Therapeutic potential of conduction system pacing as a method for improving cardiac output during ventricular tachycardia.

BACKGROUND: Ventricular tachycardia (VT) reduces cardiac output through high heart rates, loss of atrioventricular synchrony, and loss of ventricular synchrony. We studied the contribution of each mechanism and explored the potential therapeutic utility of His bundle pacing to improve cardiac output during VT. METHODS: Study 1 aimed to improve the understanding of mechanisms of harm during VT (using pacing simulated VT). In 23 patients with left ventricular impairment, we recorded continuous ECG and beat-by-beat blood pressure measurements. We assessed the hemodynamic impact of heart rate and restoration of atrial and biventricular synchrony. Study 2 investigated novel pacing interventions during clinical VT by evaluating the hemodynamic effects of His bundle pacing at 5 bpm above the VT rate in 10 patients. RESULTS: In Study 1, at progressively higher rates of simulated VT, systolic blood pressure declined: at rates of 125, 160, and 190 bpm, -22.2%, -42.0%, and -58.7%, respectively (ANOVA p < 0.0001). Restoring atrial synchrony alone had only a modest beneficial effect on systolic blood pressure (+ 3.6% at 160 bpm, p = 0.2117), restoring biventricular synchrony alone had a greater effect (+ 9.1% at 160 bpm, p = 0.242), and simultaneously restoring both significantly increased systolic blood pressure (+ 31.6% at 160 bpm, p = 0.0003). In Study 2, the mean rate of clinical VT was 143 ± 21 bpm. His bundle pacing increased systolic blood pressure by + 14.2% (p = 0.0023). In 6 of 10 patients, VT terminated with His bundle pacing. CONCLUSIONS: Restoring atrial and biventricular synchrony improved hemodynamic function in simulated and clinical VT. Conduction system pacing could improve VT tolerability and treatment.

Machine learning-derived cycle length variability metrics predict spontaneously terminating ventricular tachycardia in implantable cardioverter defibrillator recipients.

Aims: Implantable cardioverter defibrillator (ICD) therapies have been associated with increased mortality and should be minimized when safe to do so. We hypothesized that machine learning-derived ventricular tachycardia (VT) cycle length (CL) variability metrics could be used to discriminate between sustained and spontaneously terminating VT. Methods and results: In this single-centre retrospective study, we analysed data from 69 VT episodes stored on ICDs from 27 patients (36 spontaneously terminating VT, 33 sustained VT). Several VT CL parameters including heart rate variability metrics were calculated. Additionally, a first order auto-regression model was fitted using the first 10 CLs. Using features derived from the first 10 CLs, a random forest classifier was used to predict VT termination. Sustained VT episodes had more stable CLs. Using data from the first 10 CLs only, there was greater CL variability in the spontaneously terminating episodes (mean of standard deviation of first 10 CLs: 20.1 ± 8.9 vs. 11.5 ± 7.8 ms, P < 0.0001). The auto-regression coefficient was significantly greater in spontaneously terminating episodes (mean auto-regression coefficient 0.39 ± 0.32 vs. 0.14 ± 0.39, P < 0.005). A random forest classifier with six features yielded an accuracy of 0.77 (95% confidence interval 0.67 to 0.87) for prediction of VT termination. Conclusion: Ventricular tachycardia CL variability and instability are associated with spontaneously terminating VT and can be used to predict spontaneous VT termination. Given the harmful effects of unnecessary ICD shocks, this machine learning model could be incorporated into ICD algorithms to defer therapies for episodes of VT that are likely to self-terminate.

Characterization of conduction system activation in the postinfarct ventricle using ripple mapping.

