BACKGROUND:Conduction system pacing (CSP) is an emerging alternative modality of cardiac resynchronization therapy (CRT). However, not all patients obtain electrical resynchronization with CSP, there is a clinical need for reliable non-invasive predictors of response. We aimed to assess the ability of several non-invasive modalities to predict electrical resynchronization with CSP-CRT. METHODS:Patients with standard heart failure CRT indications (excluding right-bundle branch block) underwent CSP-CRT using His-bundle and left-bundle branch pacing. Electrical resynchronization was defined as a >10 ms reduction in left ventricular activation time or conversion to a physiological left ventricular activation pattern on non-invasive multi-electrode mapping. We assessed whether 12-lead ECG morphology, vector electrocardiogram (VCG) derived QRS area, Ultra High Frequency (UHF)-ECG parameters or MRI scar burden predicted electrical resynchronization. RESULTS:Thirty four patients were analyzed (mean age 69±10 years; 82% male; LVEF 30±6%; QRS duration 161±23 ms; 32% ischemic cardiomyopathy). Electrical resynchronization was achieved in 24/34 (71%; 95%CI 53-85). Strauss criteria positivity on 12-lead ECG yielded a positive predictive value (PPV) of 83% (95%CI 61-95%) and negative predictive value (NPV) of 55% (95%CI 23-83%). VCG QRS area >100µVs demonstrated PPV 100% (95% CI 81-100%) and NPV 73% (95%CI 85-100%). UHF-ECG e-DYS >50 ms gave PPV 93% (95%CI 66-100%) and NPV 47% (23%-72%); >60 ms gave PPV 90% (95%CI 66-100%) and NPV 38% (95%CI 18-62%). MRI scar burden <15% resulted in PPV 88% (95%CI 64-99%) and NPV 56% (95%CI 21-86%). Lines of propagation discontinuity on multi-electrode mapping showed PPV 100% (95%CI 85-100%) and NPV 83% (95%CI 52-98%). CONCLUSIONS:Multiple non-invasive markers, including QRS morphology, VCG QRS area, UHF-ECG e-DYS, MRI scar burden showed potential to identify patients who are likely to electrically resynchronize with CSP-CRT, although their NPVs were generally modest. Non-invasive propagation mapping had the highest PPV and NPV.

BACKGROUND:Left ventricular outflow obstruction drives symptoms and outcomes in obstructive hypertrophic cardiomyopathy (oHCM). Right ventricular pacing (RVP) can desynchronize the left ventricle to relieve this and allows control of atrioventricular delay (AVD) but may impair ventricular function. We used high-precision assessment to quantify the hemodynamic and echocardiographic effects of RVP in oHCM. METHODS:Patients with oHCM and implanted dual-chamber pacing devices underwent continuous recording of ECG, beat-by-beat outflow tract continuous wave Doppler, and beat-by-beat, noninvasive finger-cuff blood pressure while pacing was alternated between atrium-only pacing and AV-sequential RVP at a range of AVDs at 5 bpm above resting heart rate and 100 bpm. Changes in systolic blood pressure (∆SBP) and left ventricular outflow tract gradient (∆LVOTg) were fitted to parabolas to produce reproducible, narrow confidence interval estimates of effects. RESULTS:Twenty two patients were recruited (60% male, mean resting LVOTg 53 mmHg). At just above resting heart rate (mean 75 bpm), RVP produced mean peak ∆SBP from AAI to DDD of 2.47 mmHg (95% confidence interval: 0.19-4.76, p = 0.04). The mean AVD for peak ∆SBP was 173.2 ms. Mean LVOTg reduction at this AVD was 8.31 mmHg (2.43-14.18, p < 0.001). Apart from the hemodynamically optimum AVD, no other AVDs produced statistically significant increases in SBP. At 100 bpm, greater increases in SBP and reductions in LVOTg were seen at hemodynamically optimal AVD. CONCLUSION:Multiple alternation assessment allows precise, reproducible, narrow confidence interval quantification of hemodynamic and echocardiographic pacing effects. RVP can reduce LVOTg while preserving or improving cardiac output, but AVD is a key modifier of this relationship.

