Variant patterns of electrical activation and recovery in normal human hearts revealed by noninvasive electrocardiographic imaging.

AIMS: Although electrical activity of the normal human heart is well characterized by the electrocardiogram, detailed insights into within-subject and between-subject variations of ventricular activation and recovery by noninvasive electroanatomic mapping are lacking. We characterized human epicardial activation and recovery within and between normal subjects using non-invasive electrocardiographic imaging (ECGI) as a basis to better understand pathology. METHODS AND RESULTS: Epicardial activation and recovery were assessed by ECGI in 22 normal subjects, 4 subjects with bundle branch block (BBB) and 4 with long-QT syndrome (LQTS). We compared characteristics between the ventricles [left ventricle (LV) and right ventricle (RV)], sexes, and age groups (<50/≥50years). Pearson's correlation coefficient (CC) was used for within-subject and between-subject comparisons. Age of normal subjects averaged 49 ± 14 years, 6/22 were male, and no structural/electrical heart disease was present. The average activation time was longer in LV than in RV, but not different by sex or age. Electrical recovery was similar for the ventricles, but started earlier and was on average shorter in males. Median CCs of between-subject comparisons of the ECG signals, activation, and recovery patterns were 0.61, 0.32, and 0.19, respectively. Within-subject beat-to-beat comparisons yielded higher CCs (0.98, 0.89, and 0.82, respectively). Activation and/or recovery patterns of patients with BBB or LQTS contrasted significantly with those found in the normal population. CONCLUSION: Activation and recovery patterns vary profoundly between normal subjects, but are stable individually beat to beat, with a male preponderance to shorter recovery. Individual characterization by ECGI at baseline serves as reference to better understand the emergence, progression, and treatment of electrical heart disease.

Multiple anthropometric measures and proarrhythmic 12-lead ECG indices: A mendelian randomization study.

BACKGROUND: Observational studies suggest that electrocardiogram (ECG) indices might be influenced by obesity and other anthropometric measures, though it is difficult to infer causal relationships based on observational data due to risk of residual confounding. We utilized mendelian randomization (MR) to explore causal relevance of multiple anthropometric measures on P-wave duration (PWD), PR interval, QRS duration, and corrected QT interval (QTc). METHODS AND FINDINGS: Uncorrelated (r2 < 0.001) genome-wide significant (p < 5 × 10-8) single nucleotide polymorphisms (SNPs) were extracted from genome-wide association studies (GWAS) on body mass index (BMI, n = 806,834), waist:hip ratio adjusted for BMI (aWHR, n = 697,734), height (n = 709,594), weight (n = 360,116), fat mass (n = 354,224), and fat-free mass (n = 354,808). Genetic association estimates for the outcomes were extracted from GWAS on PR interval and QRS duration (n = 180,574), PWD (n = 44,456), and QTc (n = 84,630). Data source GWAS studies were performed between 2018 and 2022 in predominantly European ancestry individuals. Inverse-variance weighted MR was used for primary analysis; weighted median MR and MR-Egger were used as sensitivity analyses. Higher genetically predicted BMI was associated with longer PWD (ß 5.58; 95%CI [3.66,7.50]; p = < 0.001), as was higher fat mass (ß 6.62; 95%CI [4.63,8.62]; p < 0.001), fat-free mass (ß 9.16; 95%CI [6.85,11.47]; p < 0.001) height (ß 4.23; 95%CI [3.16, 5.31]; p < 0.001), and weight (ß 8.08; 95%CI [6.19,9.96]; p < 0.001). Finally, genetically predicted BMI was associated with longer QTc (ß 3.53; 95%CI [2.63,4.43]; p < 0.001), driven by both fat mass (ß 3.65; 95%CI [2.73,4.57]; p < 0.001) and fat-free mass (ß 2.08; 95%CI [0.85,3.31]; p = 0.001). Additionally, genetically predicted height (ß 0.98; 95%CI [0.46,1.50]; p < 0.001), weight (ß 3.45; 95%CI [2.54,4.36]; p < 0.001), and aWHR (ß 1.92; 95%CI [0.87,2.97]; p = < 0.001) were all associated with longer QTc. The key limitation is that due to insufficient power, we were not able to explore whether a single anthropometric measure is the primary driver of the associations observed. CONCLUSIONS: The results of this study support a causal role of BMI on multiple ECG indices that have previously been associated with atrial and ventricular arrhythmic risk. Importantly, the results identify a role of both fat mass, fat-free mass, and height in this association.

Epicardial adipose tissue as a mediator of cardiac arrhythmias.

Obesity is associated with higher risks of cardiac arrhythmias. Although this may be partly explained by concurrent cardiometabolic ill-health, growing evidence suggests that increasing adiposity independently confers risk for arrhythmias. Among fat depots, epicardial adipose tissue (EAT) exhibits a proinflammatory secretome and, given the lack of fascial separation, has been implicated as a transducer of inflammation to the underlying myocardium. The present review explores the mechanisms underpinning adverse electrophysiological remodeling as a consequence of EAT accumulation and the consequent inflammation. We first describe the physiological and pathophysiological function of EAT and its unique secretome and subsequently discuss the evidence for ionic channel and connexin expression modulation as well as fibrotic remodeling induced by cytokines and free fatty acids that are secreted by EAT. Finally, we highlight how weight reduction and regression of EAT volume may cause reverse remodeling to ameliorate arrhythmic risk.

