The performance of a new shock advisory algorithm to reduce interruptions during CPR

Objective: To 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.

Methods: The 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.

Results: In 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.

Conclusion: The 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.