Pulsed Field vs Conventional Thermal Ablation for Paroxysmal Atrial Fibrillation: Recurrent Atrial Arrhythmia Burden.

BACKGROUND: The ADVENT randomized trial revealed no significant difference in 1-year freedom from atrial arrhythmias (AA) between thermal (radiofrequency/cryoballoon) and pulsed field ablation (PFA). However, recent studies indicate that the postablation AA burden is a better predictor of clinical outcomes than the dichotomous endpoint of 30-second AA recurrence. OBJECTIVES: The goal of this study was to determine: 1) the impact of postablation AA burden on outcomes; and 2) the effect of ablation modality on AA burden. METHODS: In ADVENT, symptomatic drug-refractory patients with paroxysmal atrial fibrillation underwent PFA or thermal ablation. Postablation transtelephonic electrocardiogram monitor recordings were collected weekly or for symptoms, and 72-hour Holters were at 6 and 12 months. AA burden was calculated from percentage AA on Holters and transtelephonic electrocardiogram monitors. Quality-of-life assessments were at baseline and 12 months. RESULTS: From 593 randomized patients (299 PFA, 294 thermal), using aggregate PFA/thermal data, an AA burden exceeding 0.1% was associated with a significantly reduced quality of life and an increase in clinical interventions: redo ablation, cardioversion, and hospitalization. There were more patients with residual AA burden <0.1% with PFA than thermal ablation (OR: 1.5; 95% CI: 1.0-2.3; P = 0.04). Evaluation of outcomes by baseline demographics revealed that patients with prior failed class I/III antiarrhythmic drugs had less residual AA burden after PFA compared to thermal ablation (OR: 2.5; 95% CI: 1.4-4.3; P = 0.002); patients receiving only class II/IV antiarrhythmic drugs pre-ablation had no difference in AA burden between ablation groups. CONCLUSIONS: Compared with thermal ablation, PFA more often resulted in an AA burden less than the clinically significant threshold of 0.1% burden. (The FARAPULSE ADVENT PIVOTAL Trial PFA System vs SOC Ablation for Paroxysmal Atrial Fibrillation [ADVENT]; NCT04612244).

Artificial intelligence-enhanced electrocardiography derived body mass index as a predictor of future cardiometabolic disease.

The electrocardiogram (ECG) can capture obesity-related cardiac changes. Artificial intelligence-enhanced ECG (AI-ECG) can identify subclinical disease. We trained an AI-ECG model to predict body mass index (BMI) from the ECG alone. Developed from 512,950 12-lead ECGs from the Beth Israel Deaconess Medical Center (BIDMC), a secondary care cohort, and validated on UK Biobank (UKB) (n = 42,386), the model achieved a Pearson correlation coefficient (r) of 0.65 and 0.62, and an R2 of 0.43 and 0.39 in the BIDMC cohort and UK Biobank, respectively for AI-ECG BMI vs. measured BMI. We found delta-BMI, the difference between measured BMI and AI-ECG-predicted BMI (AI-ECG-BMI), to be a biomarker of cardiometabolic health. The top tertile of delta-BMI showed increased risk of future cardiometabolic disease (BIDMC: HR 1.15, p < 0.001; UKB: HR 1.58, p < 0.001) and diabetes mellitus (BIDMC: HR 1.25, p < 0.001; UKB: HR 2.28, p < 0.001) after adjusting for covariates including measured BMI. Significant enhancements in model fit, reclassification and improvements in discriminatory power were observed with the inclusion of delta-BMI in both cohorts. Phenotypic profiling highlighted associations between delta-BMI and cardiometabolic diseases, anthropometric measures of truncal obesity, and pericardial fat mass. Metabolic and proteomic profiling associates delta-BMI positively with valine, lipids in small HDL, syntaxin-3, and carnosine dipeptidase 1, and inversely with glutamine, glycine, colipase, and adiponectin. A genome-wide association study revealed associations with regulators of cardiovascular/metabolic traits, including SCN10A, SCN5A, EXOG and RXRG. In summary, our AI-ECG-BMI model accurately predicts BMI and introduces delta-BMI as a non-invasive biomarker for cardiometabolic risk stratification.

