Wetzel Thomas, Wienstroer Jan, Sopka Saša, Schroeder Hanna, Felzen Marc, Brokmann Jörg C, Plata Christopher
Department for Acute and Emergency Medicine, Medical Faculty RWTH, Aachen University, Pauwelsstrasse 30, 52074, Aachen, Germany.
Institute for Medical Informatics, Medical Faculty, RWTH Aachen University, Pauwelsstrasse 30, 52074, Aachen, Germany.
Sci Rep. 2025 Jul 29;15(1):27648. doi: 10.1038/s41598-025-12306-x.
Video-assisted dispatcher support in cardiopulmonary resuscitation (VA-CPR) has shown beneficial effects on CPR quality. This study examines the influence of professional background on the ability to identify typical errors in CPR performance using video-based assessments. Within this simulation-based observational study, 61 participants (31 EMS personnel, 30 emergency physicians) evaluated nine video sequences showing simulated CPR or ventilation. Participants were grouped by profession, not randomly. The primary endpoint was the correct identification of expert-defined errors in the presented videos, analyzed in relation to professional background. Evaluation accuracy for CPR and ventilation videos was examined in relation to participant characteristics. Overall, n = 427 CPR videos were correctly classified in 73.3% of cases by EMS personnel and 75.7% by emergency physicians (β = 0.370, SE = 0.297, 95% CI: -0.21 to 0.95, p = 0.213). Ventilation scenarios (n = 122) were correctly classified in 93.5% (EMS) and 98.3%, (EP) (β = 4.50, SE = 6.73, 95% CI: -8.82 to 17.82, p = 0.505). The models assessing classification accuracy for CPR and ventilation did not reach statistical significance (p=0.869 and p=0.183), and none of the tested predictors were significantly associated with evaluation accuracy. No significant differences in evaluation accuracy for CPR and ventilation videos were observed between professional groups or across tested participant characteristics.
心肺复苏术中的视频辅助调度员支持（VA-CPR）已显示出对心肺复苏质量有有益影响。本研究使用基于视频的评估方法，考察专业背景对识别心肺复苏操作中典型错误能力的影响。在这项基于模拟的观察性研究中，61名参与者（31名急救医疗服务人员、30名急诊医生）评估了9个显示模拟心肺复苏或通气的视频序列。参与者按职业分组，而非随机分组。主要终点是正确识别所呈现视频中专家定义的错误，并根据专业背景进行分析。针对参与者特征，考察了心肺复苏和通气视频的评估准确性。总体而言，急救医疗服务人员在73.3%的病例中正确分类了n = 427个心肺复苏视频，急诊医生的正确分类率为75.7%（β = 0.370，标准误 = 0.297，95%置信区间：-0.21至0.95，p = 0.213）。通气场景（n = 122）的正确分类率在急救医疗服务人员中为93.5%，在急诊医生中为98.3%（β = 4.50，标准误 = 6.73，95%置信区间：-8.82至17.82，p = 0.505）。评估心肺复苏和通气分类准确性的模型未达到统计学显著性（p = 0.869和p = 0.183），且没有一个测试预测因子与评估准确性显著相关。在专业组之间或在所测试的参与者特征中，未观察到心肺复苏和通气视频评估准确性的显著差异。
