Purpose: Automated external defibrillators (AED) prompt the rescuer to stop chest compressions (CC) for ECG analysis during out-of-hospital cardiac arrest (OHCA). We assessed the diagnostic accuracy and clinical benefit of a new AED algorithm (cprINSIGHT), which analyzes ECG and impedance signals during CC, allowing rhythm analysis with ongoing chest compressions.
Methods: Amsterdam Police and Fire Fighters used a conventional AED in 2016-2017 (control) and an AED with cprINSIGHT in 2018-2019 (intervention). In the intervention AED, cprINSIGHT was activated after the first (conventional) analysis. This algorithm classified the rhythm as "shockable" (S) and "non-shockable" (NS), or "pause needed". Sensitivity for S, specificity for NS with 90% lower confidence limit (LCL), chest compression fractions (CCF) and pre-shock pause were compared between control and intervention cases accounting for multiple observations per patient.
Results: Data from 465 control and 425 intervention cases were analyzed. cprINSIGHT reached a decision during CC in 70% of analyses. Sensitivity of the intervention AED was 96%, (LCL 93%) and specificity was 98% (LCL 97%), both not significantly different from control. Intervention cases had a shorter median pre-shock pause compared to control cases (8 s vs 22 s, p < 0.001) and higher median CCF (86% vs 80%, P < 0.001).
Conclusion: AEDs with cprINSIGHT analyzed the ECG during chest compressions in 70% of analyses with 96% sensitivity and 98% specificity when it made a S or a NS decision. Compared to conventional AEDs, cprINSIGHT leads to a significantly shorter pre-shock pause and a significant increase in CCF.
Keywords: Algorithm; Automated external defibrillator; Chest compression fraction; Chest compressions; Out-of-hospital cardiac arrest; Pre-shock pause; Rhythm analysis.
Copyright © 2021 The Authors. Published by Elsevier B.V. All rights reserved.