Deep neural networks detect regional wall motion abnormalities and preclinical cardiovascular disease from 12-lead ECGs.

Background: Identifying regional wall motion abnormalities (RWMAs) is critical for diagnosing and risk stratifying patients with cardiovascular disease, particularly ischemic heart disease. We hypothesized that a deep neural network could accurately identify patients with regional wall motion abnormalities from a readily available standard 12-lead electrocardiogram (ECG). Methods: This observational, retrospective study included patients who were treated at Beth Israel Deaconess Medical Center and had an ECG and echocardiogram performed within 14 days of each other between 2008 and 2019. We trained a convolutional neural network to detect the presence of RWMAs, qualitative global right ventricular (RV) hypokinesis, and varying degrees of left ventricular dysfunction (left ventricular ejection fraction [LVEF] ≤50%, LVEF ≤40%, and LVEF ≤35%) identified by echocardiography, using ECG data alone. Patients were randomly split into development (80%) and test sets (20%). Model performance was assessed using area under the receiver operating characteristic curve (AUC). Cox proportional hazard models adjusted for age and sex were performed to estimate the risk of future acute coronary events. Results: The development set consisted of 19,837 patients (mean age 66.7±16.4; 46.7% female) and the test set comprised of 4,953 patients (mean age 67.5±15.8 years; 46.5% female). On the test dataset, the model accurately identified the presence of RWMA, RV hypokinesis, LVEF ≤50%, LVEF ≤40%, and LVEF ≤35% with AUCs of 0.87 (95% CI 0.858-0.882), 0.888 (95% CI 0.878-0.899), 0.923 (95% CI 0.914-0.933), 0.93 (95% CI 0.921-0.939), and 0.876 (95% CI 0.858-0.896), respectively. Among patients with normal biventricular function at the time of the index ECG, those classified as having RMWA by the model were 3 times the risk (age- and sex-adjusted hazard ratio, 2.8; 95% CI 1.9-3.9) for future acute coronary events compared to those classified as negative. Conclusions: We demonstrate that a deep neural network can help identify regional wall motion abnormalities and reduced LV function from a 12-lead ECG and could potentially be used as a screening tool for triaging patients who need either initial or repeat echocardiographic imaging.

Competing risks of monomorphic vs. non-monomorphic ventricular arrhythmias in primary prevention implantable cardioverter-defibrillator recipients: Global Electrical Heterogeneity and Clinical Outcomes (GEHCO) study.

AIMS: Ablation of monomorphic ventricular tachycardia (MMVT) has been shown to reduce shock frequency and improve survival. We aimed to compare cause-specific risk factors for MMVT and polymorphic ventricular tachycardia (PVT)/ventricular fibrillation (VF) and to develop predictive models. METHODS AND RESULTS: The multicentre retrospective cohort study included 2668 patients (age 63.1 ± 13.0 years; 23% female; 78% white; 43% non-ischaemic cardiomyopathy; left ventricular ejection fraction 28.2 ± 11.1%). Cox models were adjusted for demographic characteristics, heart failure severity and treatment, device programming, and electrocardiogram metrics. Global electrical heterogeneity was measured by spatial QRS-T angle (QRSTa), spatial ventricular gradient elevation (SVGel), azimuth, magnitude (SVGmag), and sum absolute QRST integral (SAIQRST). We compared the out-of-sample performance of the lasso and elastic net for Cox proportional hazards and the Fine-Gray competing risk model. During a median follow-up of 4 years, 359 patients experienced their first sustained MMVT with appropriate implantable cardioverter-defibrillator (ICD) therapy, and 129 patients had their first PVT/VF with appropriate ICD shock. The risk of MMVT was associated with wider QRSTa [hazard ratio (HR) 1.16; 95% confidence interval (CI) 1.01-1.34], larger SVGel (HR 1.17; 95% CI 1.05-1.30), and smaller SVGmag (HR 0.74; 95% CI 0.63-0.86) and SAIQRST (HR 0.84; 95% CI 0.71-0.99). The best-performing 3-year competing risk Fine-Gray model for MMVT [time-dependent area under the receiver operating characteristic curve (ROC(t)AUC) 0.728; 95% CI 0.668-0.788] identified high-risk (> 50%) patients with 75% sensitivity and 65% specificity, and PVT/VF prediction model had ROC(t)AUC 0.915 (95% CI 0.868-0.962), both satisfactory calibration. CONCLUSION: We developed and validated models to predict the competing risks of MMVT or PVT/VF that could inform procedural planning and future randomized controlled trials of prophylactic ventricular tachycardia ablation. CLINICAL TRIAL REGISTRATION: URL:www.clinicaltrials.gov Unique identifier:NCT03210883.