BACKGROUND: Three-dimensional (3D) mapping of the ventricular conduction system is challenging. OBJECTIVE: The purpose of this study was to use ripple mapping to distinguish conduction system activation to that of adjacent myocardium in order to characterize the conduction system in the postinfarct left ventricle (LV). METHODS: High-density mapping (PentaRay, CARTO) was performed during normal rhythm in patients undergoing ventricular tachycardia ablation. Ripple maps were viewed from the end of the P wave to QRS onset in 1-ms increments. Clusters of >3 ripple bars were interrogated for the presence of Purkinje potentials, which were tagged on the 3D geometry. Repeating this process allowed conduction system delineation. RESULTS: Maps were reviewed in 24 patients (mean 3112 ± 613 points). There were 150.9 ± 24.5 Purkinje potentials per map, at the left posterior fascicle (LPF) in 22 patients (92%) and at the left anterior fascicle (LAF) in 15 patients (63%). The LAF was shorter (41.4 vs 68.8 mm; P = .0005) and activated for a shorter duration (40.6 vs 64.9 ms; P = .002) than the LPF. Fourteen of 24 patients had left bundle branch block (LBBB), with 11 of 14 (78%) having Purkinje potential-associated breakout. There were fewer breakouts from the conduction system during LBBB (1.8 vs 3.4; 1.6 ± 0.6; P = .039) and an inverse correlation between breakout sites and QRS duration (P = .0035). CONCLUSION: We applied ripple mapping to present a detailed electroanatomic characterization of the conduction system in the postinfarct LV. Patients with broader QRS had fewer LV breakout sites from the conduction system. However, there was 3D mapping evidence of LV breakout from an intact conduction system in the majority of patients with LBBB.

RETRO-mapping: A novel algorithm automating wavefront categorization using activation mapping during persistent atrial fibrillation demonstrates a reduction in wavefront collisions following pulmonary vein isolation.

RETRO-mapping was developed to automate activation mapping of atrial fibrillation (AF). We used the algorithm to study the effect of pulmonary vein isolation (PVI) on the frequency of focal, planar, and colliding wavefronts in persistent AF. An AFocusII catheter was placed on the left atrial endocardium to record 3 s of AF at six sites pre and post-PVI in patients undergoing wide circumferential PVI for persistent AF. RETRO-mapping analyzed each segment in 2 ms time windows for evidence of focal, planar, and colliding waveforms and the automated categorizations manually validated. Ten patients were recruited. A total of 360 s of data in 120 segments of 3 s from 60 left atrial locations were analyzed. RETRO-map was highly effective at identifying focal waves and collisions during AF. PVI significantly reduced collision frequency but not focal and planar activation frequency. However, there was a significant reduction in the dispersion of activation directions. Larger studies may help determine factors associated with successful clinical outcome.

Left atrial appendage occlusion for atrial fibrillation and bleeding diathesis.

BACKGROUND: Patients with atrial fibrillation (AF) and likelihood of bleeding can undergo left atrial appendage occlusion (LAAO) as an alternative method of stroke prophylaxis. Short-term anti-thrombotic drugs are used postprocedure to offset the risk of device-related thrombus, evidence for this practice is limited. OBJECTIVES: To investigate optimal postimplant antithrombotic strategy in high bleeding-risk patients. METHODS: Patients with AF and high-risk for both stroke and bleeding undergoing LAAO were advised their perioperative drug therapy by a multidisciplinary physician panel. Those deemed to be at higher risk of bleeding from anti-thrombotic drugs were assigned to minimal treatment with no antithrombotics or Aspirin-alone. The remaining patients received standard care (STG) with a 12 week course of dual-antiplatelets or anticoagulation postimplant. We compared mortality, device-related thrombus, ischemic stroke, and bleeding events during the 90 days postimplant and long-term. Event-free survival was assessed using Kaplan-Meier survival analysis, with logrank testing for statistical significance. RESULTS: Seventy-five patients underwent LAAO of whom 63 patients (84%) had a prior serious bleeding event. The 42 patients on minimal treatment were older (74.3 ± 7.7 vs. 71.2 ± 7.2) with higher HASBLED score (3.6 ± 0.9 vs. 3.3 ± 1.2) than the 33 patients having standard care. There were no device-related thrombi or strokes in either group at 90 days postprocedure; STG had more bleeding events (5/33 vs. 0/42, p = 0.01) with associated deaths (3/33 vs. 0/42, p = 0.05). During long-term follow-up (median 2.2 years), all patients transitioned onto no antithrombotic drugs (43 patients [61%]) or a single-antiplatelet (29 patients [39%]). There was no evidence of early minimal treatment adversely affecting long-term outcomes. CONCLUSIONS: Short-term anti-thrombotic drugs may not be needed after LAAO implant in patients with high bleeding risk and could be harmful. Larger, prospective studies would be warranted to test these findings.

