Cardiac arrest & resuscitation
Prediction of shock-refractory ventricular fibrillation in patients with out-of-hospital cardiac arrest: external validation of an electrocardiogram (ECG)-based approach
Authors' conclusion
A strategy using ECG features surrounding initial shock showed robust performance for predicting refractory VF in a distinct patient population.
Study context
- Population
- Out-of-hospital cardiac arrest (OHCA) patients with initial shockable rhythm, Seoul OHCA registry (2020–2023)
- Participants
- 428 patients
- Exposure
- ECG-feature logistic model (25 scalogram features before and after first shock) for predicting refractory ventricular fibrillation (VF) vs original study's reported AUC
- Outcome
- Prediction of refractory VF (≥3 total shocks), AUC via leave-one-out cross-validation (LOOCV)
Methodological detailsexternal validation, registry-based, leave-one-out cross-validation
- External validation
- Registry-based
- Leave-one-out cross-validation
Main finding
As reported in the abstract
Refractory VF (≥3 total shocks)
| Group | AUC |
|---|---|
| ECG-feature model | 0.782 [95% CI 0.736-0.828] |
ECG-feature model
AUC0.782 [95% CI 0.736-0.828]
- ECG-feature model vs Original study AUC 0.846: P = 0.060 — not significantly different
Observational data: associations, not effects.
Further findings
| Outcome | Values | P value |
|---|---|---|
| Refractory VF, alternative definition (≥3 consecutive shocks)ECG-feature model vs Original study AUC 0.846 · not significantly different | ECG-feature model AUC 0.805 [95% CI 0.762-0.858] | P = 0.22 |
Original publication
Prediction of shock-refractory ventricular fibrillation in patients with out-of-hospital cardiac arrest: external validation of an ECG-based approach. Resuscitation. Published 30 April 2026. doi:10.
Composed by AI from the published abstract and checked against it. How Briefs are made →