The Spatial Ventricular Gradient Is Associated With Inducibility of Ventricular Arrhythmias During Electrophysiology Study.

BACKGROUND: Myocardial electrical heterogeneity is critical for normal cardiac electromechanical function, but abnormal or excessive electrical heterogeneity is proarrhythmic. The spatial ventricular gradient (SVG), a vectorcardiographic measure of electrical heterogeneity, has been associated with arrhythmic events during long-term follow-up, but its relationship with short-term inducibility of ventricular arrhythmias (VAs) is unclear. OBJECTIVE: This study was designed to determine associations between SVG and inducible VAs during electrophysiology study. METHODS: A retrospective study was conducted of adults without prior sustained VA, cardiac arrest, or implantable cardioverter-defibrillator who underwent ventricular stimulation for evaluation of syncope and nonsustained ventricular tachycardia or for risk stratification before primary prevention implantable cardioverter-defibrillator implantation. The 12-lead electrocardiograms were converted into vectorcardiograms, and SVG magnitude (SVGmag) and direction (azimuth and elevation) were calculated. Odds of inducible VA were regressed by logistic models. RESULTS: Of 143 patients (median age, 69 years; 80% male; median left ventricular ejection fraction [LVEF], 47%; 52% myocardial infarction), 34 (23.8%) had inducible VAs. Inducible patients had lower median LVEF (38% vs 50%; P < .0001), smaller SVGmag (29.5 vs 39.4 mV·ms; P = .0099), and smaller cosine SVG azimuth (cosSVGaz; 0.64 vs 0.89; P = .0007). When LVEF, SVGmag, and cosSVGaz were dichotomized at their medians, there was a 39-fold increase in adjusted odds (P = .002) between patients with all low LVEF, SVGmag, and cosSVGaz (65% inducible) compared with patients with all high LVEF, SVGmag, and cosSVGaz (4% [n = 1] inducible). After multivariable adjustment, SVGmag, cosSVGaz, and sex but not LVEF or other characteristics remained associated with inducible VAs. CONCLUSION: Assessment of electrical heterogeneity by SVG, which reflects abnormal electrophysiologic substrate, adds to LVEF and identifies patients at high and low risk of inducible VA at electrophysiology study.

P-wave alternans rebound following pulmonary vein isolation predicts atrial arrhythmia recurrence.

INTRODUCTION: Numerous P-wave indices have been explored as biomarkers to assess atrial fibrillation (AF) risk and the impact of therapy with variable success. OBJECTIVE: We investigated the utility of P-wave alternans (PWA) to track the effects of pulmonary vein isolation (PVI) and to predict atrial arrhythmia recurrence. METHODS: This medical records study included patients who underwent PVI for AF ablation at our institution, along with 20 control subjects without AF or overt cardiovascular disease. PWA was assessed using novel artificial intelligence-enabled modified moving average (AI-MMA) algorithms. PWA was monitored from the 12-lead ECG at ~1 h before and ~16 h after PVI (n = 45) and at the 4- to 17-week clinically indicated follow-up visit (n = 30). The arrhythmia follow-up period was 955 ± 112 days. RESULTS: PVI acutely reduced PWA by 48%-63% (p < .05) to control ranges in leads II, III, aVF, the leads with the greatest sensitivity in monitoring PWA. Pre-ablation PWA was ~6 µV and decreased to ~3 µV following ablation. Patients who exhibited a rebound in PWA to pre-ablation levels at 4- to 17-week follow-up (p < .01) experienced recurrent atrial arrhythmias, whereas patients whose PWA remained reduced (p = .85) did not, resulting in a significant difference (p < .001) at follow-up. The AUC for PWA's prediction of first recurrence of atrial arrhythmia was 0.81 (p < .01) with 88% sensitivity and 82% specificity. Kaplan-Meier analysis estimated atrial arrhythmia-free survival (p < .01) with an adjusted hazard ratio of 3.4 (95% CI: 1.47-5.24, p < .02). CONCLUSION: A rebound in PWA to pre-ablation levels detected by AI-MMA in the 12-lead ECG at standard clinical follow-up predicts atrial arrhythmia recurrence.