Left bundle branch pacing with and without anodal capture: impact on ventricular activation pattern and acute haemodynamics.

AIMS: Left bundle branch pacing (LBBP) can deliver physiological left ventricular activation, but typically at the cost of delayed right ventricular (RV) activation. Right ventricular activation can be advanced through anodal capture, but there is uncertainty regarding the mechanism by which this is achieved, and it is not known whether this produces haemodynamic benefit. METHODS AND RESULTS: We recruited patients with LBBP leads in whom anodal capture eliminated the terminal R-wave in lead V1. Ventricular activation pattern, timing, and high-precision acute haemodynamic response were studied during LBBP with and without anodal capture. We recruited 21 patients with a mean age of 67 years, of whom 14 were males. We measured electrocardiogram timings and haemodynamics in all patients, and in 16, we also performed non-invasive mapping. Ventricular epicardial propagation maps demonstrated that RV septal myocardial capture, rather than right bundle capture, was the mechanism for earlier RV activation. With anodal capture, QRS duration and total ventricular activation times were shorter (116 ± 12 vs. 129 ± 14 ms, P < 0.01 and 83 ± 18 vs. 90 ± 15 ms, P = 0.01). This required higher outputs (3.6 ± 1.9 vs. 0.6 ± 0.2 V, P < 0.01) but without additional haemodynamic benefit (mean difference -0.2 ± 3.8 mmHg compared with pacing without anodal capture, P = 0.2). CONCLUSION: Left bundle branch pacing with anodal capture advances RV activation by stimulating the RV septal myocardium. However, this requires higher outputs and does not improve acute haemodynamics. Aiming for anodal capture may therefore not be necessary.

Septal scar as a barrier to left bundle branch area pacing.

BACKGROUND: The use of left bundle branch area pacing (LBBAP) for bradycardia pacing and cardiac resynchronization is increasing, but implants are not always successful. We prospectively studied consecutive patients to determine whether septal scar contributes to implant failure. METHODS: Patients scheduled for bradycardia pacing or cardiac resynchronization therapy were prospectively enrolled. Recruited patients underwent preprocedural scar assessment by cardiac MRI with late gadolinium enhancement imaging. LBBAP was attempted using a lumenless lead (Medtronic 3830) via a transeptal approach. RESULTS: Thirty-five patients were recruited: 29 male, mean age 68 years, 10 ischemic, and 16 non-ischemic cardiomyopathy. Pacing indication was bradycardia in 26% and cardiac resynchronization in 74%. The lead was successfully deployed to the left ventricular septum in 30/35 (86%) and unsuccessful in the remaining 5/35 (14%). Septal late gadolinium enhancement was significantly less extensive in patients where left septal lead deployment was successful, compared those where it was unsuccessful (median 8%, IQR 2%-18% vs. median 54%, IQR 53%-57%, p < .001). CONCLUSIONS: The presence of septal scar appears to make it more challenging to deploy a lead to the left ventricular septum via the transeptal route. Additional implant tools or alternative approaches may be required in patients with extensive septal scar.

Ventricular Conduction Stability Noninvasively Identifies an Arrhythmic Substrate in Survivors of Idiopathic Ventricular Fibrillation.

