Arrhythmias & electrophysiology
Frequency Domain Analysis of Endocardial Electrograms for Detection of Nontransmural Myocardial Fibrosis in Nonischemic Cardiomyopathy
Authors' conclusion
These data indicate the promising discriminatory value of endocardial EGM frequency content in the assessment of concealed myocardial substrate.
Study context
- Population
- Nonischemic cardiomyopathy patients undergoing VT ablation with preprocedural cardiac CT and late iodine enhancement
- Participants
- 13 patients6,015 EGM pairs
- Comparison
- Frequency-domain EGM features vs voltage amplitude for predicting MMF
- Outcome
- Prediction of midmyocardial fibrosis (MMF) presence (AUC)
Methodological detailssupervised machine learning, stratified k-fold cross-validation within patients
- Supervised machine learning
- Stratified k-fold cross-validation within patients
Performance
As reported in the abstract
Mean AUC for MMF prediction
| Test or model | Mean AUC |
|---|---|
| Frequency features | 0.841 (95% CI: 0.789-0.884) |
| Voltage | 0.591 (95% CI: 0.530-0.658) |
Mean AUC
Frequency features0.841 (95% CI: 0.789-0.884)
Voltage0.591 (95% CI: 0.530-0.658)
- Frequency features vs Voltage: P < 0.001 — frequency-trained classifiers better predicted MMF
Original publication
Frequency Domain Analysis of Endocardial Electrograms for Detection of Nontransmural Myocardial Fibrosis in Nonischemic Cardiomyopathy. JACC Clin Electrophysiol. Published 18 January 2023. doi:10.
Composed by AI from the published abstract and checked against it. How Briefs are made →