Targeting Wavefront Discontinuity Lines for Scar-Related Ventricular Tachycardia Ablation: A Novel Functional Substrate Ablation Approach.

BACKGROUND: The boundaries of critical isthmuses for re-entrant ventricular tachycardia (VT) are formed by wave-front discontinuities (fixed lines of block, slow propagation, and rotational propagation) seen during baseline rhythm. It is unknown whether wavefront discontinuities can be automatically identified and targeted for ablation using electroanatomic mapping systems. OBJECTIVES: The purpose of this study was to assess the electrophysiologic characteristics of automatically projected wavefront discontinuity lines (WADLs) and outcomes of an ablation strategy targeting WADLs in a mixed cohort of VT patients. METHODS: Late activation substrate maps were analyzed from 1 or more baseline rhythm wavefronts. WADLs were identified using the Carto Extended Early Meets Late module. Number, total length, and distance to critical VT sites were measured. VT recurrence and VT-free survival were followed. RESULTS: In total, 49 patients underwent 52 ablations with 71 unique substrate maps analyzed (18.8% epicardial; 62.0% right ventricular paced, 28.2% sinus rhythm, 9.9% left ventricular paced). A total of 28 VT critical sites were identified in 24 patients. WADLs were present in 49 of 71 (69.0%) maps. WADLs were present regardless of cardiomyopathy etiology, mapping wavefront, or surface. At a WADL threshold of 30%, 73.9% of critical VT sites were in close proximity (≤15 mm) to a WADL. VT-free survival was 62% at 1 year, with a competing risk model estimating a 1-year risk of VT recurrence of 23%. CONCLUSIONS: WADLs can be automatically projected in a majority of patients in a mixed cohort of cardiomyopathy etiology, mapped wavefronts, and myocardial surfaces mapped. Targeting WADLs results in low rate of VT recurrence at 1 year.

Recovery and safety with prolonged high-frequency jet ventilation for catheter ablation of atrial fibrillation: A hospital registry study from a New England healthcare network.

STUDY OBJECTIVE: To investigate post-procedural recovery as well as peri-procedural respiratory and hemodynamic safety parameters with prolonged use of high-frequency jet ventilation (HFJV) versus conventional ventilation in patients undergoing catheter ablation for atrial fibrillation. DESIGN: Hospital registry study. SETTING: Tertiary academic teaching hospital in New England. PATIENTS: 1822 patients aged 18 years and older undergoing catheter ablation between January 2013 and June 2020. INTERVENTIONS: HFJV versus conventional mechanical ventilation. MEASUREMENTS: The primary outcome was post-anesthesia care unit (PACU) length of stay. In secondary analyses we assessed the effect of HFJV on intra-procedural hypoxemia, defined as the occurrence of peripheral hemoglobin oxygen saturation (SpO2) <90%, post-procedural respiratory complications (PRC) as well as intra-procedural hypocarbia and hypotension. Multivariable negative binomial and logistic regression analyses, adjusted for patient and procedural characteristics, were applied. MAIN RESULTS: 1157 patients (63%) received HFJV for a median (interquartile range [IQR]) duration of 307 (253-360) minutes. The median (IQR) length of stay in the PACU was 244 (172-370) minutes in patients who underwent ablation with conventional mechanical ventilation and 226 (163-361) minutes in patients receiving HFJV. In adjusted analyses, patients undergoing HFJV had a longer PACU length of stay (adjusted absolute difference: 37.7 min; 95% confidence interval [CI] 9.7-65.8; p = 0.008). There was a higher risk of intra-procedural hypocarbia (adjusted odds ratio [ORadj] 5.90; 95%CI 2.63-13.23; p < 0.001) and hypotension (ORadj 1.88; 95%CI 1.31-2.72; p = 0.001) in patients undergoing HFJV. No association was found between the use of HFJV and intra-procedural hypoxemia or PRC (p = 0.51, and p = 0.97, respectively). CONCLUSION: After confounder adjustment, HFJV for catheter ablation procedures for treatment of atrial fibrillation was associated with a longer length of stay in the PACU. It was further associated with an increased risk of intra-procedural abnormalities including abnormal carbon dioxide homeostasis, as well as intra-procedural arterial hypotension.