Background Idiopathic ventricular fibrillation (VF) is a diagnosis of exclusion following normal cardiac investigations. We sought to determine if exercise-induced changes in electrical substrate could distinguish patient groups with various ventricular arrhythmic pathophysiological conditions and identify patients susceptible to VF. Methods and Results Computed tomography and exercise testing in patients wearing a 252-electrode vest were combined to determine ventricular conduction stability between rest and peak exercise, as previously described. Using ventricular conduction stability, conduction heterogeneity in idiopathic VF survivors (n=14) was compared with those surviving VF during acute ischemia with preserved ventricular function following full revascularization (n=10), patients with benign ventricular ectopy (n=11), and patients with normal hearts, no arrhythmic history, and negative Ajmaline challenge during Brugada family screening (Brugada syndrome relatives; n=11). Activation patterns in normal subjects (Brugada syndrome relatives) are preserved following exercise, with mean ventricular conduction stability of 99.2±0.9%. Increased heterogeneity of activation occurred in the idiopathic VF survivors (ventricular conduction stability: 96.9±2.3%) compared with the other groups combined (versus 98.8±1.6%; P=0.001). All groups demonstrated periodic variation in activation heterogeneity (frequency, 0.3-1 Hz), but magnitude was greater in idiopathic VF survivors than Brugada syndrome relatives or patients with ventricular ectopy (7.6±4.1%, 2.9±2.9%, and 2.8±1.2%, respectively). The cause of this periodicity is unknown and was not replicable by introducing exercise-induced noise at comparable frequencies. Conclusions In normal subjects, ventricular activation patterns change little with exercise. In contrast, patients with susceptibility to VF experience activation heterogeneity following exercise that requires further investigation as a testable manifestation of underlying myocardial abnormalities otherwise silent during routine testing.

Artificial intelligence-enabled electrocardiogram to distinguish atrioventricular re-entrant tachycardia from atrioventricular nodal re-entrant tachycardia.

Background: Accurately determining arrhythmia mechanism from a 12-lead electrocardiogram (ECG) of supraventricular tachycardia can be challenging. We hypothesized a convolutional neural network (CNN) can be trained to classify atrioventricular re-entrant tachycardia (AVRT) vs atrioventricular nodal re-entrant tachycardia (AVNRT) from the 12-lead ECG, when using findings from the invasive electrophysiology (EP) study as the gold standard. Methods: We trained a CNN on data from 124 patients undergoing EP studies with a final diagnosis of AVRT or AVNRT. A total of 4962 5-second 12-lead ECG segments were used for training. Each case was labeled AVRT or AVNRT based on the findings of the EP study. The model performance was evaluated against a hold-out test set of 31 patients and compared to an existing manual algorithm. Results: The model had an accuracy of 77.4% in distinguishing between AVRT and AVNRT. The area under the receiver operating characteristic curve was 0.80. In comparison, the existing manual algorithm achieved an accuracy of 67.7% on the same test set. Saliency mapping demonstrated the network used the expected sections of the ECGs for diagnoses; these were the QRS complexes that may contain retrograde P waves. Conclusion: We describe the first neural network trained to differentiate AVRT from AVNRT. Accurate diagnosis of arrhythmia mechanism from a 12-lead ECG could aid preprocedural counseling, consent, and procedure planning. The current accuracy from our neural network is modest but may be improved with a larger training dataset.

Feasibility of mapping and ablating ectopy-triggering ganglionated plexus reproducibly in persistent atrial fibrillation.

BACKGROUND: Ablation of autonomic ectopy-triggering ganglionated plexuses (ET-GP) has been used to treat paroxysmal atrial fibrillation (AF). It is not known if ET-GP localisation is reproducible between different stimulators or whether ET-GP can be mapped and ablated in persistent AF. We tested the reproducibility of the left atrial ET-GP location using different high-frequency high-output stimulators in AF. In addition, we tested the feasibility of identifying ET-GP locations in persistent atrial fibrillation. METHODS: Nine patients undergoing clinically-indicated paroxysmal AF ablation received pacing-synchronised high-frequency stimulation (HFS), delivered in SR during the left atrial refractory period, to compare ET-GP localisation between a custom-built current-controlled stimulator (Tau20) and a voltage-controlled stimulator (Grass S88, SIU5). Two patients with persistent AF underwent cardioversion, left atrial ET-GP mapping with the Tau20 and ablation (Precision™, Tacticath™ [n = 1] or Carto™, SmartTouch™ [n = 1]). Pulmonary vein isolation (PVI) was not performed. Efficacy of ablation at ET-GP sites alone without PVI was assessed at 1 year. RESULTS: The mean output to identify ET-GP was 34 mA (n = 5). Reproducibility of response to synchronised HFS was 100% (Tau20 vs Grass S88; [n = 16] [kappa = 1, SE = 0.00, 95% CI 1 to 1)][Tau20 v Tau20; [n = 13] [kappa = 1, SE = 0, 95% CI 1 to 1]). Two patients with persistent AF had 10 and 7 ET-GP sites identified requiring 6 and 3 min of radiofrequency ablation respectively to abolish ET-GP response. Both patients were free from AF for > 365 days without anti-arrhythmics. CONCLUSIONS: ET-GP sites are identified at the same location by different stimulators. ET-GP ablation alone was able to prevent AF recurrence in persistent AF, and further studies would be warranted.

