Electrophysiologic Determinants of Isoelectric Intervals on Surface Electrocardiograms During Atrial Tachycardia: Insights From High-Density Mapping.

BACKGROUND: Substrate abnormalities can alter atrial activation during atrial tachycardias (ATs) thereby influencing AT-wave morphology on the surface electrocardiogram. OBJECTIVES: This study sought to identify determinants of isoelectric intervals during ATs with complex atrial activation patterns. METHODS: High-density activation maps of 126 ATs were studied. To assess the impact of the activated atrial surface on the presence of isoelectric intervals, this study measured the minimum activated area throughout the AT cycle, defined as the smallest activated area within a 50-millisecond period, by using signal processing algorithms (LUMIPOINT). RESULTS: ATs with isoelectric intervals (P-wave ATs) included 23 macro-re-entrant ATs (40%), 26 localized-re-entrant ATs (46%), and 8 focal ATs (14%), whereas those without included 46 macro-re-entrant ATs (67%), 21 localized-re-entrant ATs (30%), and 2 focal ATs (3%). Multivariable regression identified smaller minimum activated area and larger very low voltage area as independent predictors of P-wave ATs (OR: 0.732; 95% CI: 0.644-0.831; P < 0.001; and OR: 1.042; 95% CI: 1.006-1.080; P = 0.023, respectively). The minimum activated area with the cutoff value of 10 cm2 provided the highest predictive accuracy for P-wave ATs with sensitivity, specificity, and positive and negative predictive values of 96%, 97%, 97%, and 95%, respectively. In re-entrant ATs, smaller minimum activated area was associated with lower minimum conduction velocity within the circuit and fewer areas of delayed conduction outside of the circuit (standardized ß: 0.524; 95% CI: 0.373-0.675; P < 0.001; and standardized ß: 0.353; 95% CI: 0.198-0.508; P < 0.001, respectively). CONCLUSIONS: Reduced atrial activation area and voltage were associated with isoelectric intervals during ATs.

Accuracy of automatic abnormal potential annotation for substrate identification in scar-related ventricular tachycardia.

INTRODUCTION: Ultrahigh-density mapping for ventricular tachycardia (VT) is increasingly used. However, manual annotation of local abnormal ventricular activities (LAVAs) is challenging in this setting. Therefore, we assessed the accuracy of the automatic annotation of LAVAs with the Lumipoint algorithm of the Rhythmia system (Boston Scientific). METHODS AND RESULTS: One hundred consecutive patients undergoing catheter ablation of scar-related VT were studied. Areas with LAVAs and ablation sites were manually annotated during the procedure and compared with automatically annotated areas using the Lumipoint features for detecting late potentials (LP), fragmented potentials (FP), and double potentials (DP). The accuracy of each automatic annotation feature was assessed by re-evaluating local potentials within automatically annotated areas. Automatically annotated areas matched with manually annotated areas in 64 cases (64%), identified an area with LAVAs missed during manual annotation in 15 cases (15%), and did not highlight areas identified with manual annotation in 18 cases (18%). Automatic FP annotation accurately detected LAVAs regardless of the cardiac rhythm or scar location; automatic LP annotation accurately detected LAVAs in sinus rhythm, but was affected by the scar location during ventricular pacing; automatic DP annotation was not affected by the mapping rhythm, but its accuracy was suboptimal when the scar was located on the right ventricle or epicardium. CONCLUSION: The Lumipoint algorithm was as/more accurate than manual annotation in 79% of patients. FP annotation detected LAVAs most accurately regardless of mapping rhythm and scar location. The accuracy of LP and DP annotations varied depending on mapping rhythm or scar location.

Persistent atrial fibrillation ablation in cardiac laminopathy: Electrophysiological findings and clinical outcomes.

BACKGROUND: Little is known about persistent atrial fibrillation (AF) ablation in patients with cardiac laminopathy (CLMNA). OBJECTIVES: We aimed to characterize atrial electrophysiological properties and to assess the long-term outcomes of persistent AF ablation in patients with CLMNA. METHODS: All patients with CLMNA referred in our center for persistent AF ablation were retrospectively included. Left atrial (LA) volume, left atrial appendage (LAA) cycle length, interatrial conduction delay, and LA voltage amplitude were analyzed during the ablation procedure. Sinus rhythm maintenance and LA contractile function were assessed during long-term follow-up. RESULTS: From 2011 to 2020, 8 patients were included. The mean age was 47 ± 14 years, and 3 patients (38%) were women. The LA volume was 205.8 ± 43.7 mL; the LAA AF cycle length was 250.7 ± 85.6 ms; and the interatrial conduction delay was 296.5 ± 110.1 ms. Large low-voltage areas (>50% of the LA surface; <0.5 mV electrogram) were recorded in all 8 patients. Two patients had inadvertent LAA disconnection during ablation. All A waves recorded by pulsed Doppler in sinus rhythm were <30 cm/s before and after AF ablation. Early arrhythmia recurrence was recorded in 7 patients (87%) (time to recurrence 4 ± 4 months; 1.5 procedures per patient). After a mean follow-up of 4.4 ± 3.2 years, 4 patients underwent implantable cardioverter-defibrillator therapy for life-threatening ventricular arrhythmia and 3 patients finally underwent heart transplantation. CONCLUSION: Patients with persistent AF afflicted by CLMNA exhibit severe LA impairment because of large low-voltage areas, prolonged conduction velocity, and reduced contractile function. Ablation procedures have a limited effect with a high recurrence rate.

Electrogram morphology discriminators in implantable cardioverter defibrillators: A comparative evaluation.

BACKGROUND: Morphology algorithms are currently recommended as a standalone discriminator in single-chamber implantable cardioverter defibrillators (ICDs). However, these proprietary algorithms differ in both design and nominal programming. OBJECTIVE: To compare three different algorithms with nominal versus advanced programming in their ability to discriminate between ventricular (VT) and supraventricular tachycardia (SVT). METHODS: In nine European centers, VT and SVTs were collected from Abbott, Boston Scientific, and Medtronic dual- and triple-chamber ICDs via their respective remote monitoring portals. Percentage morphology matches were recorded for selected episodes which were classified as VT or SVT by means of atrioventricular comparison. The sensitivity and related specificity of each manufacturer discriminator was determined at various values of template match percentage from receiving operating characteristics (ROC) curve analysis. RESULTS: A total of 534 episodes were retained for the analysis. In ROC analyses, Abbott Far Field MD (area under the curve [AUC]: 0.91; P < .001) and Boston Scientific RhythmID (AUC: 0.95; P < .001) show higher AUC than Medtronic Wavelet (AUC: 0.81; P < .001) when tested for their ability to discriminate VT from SVT. At nominal % match threshold all devices provided high sensitivity in VT identification, (91%, 100%, and 90%, respectively, for Abbott, Boston Scientific, and Medtronic) but contrasted specificities in SVT discrimination (85%, 41%, and 62%, respectively). Abbott and Medtronic's nominal thresholds were similar to the optimal thresholds. Optimization of the % match threshold improved the Boston Scientific specificity to 79% without compromising the sensitivity. CONCLUSION: Proprietary morphology discriminators show important differences in their ability to discriminate SVT. How much this impact the overall discrimination process remains to be investigated.