The Use of Local Activation Timing Histogram in Ablation of Focal and Re-Entrant Atrial Tachycardias.

BACKGROUND: Activation mapping is often used to differentiate focal from re-entrant arrhythmias. This can be challenging but is critical to ablation success. The local activation time (LAT) histogram, which depicts point distribution over isochronal segments, may help characterize arrhythmia mechanisms and identify an optimal ablation strategy. OBJECTIVES: This study aimed to investigate features of the LAT histogram associated with the focal vs re-entrant mechanism of atrial tachycardias (ATs) and the use of the LAT histogram in the identification of target ablation sites. METHODS: We retrospectively evaluated cases of focal and re-entrant ATs performed at a single academic tertiary care center for which activation mapping was performed using CARTO 3 version 7 software (Biosense Webster). Baseline patient, arrhythmia, and procedural characteristics as well as LAT histogram features were evaluated for each case. LAT histogram-guided ablation targets were also compared against actual ablation sites. RESULTS: Among 52 ATs assessed, 17 were focal, and 35 were re-entrant. Tachycardia cycle length was significantly shorter in re-entrant than in focal ATs (288.2 milliseconds [Q1-Q3: 250-306.5 milliseconds] vs 370 milliseconds [Q1-Q3: 285-400 milliseconds], respectively; P = 0.006). LAT histograms contained more "valleys" in re-entrant than in focal ATs (3 [Q1-Q3: 2-4] vs 1 [Q1-Q3: 1-1]; P < 0.001). No focal ATs contained >2 and no re-entrant ATs contained <1 LAT valley(s). All successful ablation sites correlated with LAT histogram-suggested sites. CONCLUSIONS: LAT histograms can help distinguish focal from re-entrant Ats and identify effective ablation sites.

BRAVEHEART: Open-source software for automated electrocardiographic and vectorcardiographic analysis.

BACKGROUND AND OBJECTIVES: Electrocardiographic (ECG) and vectorcardiographic (VCG) analyses are used to diagnose current cardiovascular disease and for risk stratification for future adverse cardiovascular events. With increasing use of digital ECGs, research into novel ECG/VCG parameters has increased, but widespread computer-based ECG/VCG analysis is limited because there are no currently available, open-source, and easily customizable software packages designed for automated and reproducible analysis. METHODS AND RESULTS: We present BRAVEHEART, an open-source, modular, customizable, and easy to use software package implemented in the MATLAB programming language, for scientific analysis of standard 12-lead ECGs acquired in a digital format. BRAVEHEART accepts a wide variety of digital ECG formats and provides complete and automatic ECG/VCG processing with signal denoising to remove high- and low-frequency artifact, non-dominant beat identification and removal, accurate fiducial point annotation, VCG construction, median beat construction, customizable measurements on median beats, and output of measurements and results in numeric and graphical formats. CONCLUSIONS: The BRAVEHEART software package provides easily customizable scientific analysis of ECGs and VCGs. We hope that making BRAVEHART available will allow other researchers to further the field of ECG/VCG analysis without having to spend significant time and resources developing their own ECG/VCG analysis software and will improve the reproducibility of future studies. Source code, compiled executables, and a detailed user guide can be found at http://github.com/BIVectors/BRAVEHEART. The source code is distributed under the GNU General Public License version 3.