Comparison of methods for delivering cardiac resynchronization therapy: an acute electrical and haemodynamic within-patient comparison of left bundle branch area, His bundle, and biventricular pacing.

AIMS: Left bundle branch area pacing (LBBAP) is a promising method for delivering cardiac resynchronization therapy (CRT), but its relative physiological effectiveness compared with His bundle pacing (HBP) is unknown. We conducted a within-patient comparison of HBP, LBBAP, and biventricular pacing (BVP). METHODS AND RESULTS: Patients referred for CRT were recruited. We assessed electrical response using non-invasive mapping, and acute haemodynamic response using a high-precision haemodynamic protocol. Nineteen patients were recruited: 14 male, mean LVEF of 30%. Twelve had time for BVP measurements. All three modalities reduced total ventricular activation time (TVAT), (ΔTVATHBP -43 ± 14 ms and ΔTVATLBBAP -35 ± 20 ms vs. ΔTVATBVP -19 ± 30 ms, P = 0.03 and P = 0.1, respectively). HBP produced a significantly greater reduction in TVAT compared with LBBAP in all 19 patients (-46 ± 15 ms, -36 ± 17 ms, P = 0.03). His bundle pacing and LBBAP reduced left ventricular activation time (LVAT) more than BVP (ΔLVATHBP -43 ± 16 ms, P < 0.01 vs. BVP, ΔLVATLBBAP -45 ± 17 ms, P < 0.01 vs. BVP, ΔLVATBVP -13 ± 36 ms), with no difference between HBP and LBBAP (P = 0.65). Acute systolic blood pressure was increased by all three modalities. In the 12 with BVP, greater improvement was seen with HBP and LBBAP (6.4 ± 3.8 mmHg BVP, 8.1 ± 3.8 mmHg HBP, P = 0.02 vs. BVP and 8.4 ± 8.2 mmHg for LBBAP, P = 0.3 vs. BVP), with no difference between HBP and LBBAP (P = 0.8). CONCLUSION: HBP delivered better ventricular resynchronization than LBBAP because right ventricular activation was slower during LBBAP. But LBBAP was not inferior to HBP with respect to LV electrical resynchronization and acute haemodynamic response.

Effects of haemodynamically atrio-ventricular optimized His bundle pacing on heart failure symptoms and exercise capacity: the His Optimized Pacing Evaluated for Heart Failure (HOPE-HF) randomized, double-blind, cross-over trial.

AIMS: Excessive prolongation of PR interval impairs coupling of atrio-ventricular (AV) contraction, which reduces left ventricular pre-load and stroke volume, and worsens symptoms. His bundle pacing allows AV delay shortening while maintaining normal ventricular activation. HOPE-HF evaluated whether AV optimized His pacing is preferable to no-pacing, in a double-blind cross-over fashion, in patients with heart failure, left ventricular ejection fraction (LVEF) ≤40%, PR interval ≥200 ms and either QRS ≤140 ms or right bundle branch block. METHODS AND RESULTS: Patients had atrial and His bundle leads implanted (and an implantable cardioverter-defibrillator lead if clinically indicated) and were randomized to 6 months of pacing and 6 months of no-pacing utilizing a cross-over design. The primary outcome was peak oxygen uptake during symptom-limited exercise. Quality of life, LVEF and patients' holistic symptomatic preference between arms were secondary outcomes. Overall, 167 patients were randomized: 90% men, 69 ± 10 years, QRS duration 124 ± 26 ms, PR interval 249 ± 59 ms, LVEF 33 ± 9%. Neither peak oxygen uptake (+0.25 ml/kg/min, 95% confidence interval [CI] -0.23 to +0.73, p = 0.3) nor LVEF (+0.5%, 95% CI -0.7 to 1.6, p = 0.4) changed with pacing but Minnesota Living with Heart Failure quality of life improved significantly (-3.7, 95% CI -7.1 to -0.3, p = 0.03). Seventy-six percent of patients preferred His bundle pacing-on and 24% pacing-off (p < 0.0001). CONCLUSION: His bundle pacing did not increase peak oxygen uptake but, under double-blind conditions, significantly improved quality of life and was symptomatically preferred by the clear majority of patients. Ventricular pacing delivered via the His bundle did not adversely impact ventricular function during the 6 months.

