• Yingying Hu, Hanqi Tang, Chenguang Liu, Daoyuan Jing, Huadong Zhu, Yazhi Zhang, Xuezhong Yu, Guoxiu Zhang, and Jun Xu.
• Department of Emergency Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, 100730, China; The First Affiliated Hospital, and College of Clinical Medicine of Henan University of Science and Technology, Luoyang, 471003, China.
• Resuscitation. 2019 Oct 1; 143: 1-9.

ObjectiveTo explore a new algorithm and strategy for rhythm analysis during chest compressions (CCs), and to improve the efficiency of cardiopulmonary resuscitation (CPR) by minimizing interruptions.MethodsThe clinical data and ECG of patients with sudden cardiac arrest (CA) from three hospitals in China were collected with Philips MRx monitor/defibrillators. The length of each analyzed ECG segment was 23 s, the first 11.5 s was selected to contain CPR compressions, the next 5 s had no compressions, and the last 6.5 s had no requirement. Three experienced emergency doctors annotated the ECG segments without compression artifacts. A two-step analysis through CPR (ATC) algorithm was applied to the selected data. The first step was analysis during chest compressions. If a shockable rhythm was not detected, compression-free analysis followed. The results of the ATC algorithm were compared with the annotations by the physicians, to determine the sensitivity and specificity of the algorithm.ResultsIn total 166 CA patients were included with 100 out-of-hospital cardiac arrest (OHCA) patients and 66 in-hospital cardiac arrest (IHCA) patients. A total of 1578 ECG segments were analyzed, including 115 (7.3%) shockable rhythms, 1278 (81.0%) non-shockable rhythms, and 185 (11.7%) intermediate/unknown rhythms. The specificity of all non-shockable rhythms was 99.8% at the end of chest compressions, and 99.5% after analysis without compression artifact. 70.5% of ventricular fibrillation (VF) rhythms were detected by the end of chest compressions. After the CC-free analysis, 93.6% of VF was identified.ConclusionThe ATC algorithm achieved sensitivity of 93.6% and specificity of 99.5% after the two-step analysis, and 70.5% of the patients with shockable rhythms did not require CC-free analysis. Such an approach has the potential to substantially reduce CC interruptions when identifying shockable rhythms.Copyright © 2019 Elsevier B.V. All rights reserved.

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