Limits of the spatial ventricular gradient and QRST angles in patients with normal electrocardiograms and no known cardiovascular disease stratified by age, sex, and race.

INTRODUCTION: Measurement of the spatial ventricular gradient (SVG), spatial QRST angles, and other vectorcardiographic measures of myocardial electrical heterogeneity have emerged as novel risk stratification methods for sudden cardiac death and other adverse cardiovascular events. Prior studies of normal limits of these measurements included primarily young, healthy, White volunteers, but normal limits in older patients are unknown. The influence of race and body mass index (BMI) on these measurements is also unclear. METHODS: Normal 12-lead electrocardiograms (ECGs) from a single center were identified. Patients with abnormal cardiovascular, pulmonary, or renal history (assessed by International Classification of Disease [ICD-9/ICD-10] codes) or abnormal cardiovascular imaging were excluded. The SVG and QRST angles were measured and stratified by age, sex, and race. Multivariable linear regression was used to assess the influence of age, BMI, and heart rate (HR) on these measurements. RESULTS: Among 3292 patients, observed ranges of SVG and QRST angles (peak and mean) differed significantly based on sex, age, and race. Sex differences attenuated with increasing age. Men tended to have larger SVG magnitude (60.4 [46.1-77.8] vs. 52.5 [41.3-65.8] mv*ms, p < .0001) and elevation, and more anterior/negative SVG azimuth (-14.8 [-25.1 to -4.3] vs. 1.3 [-9.8 to 10.5] deg, p < .0001) compared to women. Men also had wider QRST angles. Observed ranges varied significantly with BMI and HR. SVG and QRST angle measurements were robust to different filtering bandwidths and moderate fiducial point annotation errors, but were heavily affected by changes in baseline correction. CONCLUSIONS: Age, sex, race, BMI, and HR significantly affect the range of SVG and QRST angles in patients with normal ECGs and no known cardiovascular disease, and should be accounted for in future studies. An online calculator for prediction of these "normal limits" given demographics is provided at https://bivectors.github.io/gehcalc/.

Temporal Trends and Lesion Sets for Persistent Atrial Fibrillation Ablation: A Meta-Analysis With Trial Sequential Analysis and Meta-Regression.

BACKGROUND: Ablation for persistent atrial fibrillation (PsAF) has been performed for over 20 years, although success rates have remained modest. Several adjunctive lesion sets have been studied but none have become standard of practice. We sought to describe how the efficacy of ablation for PsAF has evolved in this time period with a focus on the effect of adjunctive ablation strategies. METHODS: Databases were searched for prospective studies of PsAF ablation. We performed meta-regression and trial sequential analysis. RESULTS: A total of 99 studies (15 424 patients) were included. Ablation for PsAF achieved the primary outcome (freedom of atrial fibrillation/atrial tachycardia rate at 12 months follow-up) in 48.2% (5% CI, 44.0-52.3). Meta-regression showed freedom from atrial arrhythmia at 12 months has improved over time, while procedure time and fluoroscopy time have significantly reduced. Through the use of cumulative meta-analyses and trial sequential analysis, we show that some ablation strategies may initially seem promising, but after several randomized controlled trials may be found to be ineffective. Trial sequential analysis showed that complex fractionated atrial electrogram ablation is ineffective and further study of this treatment would be futile, while posterior wall isolation currently does not have sufficient evidence for routine use in PsAF ablation. CONCLUSIONS: Overall success rates from PsAF ablation and procedure/fluoroscopy times have improved over time. However, no adjunctive lesion set, in addition to pulmonary vein isolation, has been conclusively demonstrated to be beneficial. Through the use of trial sequential analysis, we highlight the importance of adequately powered randomized controlled trials, to avoid reaching premature conclusions, before widespread adoption of novel therapies.

Correlation Between Functional Substrate Mapping and Cardiac Computed Tomography-Derived Wall Thinning for Ventricular Tachycardia Ablation.