Cycle Length Evaluation in Persistent Atrial Fibrillation Using Kernel Density Estimation to Identify Transient and Stable Rapid Atrial Activity.

PURPOSE: Left atrial (LA) rapid AF activity has been shown to co-localise with areas of successful atrial fibrillation termination by catheter ablation. We describe a technique that identifies rapid and regular activity. METHODS: Eight-second AF electrograms were recorded from LA regions during ablation for psAF. Local activation was annotated manually on bipolar signals and where these were of poor quality, we inspected unipolar signals. Dominant cycle length (DCL) was calculated from annotation pairs representing a single activation interval, using a probability density function (PDF) with kernel density estimation. Cumulative annotation duration compared to total segment length defined electrogram quality. DCL results were compared to dominant frequency (DF) and averaging. RESULTS: In total 507 8 s AF segments were analysed from 7 patients. Spearman's correlation coefficient was 0.758 between independent annotators (P < 0.001), 0.837-0.94 between 8 s and ≥ 4 s segments (P < 0.001), 0.541 between DCL and DF (P < 0.001), and 0.79 between DCL and averaging (P < 0.001). Poorer segment organization gave greater errors between DCL and DF. CONCLUSION: DCL identifies rapid atrial activity that may represent psAF drivers. This study uses DCL as a tool to evaluate the dynamic, patient specific properties of psAF by identifying rapid and regular activity. If automated, this technique could rapidly identify areas for ablation in psAF.

Ectopy-triggering ganglionated plexuses ablation to prevent atrial fibrillation: GANGLIA-AF study.

BACKGROUND: The ganglionated plexuses (GPs) of the intrinsic cardiac autonomic system may play a role in atrial fibrillation (AF). OBJECTIVE: We hypothesized that ablating the ectopy-triggering GPs (ET-GPs) prevents AF. METHODS: GANGLIA-AF (ClinicalTrials.gov identifier NCT02487654) was a prospective, randomized, controlled, 3-center trial. ET-GPs were mapped using high frequency stimulation, delivered within the atrial refractory period and ablated until nonfunctional. If triggered AF became incessant, atrioventricular dissociating GPs were ablated. We compared GP ablation (GPA) without pulmonary vein isolation (PVI) against PVI in patients with paroxysmal AF. Follow-up was for 12 months including 3-monthly 48-hour Holter monitors. The primary end point was documented ≥30 seconds of atrial arrhythmia after a 3-month blanking period. RESULTS: A total of 102 randomized patients were analyzed on a per-protocol basis after GPA (n = 52; 51%) or PVI (n = 50; 49%). Patients who underwent GPA had 89 ± 26 high frequency stimulation sites tested, identifying a median of 18.5% (interquartile range 16%-21%) of GPs. The radiofrequency ablation time was 22.9 ± 9.8 minutes in GPA and 38 ± 14.4 minutes in PVI (P < .0001). The freedom from ≥30 seconds of atrial arrhythmia at 12-month follow-up was 50% (26 of 52) with GPA vs 64% (32 of 50) with PVI (log-rank, P = .09). ET-GPA without atrioventricular dissociating GPA achieved 58% (22 of 38) freedom from the primary end point. There was a significantly higher reduction in antiarrhythmic drug usage postablation after GPA than after PVI (55.5% vs 36%; P = .05). Patients were referred for redo ablation procedures in 31% (16 of 52) after GPA and 24% (12 of 50) after PVI (P = .53). CONCLUSION: GPA did not prevent atrial arrhythmias more than PVI. However, less radiofrequency ablation was delivered to achieve a higher reduction in antiarrhythmic drug usage with GPA than with PVI.