INTRODUCTION:Electrical activity in atrial fibrillation (AF) ranges from organized focal drivers to multiple wavelet re-entry. Understanding the effect of pulmonary vein isolation (PVI) on AF organization is clinically important, as it may optimize treatment strategies and outcomes. This study investigates the impact of PVI on AF organization and explores whether ventricular response regularity, measured from surface electrocardiograms (ECGs), reflects AF dynamics and electrophenotype. METHODS:Patients undergoing first-time PVI at Imperial College Healthcare NHS Trust between 2014 and 2022 were assessed pre- and post-PVI. AF organization was quantified using Shannon entropy (ShEn) and Sample entropy (SampEn) from coronary sinus (CS) electrograms. Ventricular response regularity was evaluated using surface ECG RR interval (RRI) variability and SampEn. RESULTS:PVI reduced ShEn and SampEn across all CS channels (e.g., SampEn CS 3-4: pre-ablation = 0.907 ± 0.512 vs. post-ablation = 0.790 ± 0.446, p < 0.001). Atrial ShEn and SampEn were correlated with ventricular response both pre- and post-ablation (e.g., correlations between atrial SampEn CS 3-4 and the following ventricular metrics: percentage of RRIs > 50 ms difference: r = 0.077, p = 0.008; normalized mean RRI difference: r = 0.144, p < 0.001; and normalized SampEn: r = 0.168, p < 0.001). CONCLUSION:The reduction in atrial ShEn and SampEn post-PVI indicates increased AF organization. The significant correlation between atrial entropy and ventricular variability suggests that AF organization affects ventricular response, assessed via surface ECG metrics. These findings highlight the potential of ECG-based measures as proxies for intracardiac AF organization.

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.

Introduction: Patients with hypertrophic cardiomyopathy (HCM) are at risk for lethal ventricular arrhythmia, but the electrophysiological substrate behind this is not well-understood. We used non-invasive electrocardiographic imaging to characterize patients with HCM, including cardiac arrest survivors.Methods: HCM patients surviving ventricular fibrillation or hemodynamically unstable ventricular tachycardia (n = 17) were compared to HCM patients without a personal history of potentially lethal arrhythmia (n = 20) and a pooled control group with structurally normal hearts. Subjects underwent exercise testing by non-invasive electrocardiographic imaging to estimate epicardial electrophysiology.Results: Visual inspection of reconstructed epicardial HCM maps revealed isolated patches of late activation time (AT), prolonged activation-recovery intervals (ARIs), as well as reversal of apico-basal trends in T-wave inversion and ARI compared to controls (p < 0.005 for all). AT and ARI were compared between groups. The pooled HCM group had longer mean AT (60.1 ms vs. 52.2 ms, p < 0.001), activation dispersion (55.2 ms vs. 48.6 ms, p = 0.026), and mean ARI (227 ms vs. 217 ms, p = 0.016) than structurally normal heart controls. HCM ventricular arrhythmia survivors could be differentiated from HCM patients without a personal history of life-threatening arrhythmia by longer mean AT (63.2 ms vs. 57.4 ms, p = 0.007), steeper activation gradients (0.45 ms/mm vs. 0.36 ms/mm, p = 0.011), and longer mean ARI (234.0 ms vs. 221.4 ms, p = 0.026). A logistic regression model including whole heart mean activation time and activation recovery interval could identify ventricular arrhythmia survivors from the HCM cohort, producing a C statistic of 0.76 (95% confidence interval 0.72–0.81), with an optimal sensitivity of 78.6% and a specificity of 79.8%.Discussion: The HCM epicardial electrotype is characterized by delayed, dispersed conduction and prolonged, dispersed activation-recovery intervals. Combination of electrophysiologic measures with logistic regression can improve differentiation over single variables. Future studies could test such models prospectively for risk stratification of sudden death due to HCM.

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. 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. In Study 1, at progressively higher rates of simulated VT, systolic blood pressure declined: at rates of 125, 160, and 190 bpm, -22.2

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.

