• Vishal Gupta, Robert H Schmicker, Pamela Owens, Ava E Pierce, and Ahamed H Idris.
• University of Texas Southwestern Medical School, 5323 Harry Hines Blvd, Dallas, TX 75390-8579, United States.
• Resuscitation. 2021 Mar 1; 160: 7-13.

BackgroundHigh-quality chest compressions are associated with improved outcomes after cardiac arrest. Defibrillators record important information about chest compressions during cardiopulmonary resuscitation (CPR) and can be used in quality-improvement programs. Defibrillator review software can automatically annotate files and measure chest compression metrics. However, evidence is limited regarding the accuracy of such measurements.ObjectiveTo compare chest compression fraction (CCF) and rate measurements made with software annotation vs. manual annotation vs. limited manual annotation of defibrillator files recorded during out-of-hospital cardiac arrest (OHCA) CPR.MethodsThis was a retrospective, observational study of 100 patients who had CPR for OHCA. We assessed chest compression bioimpedance waveforms from the time of initial CPR until defibrillator removal. A reviewer revised software annotations in two ways: completely manual annotations and limited manual annotations, which marked the beginning and end of CPR and ROSC, but not chest compressions. Measurements were compared for CCF and rate using intraclass correlation coefficient (ICC) analysis.ResultsCase mean rate showed no significant difference between the methods (108.1-108.6 compressions per minute) and ICC was excellent (>0.90). The case mean (±SD) CCF for software, manual, and limited manual annotation was 0.64 ± 0.19, 0.86 ± 0.07, and 0.81 ± 0.10, respectively. The ICC for manual vs. limited manual annotation of CCF was 0.69 while for individual minute epochs it was 0.83.ConclusionSoftware annotation performed very well for chest compression rate. For CCF, the difference between manual and software annotation measurements was clinically important, while manual vs. limited manual annotation were similar with an ICC that was good-to-excellent.Copyright © 2020 Elsevier B.V. All rights reserved.

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