Artificial intelligence-enabled electrocardiogram to distinguish cavotricuspid isthmus dependence from other atrial tachycardia mechanisms.

Aims: Accurately determining atrial arrhythmia mechanisms from a 12-lead electrocardiogram (ECG) can be challenging. Given the high success rate of cavotricuspid isthmus (CTI) ablation, identification of CTI-dependent typical atrial flutter (AFL) is important for treatment decisions and procedure planning. We sought to train a convolutional neural network (CNN) to classify CTI-dependent AFL vs. non-CTI dependent atrial tachycardia (AT), using data from the invasive electrophysiology (EP) study as the gold standard. Methods and results: We trained a CNN on data from 231 patients undergoing EP studies for atrial tachyarrhythmia. A total of 13 500 five-second 12-lead ECG segments were used for training. Each case was labelled CTI-dependent AFL or non-CTI-dependent AT based on the findings of the EP study. The model performance was evaluated against a test set of 57 patients. A survey of electrophysiologists in Europe was undertaken on the same 57 ECGs. The model had an accuracy of 86% (95% CI 0.77-0.95) compared to median expert electrophysiologist accuracy of 79% (range 70-84%). In the two thirds of test set cases (38/57) where both the model and electrophysiologist consensus were in agreement, the prediction accuracy was 100%. Saliency mapping demonstrated atrial activation was the most important segment of the ECG for determining model output. Conclusion: We describe the first CNN trained to differentiate CTI-dependent AFL from other AT using the ECG. Our model matched and complemented expert electrophysiologist performance. Automated artificial intelligence-enhanced ECG analysis could help guide treatment decisions and plan ablation procedures for patients with organized atrial arrhythmias.

Classification of Fibrillation Organisation Using Electrocardiograms to Guide Mechanism-Directed Treatments.

Background: Atrial fibrillation (AF) and ventricular fibrillation (VF) are complex heart rhythm disorders and may be sustained by distinct electrophysiological mechanisms. Disorganised self-perpetuating multiple-wavelets and organised rotational drivers (RDs) localising to specific areas are both possible mechanisms by which fibrillation is sustained. Determining the underlying mechanisms of fibrillation may be helpful in tailoring treatment strategies. We investigated whether global fibrillation organisation, a surrogate for fibrillation mechanism, can be determined from electrocardiograms (ECGs) using band-power (BP) feature analysis and machine learning. Methods: In this study, we proposed a novel ECG classification framework to differentiate fibrillation organisation levels. BP features were derived from surface ECGs and fed to a linear discriminant analysis classifier to predict fibrillation organisation level. Two datasets, single-channel ECGs of rat VF (n = 9) and 12-lead ECGs of human AF (n = 17), were used for model evaluation in a leave-one-out (LOO) manner. Results: The proposed method correctly predicted the organisation level from rat VF ECG with the sensitivity of 75%, specificity of 80%, and accuracy of 78%, and from clinical AF ECG with the sensitivity of 80%, specificity of 92%, and accuracy of 88%. Conclusion: Our proposed method can distinguish between AF/VF of different global organisation levels non-invasively from the ECG alone. This may aid in patient selection and guiding mechanism-directed tailored treatment strategies.

A Multicenter External Validation of a Score Model to Predict Risk of Events in Patients With Brugada Syndrome.

A multivariate risk score model was proposed by Sieira et al in 2017 for sudden death in Brugada syndrome; their validation in 150 patients was highly encouraging, with a C-index of 0.81; however, this score is yet to be validated by an independent group. A total of 192 records of patients with Brugada syndrome were collected from 2 centers in the United Kingdom and retrospectively scored according to a score model by Sieira et al. Data were compiled summatively over follow-up to mimic regular risk re-evaluation as per current guidelines. Sudden cardiac death survivor data were considered perievent to ascertain the utility of the score before cardiac arrest. Scores were compared with actual outcomes. Sensitivity in our cohort was 22.7%, specificity was 57.6%, and C-index was 0.58. In conclusion, up to 75% of cardiac arrest survivors in this cohort would not have been offered a defibrillator if evaluated before their event. This casts doubt on the utility of the score model for primary prevention of sudden death. Inherent issues with modern risk scoring strategies decrease the likelihood of success even in robustly designed tools such as the Sieira score model.