Abstract Funding Acknowledgements Type of funding sources: Foundation. Main funding source(s): British Heart Foundation Introduction Cardiac resynchronisation therapy (CRT) in the form of His bundle CRT and left bundle area CRT can be more effective than the gold standard, biventricular pacing (BVP). In BVP scar burden is known to predict response whether this is true for these novel modalities is not known. Purpose The purpose of this study was to determine whether left ventricular scar burden assessed using cardiac MRI can be used to predict the electrical and acute haemodynamic response to two novel CRT modalities. Methods Patients with standard CRT indications were recruited. They underwent a pre-procedure cardiac MRI, with late gadolinium enhancement (LGE) to quantify scar. His bundle CRT (His CRT) and left bundle area CRT (LBA CRT) were attempted. The electrical response was measured using high precision non-invasive mapping ECGi (CardioInsight, Medtronic). The haemodynamic response was measured with a high precision protocol. We investigated the impact of scar and baseline electrical characteristic on ECGi and haemodynamic response. Results 26 patients were recruited (85% male, mean age 69 ± 10, with ischaemic cardiomyopathy in 35%). LGE was observed in 96% of cases and the mean (range 1-39%). We found a significant correlation between scar extent and the electrical response with both modalities. There was a significant correlation between a lower scar burden and better electrical response. For His CRT the reduction in left ventricular activation time was better with lower scar burden (R= 0.77, p < 0.01, Picture 1), for LBA CRT for reduction in left ventricular activation was also better with lower scar burden (R = 0.53, p = 0.05, Picture 2). With His CRT there was also a significant correlation between lower scar extent and better acute haemodynamic response ( R = 0.6, p = 0.002) but this was not observed with LBA CRT (R = 0.07, p = 0.77). Conclusion Left ventricular myocardial scar can be used to predict the electrical response to two different conduction system CRT modalities.

Abstract Background Atrial fibrillation (AF) is characterised by an irregularly irregular ventricular rhythm. However, the mechanisms by which the regularity of ventricular response is influenced by AF dynamics is yet to be understood. In AF, there is a spectrum of organisation of atrial electrical activity; from organised AF sustained by focal drivers through to disorganised AF sustained by multiple wavelet re-entry. We aimed to investigate whether the ventricular response in AF was associated with the organisation of atrial electrical activity, with the hypothesis that AF organisation correlates with ventricular response regularity. Methods We retrospectively reviewed data from 239 patients with persistent AF undergoing pulmonary vein isolation (PVI). In each patient both before and after ablation, AF organisation and measures of ventricular variability and irregularity were evaluated in 50s segments. Shannon entropy (ShEn) and Sample entropy (SampEn) derived from coronary sinus (CS) atrial electrograms were used to assess AF organisation. RR interval (RRI) metrics derived from the surface ECG were used to determine ventricular variability and irregularity. RRI variability was evaluated using the time-domain measures: normalised mean RRI difference, standard deviation of RRIs (SD RRI), normalised SD RRI, root mean square of successive RRI differences (rMSSD) and percentage of successive RR intervals that differ from each other by more than 50ms (pNN50). RRI irregularity was measured using SampEn and normalised SampEn. Results A significant decrease in atrial ShEn and SampEn was observed following PVI across all CS channels (e.g. SampEn CS 3-4: pre-ablation=0.907±0.512 vs post-ablation=0.790±0.447, p<0.0001). Both ShEn and SampEn from CS atrial electrograms were significantly correlated with the RRI variability and irregularity measures from surface ECG (pNN50, normalised mean RRI difference, normalised SD RRI and normalised SampEn) both pre- and post-ablation (pNN50: r=0.0771, p=0.00838, Figure 1; normalised mean RRI difference: r=0.144, p<0.0001; normalised SD RRI: r=0.175, p<0.0001; normalised SampEn: r=0.168, p<0.0001; correlations with SampEn CS 3-4 pre-ablation shown). Conclusion The reduction in atrial ShEn and SampEn following PVI suggests that an increase in AF organisation occurs with PVI. The significant correlations between atrial entropy and measures of RRI variability and irregularity suggest that AF organisation impacts ventricular response regularity. Therefore, interpretation of the RRI variability and irregularity from the surface ECG may give some insight, non-invasively, into the level of AF organisation.Figure 1

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.

AbstractAimsLeft 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 resultsPatients 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).ConclusionHBP 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.

Background Guidelines support upgrade to cardiac resynchronization therapy (CRT) through His-bundle pacing (HBP) in pacing-induced cardiomyopathy and moderate left ventricular systolic dysfunction (LVSD). Lead-related venous occlusion can represent an obstacle to upgrade procedures. We describe a technique to overcome venous occlusion through direct puncture of a collateral vein facilitating upgrade to HBP. Case summary An 84-year-old man with a right ventricular (RV) pacemaker was referred with New York Heart Association (NYHA) Class III breathlessness secondary to moderate LVSD (left ventricular ejection fraction [LVEF] 45%). Device interrogation revealed 100% RV pacing and AV-dyssynchrony. To optimize atrioventricular (AV) and interventricular (VV) synchrony a CRT upgrade with HBP was planned. Venography revealed an occluded left subclavian vein which was probed in a retrograde manner using a 6F MPA catheter from right femoral venous access. We were able to direct the catheter distal to the left brachio-cephalic vein and define the occlusion using contrast. A collateral branch was identified, a J-wire was left in this branch and venous access was secured at this medial subclavian site using the Seldinger technique. A right atrial lead was deployed and 69 cm ISI-1 His lead was deployed via a C315 sheath at the His-bundle. The resulted in non-selective HBP (Stim-QRS end 146 ms). There were no procedural complications. Two months later both symptoms and LV function (LVEF 55%) improved. Discussion Lead-related venous occlusion occurs frequently and can be probed in a retrograde manner from femoral venous access using contrast, facilitating direct percutaneous puncture of collateral venous branches to allow upgrade to CRT via HBP.

