% of the expected tasks were completed but resulted in longer delays before initiating actions than for the other groups. There was no difference between G4 and C with less than half of the tasks performed (47 and 43% respectively, p = 0.57). There was no correlation between clinical level of experience and performance (p = 0.39)., Conclusion: Performance decreased at 6 months after specific training for pediatric emergency skills, with total loss at 4 years after training, irrespective of experience. Repetition of simulation sessions should be implemented frequently after training to improve long-term retention and the optimal rate of refresher courses requires further research.

In recent decades, climate change has been responsible for an increase in the average temperature of the troposphere and of the oceans, with consequences on the frequency and intensity of many extreme weather phenomena. Climate change&rsquo;s effects on natural disasters can be expected to induce a rise in humanitarian crises. In addition, it will surely impact the population&rsquo;s long-term general health, especially among the most fragile. There are foreseeable health risks that both ambulatory care organizations and hospitals will face as global temperatures rise. These risks include the geographic redistribution of infectious (particularly zoonotic) diseases, an increase in cardiac and respiratory illnesses, as well as a host of other health hazards. Some of these risks have been detailed for most developed countries as well as for some developing countries. Using these existing risk assessments as a template, organizational innovations as well as implementation strategies should be proposed to mitigate the disruptive effects of these health risks on emergency departments and by extension, reduce the negative impact of climate change on the populations they serve.

Stress might impair clinical performance in real life and in simulation-based education (SBE). Subjective or objective measures can be used to assess stress during SBE. This monocentric study aimed to evaluate the effects of simulation of life-threatening events on measurements of various stress parameters (psychological, biological, and electrophysiological parameters) in multidisciplinary teams (MDTs) during SBE. The effect of gender and status of participants on stress response was also investigated. Twelve emergency MDTs of 4 individuals were recruited for an immersive simulation session. Stress was assessed by: (1) self-reported stress; (2) Holter analysis, including heart rate and heart rate variability in the temporal and spectral domain (autonomic nervous system); (3) salivary cortisol (hypothalamic pituitary adrenal axis). Forty-eight participants (54.2% men, <7years of experience) were included. Measures were performed at baseline (T0), after simulation (T1), after debriefing (T2), and 30min after debriefing (T3). There was an increase in stress level at T1 (p<0.001) and a decrease at T2 (p<0.001). However, the variations of stress parameters induced by simulation (T0-T1 difference and T1-T2 difference) estimated by the three approaches were not correlated, while, as expected, Holter parameters were well-correlated to each other. Immersive SBE produced a change of stress level in all MDT members with no evidence for status effect but with gender difference. None developed a PTSD. These results support the hypothesis of a complementarity of the stress paths (collective reaction with increased stress level during simulation and a decrease during debriefing) but with relative independence of these paths (lack of correlation to each other). This study also suggests that because of the lack of correlation, stress response should be assessed by a combination of psychological, biological and electrophysiological parameters., (Copyright © 2017 Australian College of Critical Care Nurses Ltd. Published by Elsevier Ltd. All rights reserved.)

In the field of emergency medicine (EM), the use of decision support tools based on artificial intelligence has increased markedly in recent years. In some cases, data are omitted deliberately and thus constitute "data not purposely collected" (DNPC). This accepted information bias can be managed in various ways: dropping patients with missing data, imputing with the mean, or using automatic techniques (e.g., machine learning) to handle or impute the data. Here, we systematically reviewed the methods used to handle missing data in EM research. A systematic review was performed after searching PubMed with the query "(emergency medicine OR emergency service) AND (artificial intelligence OR machine learning)". Seventy-two studies were included in the review. The trained models variously predicted diagnosis in 25 (35%) publications, mortality in 21 (29%) publications, and probability of admission in 21 (29%) publications. Eight publications (11%) predicted two outcomes. Only 15 (21%) publications described their missing data. DNPC constitute the "missing data" in EM machine learning studies. Although DNPC have been described more rigorously since 2020, the descriptions in the literature are not exhaustive, systematic or homogeneous. Imputation appears to be the best strategy but requires more time and computational resources. To increase the quality and the comparability of studies, we recommend inclusion of the TRIPOD checklist in each new publication, summarizing the machine learning process in an explicit methodological diagram, and always publishing the area under the receiver operating characteristics curve—even when it is not the primary outcome. [ABSTRACT FROM AUTHOR]