Background: Quantitative measures of the ventricular fibrillation (VF) electrocardiogram (ECG) waveform can assess myocardial physiology and predict cardiac arrest outcomes, making these measures a candidate to help guide resuscitation. Chest compressions are typically paused for waveform measure calculation, as compressions cause ECG artifact. However, such pauses contradict resuscitation guideline recommendations to minimize CPR interruptions. We evaluated a comprehensive group of VF measures with and without ongoing compressions to determine their performance under both conditions for predicting functionally-intact survival, the study’s primary outcome. Methods: Five-second VF ECG segments were collected with and without chest compressions prior to 2755 defibrillation shocks from 1151 out-of-hospital cardiac arrest patients. Twenty-four individual measures and three combination measures were implemented. Measures were optimized to predict functionally-intact survival (Cerebral Performance Category score ≤ 2) using 460 training cases, and their performance evaluated using 691 independent test cases. Results: Measures predicted functionally-intact survival on test data with an area under the receiver operating characteristic curve (AUC) ranging from 0.56-0.75 (median=0.73) without chest compressions and from 0.53-0.75 (median=0.69) with compressions (p<0.001 for difference). Of all measures evaluated, the support vector machine model ranked highest both without chest compressions (AUC=0.75, 95% CI 0.73-0.78) and with compressions (AUC=0.75, 95% CI 0.72-0.78) (p=0.75 for difference). Conclusions: VF waveform measures predict functionally-intact survival when calculated during chest compressions, but prognostic performance is generally reduced compared to compression-free analysis. However, support vector machine models exhibited similar performance with and without compressions while also achieving the highest AUC. Such machine learning models may therefore offer means to guide resuscitation during uninterrupted CPR.

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