Zhuoyan Xie1, Qiyu Yang1, Ming Li1, Zhaolan Huang1, Yue Wang2, Qin Ling3, Wanchun Tang4, Zhengfei Yang5. 1. School of Automation, GuangDong University of Technology, Guangzhou, China. 2. Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China. 3. Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China; ZengCheng District People's Hospital of GuangZhou, Guangzhou, China. 4. Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China; Weil Institute of Emergency and Critical Care Research, School of Medicine, Virginia Commonwealth University, Richmond, VA, USA. Electronic address: wanchun.tang@vcuhealth.org. 5. Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China; ZengCheng District People's Hospital of GuangZhou, Guangzhou, China; Weil Institute of Emergency and Critical Care Research, School of Medicine, Virginia Commonwealth University, Richmond, VA, USA. Electronic address: yangzhengfei@vip.163.com.
Abstract
PURPOSE: A novel amplitude screening method, termed Optimal Amplitude Spectrum Area (Opt-AMSA) with the aim of improving the performance of the Amplitude Spectrum Area (AMSA) method, was proposed to optimize the timing of defibrillation. We investigated the effects of the Opt-AMSA method on the prediction of successful defibrillation when compared with AMSA in a porcine model of ventricular fibrillation (VF). METHOD: 60 male domestic pigs were untreated in the first 10 min of VF, then received cardiopulmonary resuscitation (CPR) for 6 min. Values of Opt-AMSA and AMSA were calculated every minute before defibrillation. Linear regression was used to evaluate the correlation between Opt-AMSA and AMSA. Receiver Operating Characteristic (ROC) analysis was conducted for the two methods and to compare their predictive values. RESULTS: The values of both AMSA and Opt-AMSA gradually decreased over time during untreated VF in all animals. The values of both methods of defibrillation were slightly increased after the implementation of CPR in animals that were successfully resuscitated, while there were no significant changes in either method in those who ultimately failed to resuscitate. The significant positive correlation between Opt-AMSA and AMSA was shown by Pearson correlation analysis. ROC analysis showed that Opt-AMSA (AUC = 0.87) significantly improved the performance of AMSA (AUC = 0.77) to predict successful defibrillation (Z = 2.27, P < 0.05). CONCLUSION: Both the Opt-AMSA and AMSA methods showed high potential to predict the success of defibrillation. Moreover, the Opt-AMSA method improved the performance of the AMSA method, and may be a promising tool to optimize the timing of defibrillation.
PURPOSE: A novel amplitude screening method, termed Optimal Amplitude Spectrum Area (Opt-AMSA) with the aim of improving the performance of the Amplitude Spectrum Area (AMSA) method, was proposed to optimize the timing of defibrillation. We investigated the effects of the Opt-AMSA method on the prediction of successful defibrillation when compared with AMSA in a porcine model of ventricular fibrillation (VF). METHOD: 60 male domestic pigs were untreated in the first 10 min of VF, then received cardiopulmonary resuscitation (CPR) for 6 min. Values of Opt-AMSA and AMSA were calculated every minute before defibrillation. Linear regression was used to evaluate the correlation between Opt-AMSA and AMSA. Receiver Operating Characteristic (ROC) analysis was conducted for the two methods and to compare their predictive values. RESULTS: The values of both AMSA and Opt-AMSA gradually decreased over time during untreated VF in all animals. The values of both methods of defibrillation were slightly increased after the implementation of CPR in animals that were successfully resuscitated, while there were no significant changes in either method in those who ultimately failed to resuscitate. The significant positive correlation between Opt-AMSA and AMSA was shown by Pearson correlation analysis. ROC analysis showed that Opt-AMSA (AUC = 0.87) significantly improved the performance of AMSA (AUC = 0.77) to predict successful defibrillation (Z = 2.27, P < 0.05). CONCLUSION: Both the Opt-AMSA and AMSA methods showed high potential to predict the success of defibrillation. Moreover, the Opt-AMSA method improved the performance of the AMSA method, and may be a promising tool to optimize the timing of defibrillation.