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Real-time electrogram analysis for monitoring coronary blood flow during human ventricular fibrillation: implications
Karthikeyan Umapathy1, Farbod H Foomany, Paul Dorian
1Ryerson University, Toronto, Ontario, Canada.
Insights
Chest compressions during ventricular fibrillation (VF) improve defibrillation success. This study shows wavelet analysis of VF electrograms can monitor coronary blood flow, potentially guiding chest compression efficacy.
Area of Science:
- Cardiology
- Biomedical Engineering
- Signal Processing
Background:
- Effective chest compressions during ventricular fibrillation (VF) are crucial for defibrillation success.
- Current methods lack the ability to measure antegrade coronary artery flow during chest compressions in VF.
Purpose of the Study:
- To quantify the relationship between antegrade coronary flow and human VF characteristics.
- To utilize near real-time wavelet-based electrocardiographic markers for this assessment.
Main Methods:
- Experiments conducted on 8 isolated human hearts using Langendorff perfusion to simulate varying chest compression efficacies (0%, 30%, 100% flow).
- Ventricular fibrillation (VF) induced, followed by ischemia and reperfusion periods.
- Surface electrograms recorded and analyzed using continuous wavelet transform.
Main Results:
- Wavelet features derived from VF signals showed significant differences correlating with perfusion rates (P < .0006).
- A pattern classifier predicted flow rates with 90% accuracy in independent hearts.
- Demonstrated a link between VF signal complexity and coronary flow.
Conclusions:
- Ventricular fibrillation (VF) electrogram characteristics, analyzed via wavelets, correlate with antegrade coronary flow rate.
- Near real-time wavelet analysis may offer a method to monitor chest compression efficacy during VF.
Background:
Effective chest compressions during prolonged ventricular fibrillation (VF) have been shown to increase the chances of successful defibrillation to a rhythm associated with a sustainable cardiac output. There is currently no effective method of recording the degree of antegrade coronary artery flow during chest compression in VF.
Objective:
This study sought to quantify the relationship between the antegrade coronary flow and the characteristics of human VF using near real-time wavelet-based electrocardiographic markers.
Methods:
VF experiments were conducted in 8 isolated human hearts. The Langendorff perfusion enabled different flow rates (perfusion) during VF, which allowed for the simulation of chest compression with different efficacies. After the initiation of VF, the hearts were maintained in ischemia (no flow) for 3 minutes, followed by a 2-minute reperfusion and defibrillation. The experiments were repeated at flows of 0%, 30%, and 100% of baseline perfusion, and volume-conducted surface electrograms were recorded and analyzed using continuous wavelet transform in 5-second frames.
Results:
Near real-time wavelet features were derived that demonstrated significant differences in the multicomponent nature of VF signals and predicted perfusion rate characteristics for different flow rates (i.e., 0%, 30%, and 100%; P < .0006). A pattern classifier was trained using the feature values from 5 hearts, and the flow rates for 3 additional hearts were predicted with an accuracy of 90%.
Conclusion:
VF electrogram characteristics as measured by wavelet analysis relate to antegrade coronary flow rate during VF. These findings suggest that chest compression efficacy of physiological importance could be monitored using near real-time wavelet analysis.
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