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Background: Adaptive cardiac resynchronization therapy (aCRT) is known to have clinical benefits over conventional CRT, but the mechanisms are unclear., Objective: Compare effects of aCRT and conventional CRT on electrical dyssynchrony., Methods: A prospective, double-blind, 1:1 parallel-group assignment randomized controlled trial in patients receiving CRT for routine clinical indications. Participants underwent cardiac computed tomography and 128-electrode body surface mapping. The primary outcome was change in electrical dyssynchrony measured on the epicardial surface using noninvasive electrocardiographic imaging before and 6 months post-CRT. Ventricular electrical uncoupling (VEU) was calculated as the difference between the mean left ventricular (LV) and right ventricular (RV) activation times. An electrical dyssynchrony index (EDI) was computed as the standard deviation of local epicardial activation times., Results: We randomized 27 participants (aged 64 ± 12 years; 34% female; 53% ischemic cardiomyopathy; LV ejection fraction 28% ± 8%; QRS duration 155 ± 21 ms; typical left bundle branch block [LBBB] in 13%) to conventional CRT (n = 15) vs aCRT (n = 12). In atypical LBBB (n = 11; 41%) with S waves in V 5 -V 6 , conduction block occurred in the anterior RV, as opposed to the interventricular groove in strict LBBB. As compared to baseline, VEU reduced post-CRT in the aCRT (median reduction 18.9 [interquartile range 4.3-29.2 ms; P = .034]), but not in the conventional CRT (21.4 [-30.0 to 49.9 ms; P = .525]) group. There were no differences in the degree of change in VEU and EDI indices between treatment groups., Conclusion: The effect of aCRT and conventional CRT on electrical dyssynchrony is largely similar, but only aCRT harmoniously reduced interventricular dyssynchrony by reducing RV uncoupling., (© 2021 Heart Rhythm Society. Published by Elsevier Inc.)

Objectives: We hypothesised that (1) the prevalent cardiovascular disease (CVD) is associated with global electrical heterogeneity (GEH) after adjustment for demographic, anthropometric, socioeconomic and traditional cardiovascular risk factors, (2) there are sex differences in GEH and (3) sex modifies an association of prevalent CVD with GEH., Design: Cross-sectional, cohort study., Setting: Prospective African-American The Jackson Heart Study (JHS) with a nested family cohort in 2000-2004 enrolled residents of the Jackson, Mississippi metropolitan area., Participants: Participants from the JHS with analysable ECGs recorded in 2009-2013 (n=3679; 62±12 y; 36% men; 863 family units). QRS, T and spatial ventricular gradient (SVG) vectors' magnitude and direction, spatial QRS-T angle and sum absolute QRST integral (SAI QRST) were measured., Outcome: Prevalent CVD was defined as the history of (1) coronary heart disease defined as diagnosed/silent myocardial infarction, or (2) revascularisation procedure defined as prior coronary/peripheral arterial revascularisation, or (3) carotid angioplasty/carotid endarterectomy, or (4) stroke., Results: In adjusted mixed linear models, women had a smaller spatial QRS-T angle (-12.2 (95% CI -19.4 to -5.1)°; p=0.001) and SAI QRST (-29.8 (-39.3 to -20.3) mV*ms; p<0.0001) than men, but larger SVG azimuth (+16.2(10.5-21.9)°; p<0.0001), with a significant random effect between families (+20.8 (8.2-33.5)°; p=0.001). SAI QRST was larger in women with CVD as compared with CVD-free women or men (+15.1 (3.8-26.4) mV*ms; p=0.009). Men with CVD had a smaller T area (by 5.1 (95% CI 1.2 to 9.0) mV*ms) and T peak magnitude (by 44 (95%CI 16 to 71) µV) than CVD-free men. T vectors pointed more posteriorly in women as compared with men (peak T azimuth + 17.2(8.9-25.6)°; p<0.0001), with larger sex differences in T azimuth in some families by +26.3(7.4-45.3)°; p=0.006., Conclusions: There are sex differences in the electrical signature of CVD in African-American men and women. There is a significant effect of unmeasured genetic and environmental factors on cardiac repolarisation., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Aims: Almost half of African American (AA) men and women have cardiovascular disease (CVD). Detection of prevalent CVD in community settings would facilitate secondary prevention of CVD. We sought to develop a tool for automated CVD detection., Methods and Results: Participants from the Jackson Heart Study (JHS) with analysable electrocardiograms (ECGs) ( n =3679; age, 6212 years; 36% men) were included. Vectorcardiographic (VCG) metrics QRS, T, and spatial ventricular gradient vectors magnitude and direction, and traditional ECG metrics were measured on 12-lead ECG. Random forests, convolutional neural network (CNN), lasso, adaptive lasso, plugin lasso, elastic net, ridge, and logistic regression models were developed in 80% and validated in 20% samples. We compared models with demographic, clinical, and VCG input (43 predictors) and those after the addition of ECG metrics (695 predictors). Prevalent CVD was diagnosed in 411 out of 3679 participants (11.2%). Machine learning models detected CVD with the area under the receiver operator curve (ROC AUC) 0.690.74. There was no difference in CVD detection accuracy between models with VCG and VCG + ECG input. Models with VCG input were better calibrated than models with ECG input. Plugin-based lasso model consisting of only two predictors (age and peak QRS-T angle) detected CVD with AUC 0.687 [95% confidence interval (CI) 0.6250.749], which was similar ( P =0.394) to the CNN (0.660; 95% CI 0.5970.722) and better ( P <0.0001) than random forests (0.512; 95% CI 0.4930.530)., Conclusions: Simple model (age and QRS-T angle) can be used for prevalent CVD detection in limited-resources community settings, which opens an avenue for secondary prevention of CVD in underserved communities., (The Author(s) 2021. Published by Oxford University Press on behalf of the European Society of Cardiology.)

