Key result
ECG filtering techniques during CPR achieve >99% sensitivity but <93% specificity for rhythm analysis, while amplitude spectrum area predicts defibrillation success with an AUC of 0.86.
Why the study?
Does see-through ECG technology improve rhythm analysis and defibrillation outcome prediction in patients undergoing cardiopulmonary resuscitation?
Does see-through ECG technology improve rhythm analysis and defibrillation outcome prediction in patients undergoing cardiopulmonary resuscitation?
Answers are grounded in this paper and cite their sources.
See-through ECG technology during CPR shows high sensitivity but limited specificity for rhythm analysis, though amplitude spectrum area is a promising predictor of defibrillation success.
PURPOSE OF REVIEW: Automated external defibrillators require preshock interruptions in cardiopulmonary resuscitation (CPR) to perform rhythm analysis. Artifact filtering technology may provide the opportunity to visualize the underlying ECG trace during CPR. Moreover, a continuous ventricular fibrillation analysis may be performed such to prioritize CPR interventions, that is, chest compression or defibrillation. RECENT FINDINGS: Different ECG filtering techniques and ventricular fibrillation analysis algorithms to predict defibrillation outcome have been developed. Techniques to analyze ECG rhythm during CPR encompass two major solutions: adaptive filters for the suppression of chest compression artifacts and algorithms for a direct analysis of the artifact-contaminated ECG. The above methods achieve overall a high sensitivity of more than 99%, but an unacceptable specificity of less than 93%. Among the different ventricular fibrillation analysis approaches and defibrillation predictors, amplitude spectrum area has appeared as an independent predictor of defibrillation success, with an area under the receiver operating curve of 0.86. SUMMARY: The feasibility of ventricular fibrillation detection during CPR is a challenging issue that, if solved, would enable CPR to continue during the automated external defibrillator rhythm analysis. Furthermore, it would allow a continuous ventricular fibrillation analysis to optimize the timing of defibrillation and maximize the shock success.
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Affatato et al. (2016) conducted a review in Cardiopulmonary resuscitation and ventricular fibrillation. See through ECG technology and artifact filtering was evaluated on Ventricular fibrillation detection and defibrillation outcome prediction. ECG filtering techniques during CPR achieve >99% sensitivity but <93% specificity for rhythm analysis, while amplitude spectrum area predicts defibrillation success with an AUC of 0.86.
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