BACKGROUND: Functional substrate mapping during baseline rhythm can identify arrhythmogenic tissue during ventricular tachycardia (VT) ablation. Wall thinning and wall thickness channels (WTCs) derived from computed tomography angiography have been shown to correlate with low voltage and VT isthmuses. The correlation between functional substrate mapping, wall thinning, and WTCs in patients with infarct- or non-infarct-related cardiomyopathies (ICM and NICM, respectively) has not been previously described. OBJECTIVES: The purpose of this study was to correlate cardiac CTA-derived myocardial wall thinning with functional VT substrate mapping using isochronal late activation mapping. METHODS: In 34 patients with ICM or NICM undergoing VT ablation who had a preprocedure computed tomography angiography, myocardial wall thinning was segmented in layers of 1 to 5 mm. Areas of wall thinning and WTCs were then spatially correlated with deceleration zones (DZs) from registered left ventricular endocardial isochronal late activation maps. RESULTS: In 21 ICM patients and 13 NICM patients, ICM patients had greater surfaces areas of wall thinning (P < 0.001). In ICM patients, 94.1% of primary DZs were located on areas of wall thinning, compared to 20% of DZs in NICM patients overall but 50% if there was any wall thinning present. Fifty-nine percent of DZs in ICM patients and 56% of DZs in NICM patients were located near WTCs. The positive predictive value for WTC in localizing DZs was 22.5% and 37.8% in ICM and NICM patients, respectively. CONCLUSIONS: Wall thinning is highly sensitive for functional substrate in ICM patients. WTCs had modest sensitivity for functional substrate but low positive predictive value for identifying DZs in ICM and NICM patients. These findings suggest that wall thinning may facilitate more efficient mapping in ICM patients, but WTCs are insufficient to localize wavefront discontinuities.

Individuals with chronic epilepsy have elevated P-wave heterogeneity comparable to patients with atrial fibrillation.

OBJECTIVE: Identification of epilepsy patients with elevated risk for atrial fibrillation (AF) is critical given the heightened morbidity and premature mortality associated with this arrhythmia. Epilepsy is a worldwide health problem affecting nearly 3.4 million people in the United States alone. The potential for increased risk for AF in patients with epilepsy is not well appreciated, despite recent evidence from a national survey of 1.4 million hospitalizations indicating that AF is the most common arrhythmia in people with epilepsy. METHODS: We analyzed inter-lead heterogeneity of P-wave morphology, a marker reflecting arrhythmogenic nonuniformities of activation/conduction in atrial tissue. The study groups consisted of 96 patients with epilepsy and 44 consecutive patients with AF in sinus rhythm before clinically indicated ablation. Individuals without cardiovascular or neurological conditions (n = 77) were also assessed. We calculated P-wave heterogeneity (PWH) by second central moment analysis of simultaneous beats from leads II, III, and aVR ("atrial dedicated leads") from standard 12-lead electrocardiography (ECG) recordings from admission day to the epilepsy monitoring unit (EMU). RESULTS: Female patients composed 62.5%, 59.6%, and 57.1% of the epilepsy, AF, and control subjects, respectively. The AF cohort was older (66 ± 1.1 years) than the epilepsy group (44 ± 1.8 years, p < .001). The level of PWH was greater in the epilepsy group than in the control group (67 ± 2.6 vs. 57 ± 2.5 µV, p = .046) and reached levels observed in AF patients (67 ± 2.6 vs. 68 ± 4.9 µV, p = .99). In multiple linear regression analysis, PWH levels in individuals with epilepsy were mainly correlated with the PR interval and could be related to sympathetic tone. Epilepsy remained associated with PWH after adjustments for cardiac risk factors, age, and sex. SIGNIFICANCE: Patients with chronic epilepsy have increased PWH comparable to levels observed in patients with AF, while being ~20 years younger, suggesting an acceleration in structural change and/or cardiac electrical instability. These observations are consistent with emerging evidence of an "epileptic heart" condition.

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.

A Focus on the Right Atrium: Right Atrial Diverticulum and Atrial Flutter.