Left ventricular activation time and pattern are preserved with both selective and nonselective His bundle pacing.

BACKGROUND: His bundle pacing (HBP) can be achieved in 2 ways: selective HBP (S-HBP), where the His bundle is captured alone, and nonselective HBP (NS-HBP), where local myocardium is also captured, resulting a pre-excited electrocardiogram appearance. OBJECTIVE: We assessed the impact of this ventricular pre-excitation on left and right ventricular dyssynchrony. METHODS: We recruited patients who displayed both S-HBP and NS-HBP. We performed noninvasive epicardial electrical mapping for left and right ventricular activation time (LVAT and RVAT) and pattern. RESULTS: Twenty patients were recruited. In the primary analysis, the mean within-patient change in LVAT from S-HBP to NS-HBP was -5.5 ms (95% confidence interval: -0.6 to -10.4, noninferiority P < .0001). NS-HBP did not prolong RVAT (4.3 ms, -4.0 to 12.8, P = .296) but did prolong QRS duration (QRSd, 22.1 ms, 11.8 to 32.4, P = .0003). In patients with narrow intrinsic QRS (n = 6), NS-HBP preserved LVAT (-2.9 ms, -9.7 to 4.0, P = .331) but prolonged QRS duration (31.4 ms, 22.0 to 40.7, P = .0003) and mean RVAT (16.8 ms, -5.3 to 38.9, P = .108) compared to S-HBP. Activation pattern of the left ventricular surface was unchanged between S-HBP and NS-HBP, but NS-HBP produced early basal right ventricular activation that was not seen in S-HBP. CONCLUSION: Compared to S-HBP, local myocardial capture during NS-HBP produces pre-excitation of the basal right ventricle resulting in QRS duration prolongation. However, NS-HBP preserves the left ventricular activation time and pattern of S-HBP. Left ventricular dyssynchrony is not an important factor when choosing between S-HBP and NS-HBP in most patients.

Postinfarct ventricular tachycardia substrate: Characterization and ablation of conduction channels using ripple mapping.

BACKGROUND: Conduction channels have been demonstrated within the postinfarct scar and seem to be co-located with the isthmus of ventricular tachycardia (VT). Mapping the local scar potentials (SPs) that define the conduction channels is often hindered by large far-field electrograms generated by healthy myocardium. OBJECTIVE: The purpose of this study was to map conduction channel using ripple mapping to categorize SPs temporally and anatomically. We tested the hypothesis that ablation of early SPs would eliminate the latest SPs without direct ablation. METHODS: Ripple maps of postinfarct scar were collected using the PentaRay (Biosense Webster) during normal rhythm. Maps were reviewed in reverse, and clusters of SPs were color-coded on the geometry, by timing, into early, intermediate, late, and terminal. Ablation was delivered sequentially from clusters of early SPs, checking for loss of terminal SPs as the endpoint. RESULTS: The protocol was performed in 11 patients. Mean mapping time was 65 ± 23 minutes, and a mean 3050 ± 1839 points was collected. SP timing ranged from 98.1 ± 60.5 ms to 214.8 ± 89.8 ms post QRS peak. Earliest SPs were present at the border, occupying 16.4% of scar, whereas latest SPs occupied 4.8% at the opposing border or core. Analysis took 15 ± 10 minutes to locate channels and identify ablation targets. It was possible to eliminate latest SPs in all patients without direct ablation (mean ablation time 16.3 ± 11.1 minutes). No VT recurrence was recorded (mean follow-up 10.1 ± 7.4 months). CONCLUSION: Conduction channels can be located using ripple mapping to analyze SPs. Ablation at channel entrances can eliminate the latest SPs and is associated with good medium-term results.

RETRO-MAPPING: A New Approach to Activation Mapping in Persistent Atrial Fibrillation Reveals Evidence of Spatiotemporal Stability.

[Figure: see text].