Background—: Sex is a well-recognized risk factor for sudden cardiac death (SCD). We hypothesized that sex modifies the association of electrophysiological (EP) substrate with SCD., Methods—: Participants from the Atherosclerosis Risk in Communities study with analyzable ECGs (n=14,725; age, 54.2±5.8 yrs; 55% female, 74% white) were included. EP substrate was characterized by heart rate, QRS, QTc, Cornell voltage, spatial ventricular gradient (SVG), and sum absolute QRST integral (SAI QRST) ECG metrics. Two competing outcomes were adjudicated SCD and nonSCD. Interaction of ECG metrics with sex was studied in Cox proportional hazards and Fine-Gray competing risk models. Model 1 was adjusted for prevalent cardiovascular disease (CVD) and risk factors. Time-updated model 2 was additionally adjusted for incident non-fatal CVD. Relative hazard ratio (RHR) and relative sub-hazard ratio (RSHR) with a 95% confidence interval for SCD and nonSCD risk for women relative to men was calculated. Model 1 was adjusted for prevalent CVD and risk factors. Time-updated model 2 was additionally adjusted for incident non-fatal CVD., Results—: Over a median follow-up of 24.4 years, there were 530 SCDs (incidence 1.72 (1.58-1.88)/1000 person-years). Women as compared to men experienced a greater risk of SCD associated with Cornell voltage (RHR 1.18(1.06-1.32); P=0.003), SAI QRST (RHR 1.16(1.04-1.30); P=0.007), and SVG magnitude (RHR 1.24(1.05-1.45); P=0.009), independently from incident CVD., Conclusion—: In women, the global EP substrate is associated with up to 24% greater risk of SCD than in men, suggesting differences in underlying mechanisms and the need for sex-specific SCD risk stratification., Competing Interests: Conflict of interest: None.

Background: Adult congenital heart disease (ACHD) patients can benefit from a subcutaneous implantable cardioverter-defibrillator (S-ICD)., Objective: The purpose of this study was to assess left- and right-sided S-ICD eligibility in ACHD patients, use machine learning to predict S-ICD eligibility in ACHD patients, and transform 12-lead electrocardiogram (ECG) to S-ICD 3-lead ECG, and vice versa., Methods: ACHD outpatients (n = 101; age 42 ± 14 years; 52% female; 85% white; left ventricular ejection fraction [LVEF] 56% ± 9%) were enrolled in a prospective study. Supine and standing 12-lead ECG were recorded simultaneously with a right- and left-sided S-ICD 3-lead ECG. Peak-to-peak QRS and T amplitudes; RR, PR, QT, QTc, and QRS intervals; Tmax, and R/Tmax (31 predictor variables) were tested. Model selection, training, and testing were performed using supine ECG datasets. Validation was performed using standing ECG datasets and an out-of-sample non-ACHD population (n = 68; age 54 ± 16 years; 54% female; 94% white; LVEF 61% ± 8%)., Results: Forty percent of participants were ineligible for S-ICD. Tetralogy of Fallot patients passed right-sided screening (57%) more often than left-sided screening (21%; McNemar χ 2 P = .025). Female participants had greater odds of eligibility (adjusted odds ratio [OR] 5.9; 95% confidence interval [CI] 1.6-21.7; P = .008). Validation of the ridge models was satisfactory for standing left-sided (receiver operating characteristic area under the curve [ROC AUC] 0.687; 95% CI 0.582-0.791) and right-sided (ROC AUC 0.655; 95% CI 0.549-0.762) S-ICD eligibility prediction. Validation of transformation matrices showed satisfactory agreement (<0.1 mV difference)., Conclusion: Nearly half of the contemporary ACHD population is ineligible for S-ICD. The odds of S-ICD eligibility are greater for female than for male ACHD patients. Machine learning prediction of S-ICD eligibility can be used for screening of S-ICD candidates., (Copyright © 2020 Heart Rhythm Society. Published by Elsevier Inc. All rights reserved.)