Abstract 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.

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.

Hereditary haemorrhagic telangiectasia (HHT) is a complex, multisystemic vascular dysplasia affecting approximately 85,000 European Citizens. In 2016, eight founding centres operating within 6 countries, set up a working group dedicated to HHT within what became the European Reference Network on Rare Multisystemic Vascular Diseases. By launch, combined experience exceeded 10,000 HHT patients, and Chairs representing 7 separate specialties provided a median of 24 years' experience in HHT. Integrated were expert patients who focused discussions on the patient experience. Following a 2016-2017 survey to capture priorities, and underpinned by more than 40 monthly meetings, and new data acquisitions, VASCERN HHT generated position statements that distinguish expert HHT care from non-expert HHT practice. Leadership was by specialists in the relevant sub-discipline(s), and 100% consensus was required amongst all clinicians before statements were published or disseminated. One major set of outputs targeted all healthcare professionals and their HHT patients, and include the new Orphanet definition; Do's and Don'ts for common situations; Outcome Measures suitable for all consultations; COVID-19; and anticoagulation. The second output set span aspects of vascular pathophysiology where greater understanding will assist organ-specific specialist clinicians to provide more informed care to HHT patients. These cover cerebral vascular malformations and screening; mucocutaneous telangiectasia and differential diagnosis; anti-angiogenic therapies; circulatory interplays between anaemia and arteriovenous malformations; and microbiological strategies to counteract loss of normal pulmonary capillary function. Overall, the integrated outputs, and documented current practices, provide frameworks for approaches that augment the health and safety of HHT patients in diverse health-care settings.

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.

Background Left bundle area pacing is growing in use both for bradycardia pacing and cardiac resynchronization, but implants are not always successful. We prospectively studied consecutive patients to determine whether septal scar contributes to implant failure. Methods Patients scheduled for left bundle area pacing, using the 3830 Selectsecure lead were prospectively enrolled. All patients underwent standardized scar assessment by cardiac MRI with late gadolinium enhancement imaging. Scar burden was quantified as the proportion of basal septal segments showing late enhancement. Results 35 patients were recruited: 29 male, mean age 68 years, 10 with ischemic and 16 with dilated cardiomyopathy. Pacing indication was bradycardia in 26% and cardiac resynchronization in 74%. In 5/35 (14%) it was not possible to advance the lead through the ventricular septum. Basal septal late gadolinium enhancement was significantly more extensive in these patients (median 67%, IQR 58-69.5) compared to the other 30 (median 10%, IQR 0-20, p = 0.0006). There was no significant correlation between the paced QRS duration achieved and the extent of basal septal scar (r = 0.06, P = 0.75). Conclusions Failure to deliver a lead to the left bundle area is strongly associated with a (very) high burden of scar in the basal septum. Once the lead is delivered, however, the electrical response is independent of scar burden. This suggests that it would be worth developing delivery tools to tackle scarred basal septa, because if the lead could be delivered the electrical capture might still achieve a narrow QRS.

We present a case of pacing-induced cardiomyopathy and an occluded left subclavian vein (SCV). The SCV occlusion was delineated in a retrograde manner from femoral venous access and bypassed through direct puncture of a collateral branch. Cardiac resynchronisation therapy was achieved through His bundle pacing, with subsequent normalisation of LV function.

The use of Left bundle area pacing is rapidly growing for both bradycardia and CRT indications. It offers physiological activation of the left ventricle, but right ventricular activation may be delayed. It is often possible to shorten QRS duration and eliminate the R wave in V1 by adjusting pacing output and/or configuration. It is not clear whether the reduction in QRS occurs as a result of bi-bundle capture or due to RV septal capture and it is not known whether programming this configuration offers an advantage in cardiac function.