We report a case of a 70-year-old woman who presented for a cavotricuspid isthmus atrial flutter ablation that was aborted prematurely. On subsequent imaging, she was discovered to have a right atrial diverticulum, which was present on prior imaging but not reported, likely due to unfamiliarity with the entity. (Level of Difficulty: Intermediate.).

Reduction in atrial and ventricular electrical heterogeneity following pulmonary vein isolation in patients with atrial fibrillation.

BACKGROUND: Pulmonary vein isolation (PVI) modulates the intrinsic cardiac autonomic nervous system and reduces atrial fibrillation (AF) recurrence. METHODS: In this retrospective analysis, we investigated the impact of PVI on ECG interlead P-wave, R-wave, and T-wave heterogeneity (PWH, RWH, TWH) in 45 patients in sinus rhythm undergoing clinically indicated PVI for AF. We measured PWH as a marker of atrial electrical dispersion and AF susceptibility and RWH and TWH as markers of ventricular arrhythmia risk along with standard ECG measures. RESULTS: PVI acutely (16 ± 8.9 h) reduced PWH by 20.7% (from 31 ± 1.9 to 25 ± 1.6 µV, p < 0.001) and TWH by 27% (from 111 ± 7.8 to 81 ± 6.5 µV, p < 0.001). RWH was unchanged after PVI (p = 0.068). In a subgroup of 20 patients with longer follow-up (mean = 47 ± 3.7 days after PVI), PWH remained low (25 ± 1.7 µV, p = 0.01), but TWH partially returned to the pre-ablation level (to 93 ± 10.2, p = 0.16). In three individuals with early recurrence of atrial arrhythmia in the first 3 months after ablation, PWH increased acutely by 8.5%, while in patients without early recurrence, PWH decreased acutely by 22.3% (p = 0.048). PWH was superior to other contemporary P-wave metrics including P-wave axis, dispersion, and duration in predicting early AF recurrence. CONCLUSION: The rapid time course of decreased PWH and TWH after PVI suggests a beneficial influence likely mediated via ablation of the intrinsic cardiac nervous system. Acute responses of PWH and TWH to PVI suggest a favorable dual effect on atrial and ventricular electrical stability and could be used to track individual patients' electrical heterogeneity profile.

The spatial ventricular gradient is associated with adverse outcomes in acute pulmonary embolism.

BACKGROUND: The spatial ventricular gradient (SVG) is a vectorcardiographic measurement that reflects cardiac loading conditions via electromechanical coupling. OBJECTIVES: We hypothesized that the SVG is correlated with right ventricular (RV) strain and is prognostic of adverse events in patients with acute pulmonary embolism (PE). METHODS: Retrospective, single-center study of patients with acute PE. Electrocardiogram (ECG), imaging, and outcome data were obtained. SVG components were regressed on tricuspid annular plane systolic excursion (TAPSE), qualitative RV dysfunction, and RV/left ventricular (LV) ratio. Odds of adverse outcomes (30-day mortality, vasopressor requirement, or advanced therapy) after PE were regressed on demographics, RV/LV ratios, traditional ECG signs of RV dysfunction, and SVG components using a logit model. RESULTS: ECGs from 317 patients (48% male, age 63.1 ± 16.6 years) with acute PE were analyzed; 36 patients (11.4%) experienced an adverse event. Worse RV hypokinesis, larger RV/LV ratio, and smaller TAPSE were associated with smaller SVG X and Y components, larger SVG Z components, and smaller SVG vector magnitude (p < .001 for all). In multivariable logistic regression, odds of adverse events after PE decreased with increasing SVG magnitude and TAPSE (OR 0.32 and 0.54 per standard deviation increase; p = .03 and p = .004, respectively). Receiver operating characteristic (ROC) analysis showed that, when combined with imaging, replacing traditional ECG criteria with the SVG significantly improved the area under the ROC from 0.70 to 0.77 (p = .01). CONCLUSION: The SVG is correlated with RV dysfunction and adverse outcomes in acute PE and has a better prognostic value than traditional ECG markers.