Background: Mechanisms of arrhythmogenicity in hypertrophic cardiomyopathy (HCM) are not well understood., Objective: To characterize an electrophysiological substrate of HCM in comparison to ischemic cardiomyopathy (ICM), or healthy individuals., Methods: We conducted a prospective case-control study. The study enrolled HCM patients at high risk for ventricular tachyarrhythmia (VT) [ n = 10; age 61 ± 9 years; left ventricular ejection fraction (LVEF) 60 ± 9%], and three comparison groups: healthy individuals ( n = 10; age 28 ± 6 years; LVEF > 70%), ICM patients with LV hypertrophy (LVH) and known VT ( n = 10; age 64 ± 9 years; LVEF 31 ± 15%), and ICM patients with LVH and no known VT ( n = 10; age 70 ± 7 years; LVEF 46 ± 16%). All participants underwent 12-lead ECG, cardiac CT or MRI, and 128-electrode body surface mapping (BioSemi ActiveTwo, Netherlands). Non-invasive voltage and activation maps were reconstructed using the open-source SCIRun (University of Utah) inverse problem-solving environment., Results: In the epicardial basal anterior segment, HCM patients had the greatest ventricular activation dispersion [16.4 ± 5.5 vs. 13.1 ± 2.7 (ICM with VT) vs. 13.8 ± 4.3 (ICM no VT) vs. 8.1 ± 2.4 ms (Healthy); P = 0.0007], the largest unipolar voltage [1094 ± 211 vs. 934 ± 189 (ICM with VT) vs. 898 ± 358 (ICM no VT) vs. 842 ± 90 μV (Healthy); P = 0.023], and the greatest voltage dispersion [median (interquartile range) 215 (161-281) vs. 189 (143-208) (ICM with VT) vs. 158 (109-236) (ICM no VT) vs. 110 (106-168) μV (Healthy); P = 0.041]. Differences were also observed in other endo-and epicardial basal and apical segments., Conclusion: HCM is characterized by a greater activation dispersion in basal segments, a larger voltage, and a larger voltage dispersion through LV., Clinical Trial Registration: www.clinicaltrials.gov Unique identifier: NCT02806479., (Copyright © 2020 Perez-Alday, Haq, German, Hamilton, Johnson, Phan, Rogovoy, Yang, Wirth, Thomas, Dalouk, Fuss, Ferencik, Heitner and Tereshchenko.)

Background In patients with end-stage kidney disease, sudden cardiac death is more frequent after a long interdialytic interval, within 6 hours after the end of a hemodialysis session. We hypothesized that the occurrence of paroxysmal arrhythmias is associated with changes in heart rate and heart rate variability in different phases of hemodialysis. Methods and Results We conducted a prospective ancillary study of the Predictors of Arrhythmic and Cardiovascular Risk in End Stage Renal Disease cohort. Continuous ECG monitoring was performed using an ECG patch, and short-term heart rate variability was measured for 3 minutes every hour (by root mean square of the successive normal-to-normal intervals, spectral analysis, Poincaré plot, and entropy), up to 300 hours. Out of enrolled participants (n=28; age 54±13 years; 57% men; 96% black; 33% with a history of cardiovascular disease; left ventricular ejection fraction 70±9%), arrhythmias were detected in 13 (46%). Nonsustained ventricular tachycardia occurred more frequently during/posthemodialysis than pre-/between hemodialysis (63% versus 37%, P =0.015). In adjusted for cardiovascular disease time-series analysis, nonsustained ventricular tachycardia was preceded by a sudden heart rate increase (by 11.2 [95% CI 10.1-12.3] beats per minute; P <0.0001). During every-other-day dialysis, root mean square of the successive normal-to-normal intervals had a significant circadian pattern (Mesor 10.6 [ 95% CI 0.9-11.2] ms; amplitude 1.5 [95% CI 1.0-3.1] ms; peak at 02:01 [95% CI 20:22-03:16] am; P <0.0001), which was replaced by a steady worsening on the second day without dialysis (root mean square of the successive normal-to-normal intervals -1.41 [95% CI -1.67 to -1.15] ms/24 h; P <0.0001). Conclusions Sudden increase in heart rate during/posthemodialysis is associated with nonsustained ventricular tachycardia. Every-other-day hemodialysis preserves circadian rhythm, but a second day without dialysis is characterized by parasympathetic withdrawal.