Early Identification of Recurrent Out-of-hospital Cardiac Arrest Using Clinical ECG Features

Recurrent cardiac arrest (rearrest) after initial return of spontaneous circulation (ROSC) is associated with relatively poor outcomes. Early identification of rearrest might allow for intervention to prevent rearrest. In this study, we sought to determine whether clinical ECG features can predict rearrest.

We performed a retrospective cohort study of adult out-of-hospital cardiac arrest (OHCA) patients who achieved ROSC between 2018-2024. We evaluated the association of ECG features (QRS width, standard deviation of NN intervals, root mean square of successive NN interval differences, and percentage of NN intervals that differ by more than 50 milliseconds) within individual 15-second segments throughout a 5-minute window prior to rearrest as well as their temporal trends over the 5-minute analytic window.

Of the 1,489 OHCA patients achieving ROSC, 1,298 were analyzed; 528 (40.7%) experienced rearrest. Rearrest patients were older, less likely to receive bystander CPR (48.7% vs. 61.9%), and had lower survival (20.4% vs. 43.1%) and favorable neurologic outcomes (7.8% vs. 21.2%; all p<0.001). We found lower heart rate, wider QRS, and higher HR variability in those with rearrest. Identification was highest 1 minute prior to rearrest (AUROC 0.74), declining beyond 3 minutes. Models using temporal trends achieved AUROC 0.67; strongest predictors were heart rate variability measures and QRS width.

Established ECG features achieved good prediction for rearrest with identification improving closer to time of rearrest. Future work leveraging novel features or more advanced artificial intelligence models may further improve prediction.