Proarrhythmic electrophysiological and structural remodeling in rheumatoid arthritis.

Chronic inflammatory disorders, including rheumatoid arthritis (RA), are associated with a twofold increase in the incidence of sudden cardiac death (SCD) compared with the healthy population. Although this is partly explained by an increased prevalence of coronary artery disease, growing evidence suggests that ischemia alone cannot completely account for the increased risk. The present review explores the mechanisms of cardiac electrophysiological remodeling in response to chronic inflammation in RA. In particular, it focuses on the roles of nonischemic structural remodeling, altered cardiac ionic currents, and autonomic nervous system dysfunction in ventricular arrhythmogenesis and SCD. It also explores whether common genetic elements predispose to both RA and SCD. Finally, it evaluates the potential dual effects of disease-modifying therapy in both diminishing and promoting the risk of ventricular arrhythmias and SCD.

Bariatric surgery partially reverses subclinical proarrhythmic structural, electrophysiological, and autonomic changes in obesity.

BACKGROUND: Obesity confers higher risks of cardiac arrhythmias. The extent to which weight loss reverses subclinical proarrhythmic adaptations in arrhythmia-free obese individuals is unknown. OBJECTIVE: The purpose of this study was to study structural, electrophysiological, and autonomic remodeling in arrhythmia-free obese patients and their reversibility with bariatric surgery using electrocardiographic imaging (ECGi). METHODS: Sixteen arrhythmia-free obese patients (mean age 43 ± 12 years; 13 (81%) female participants; BMI 46.7 ± 5.5 kg/m2) had ECGi pre-bariatric surgery, of whom 12 (75%) had ECGi postsurgery (BMI 36.8 ± 6.5 kg/m2). Sixteen age- and sex-matched lean healthy individuals (mean age 42 ± 11 years; BMI 22.8 ± 2.6 kg/m2) acted as controls and had ECGi only once. RESULTS: Obesity was associated with structural (increased epicardial fat volumes and left ventricular mass), autonomic (blunted heart rate variability), and electrophysiological (slower atrial conduction and steeper ventricular repolarization time gradients) remodeling. After bariatric surgery, there was partial structural reverse remodeling, with a reduction in epicardial fat volumes (68.7 cm3 vs 64.5 cm3; P = .0010) and left ventricular mass (33 g/m2.7 vs 25 g/m2.7; P < .0005). There was also partial electrophysiological reverse remodeling with a reduction in mean spatial ventricular repolarization gradients (26 mm/ms vs 19 mm/ms; P = .0009), although atrial activation remained prolonged. Heart rate variability, quantified by standard deviation of successive differences in R-R intervals, was also partially improved after bariatric surgery (18.7 ms vs 25.9 ms; P = .017). Computational modeling showed that presurgical obese hearts had a larger window of vulnerability to unidirectional block and had an earlier spiral-wave breakup with more complex reentry patterns than did postsurgery counterparts. CONCLUSION: Obesity is associated with adverse electrophysiological, structural, and autonomic remodeling that is partially reversed after bariatric surgery. These data have important implications for bariatric surgery weight thresholds and weight loss strategies.

Association of Hypertensive Disorders of Pregnancy With Future Cardiovascular Disease.

Conclusions and Relevance: The findings of this study provide genetic evidence supporting an association between HDPs and higher risk of coronary artery disease and stroke, which is only partially mediated by cardiometabolic factors. This supports classification of HDPs as risk factors for cardiovascular disease. Design, Setting, and Participants: A genome-wide genetic association study using mendelian randomization (MR) was performed from February 16 to March 4, 2022. Primary analysis was conducted using inverse-variance-weighted MR. Mediation analyses were performed using a multivariable MR framework. All studies included patients predominantly of European ancestry. Female-specific summary-level data from FinnGen (sixth release). Exposures: Uncorrelated (r2<0.001) single-nucleotide variants (SNVs) were selected as instrumental variants from the FinnGen consortium summary statistics for exposures of any HDP, gestational hypertension, and preeclampsia or eclampsia. Importance: Hypertensive disorders in pregnancy (HDPs) are major causes of maternal and fetal morbidity and are observationally associated with future maternal risk of cardiovascular disease. However, observational results may be subject to residual confounding and bias. Main Outcomes and Measures: Genetic association estimates for outcomes were extracted from genome-wide association studies of 122 733 cases for coronary artery disease, 34 217 cases for ischemic stroke, 47 309 cases for heart failure, and 60 620 cases for atrial fibrillation. Objective: To investigate the association of HDPs with multiple cardiovascular diseases. Results: Genetically predicted HDPs were associated with a higher risk of coronary artery disease (odds ratio [OR], 1.24; 95% CI, 1.08-1.43; P = .002); this association was evident for both gestational hypertension (OR, 1.08; 95% CI, 1.00-1.17; P = .04) and preeclampsia/eclampsia (OR, 1.06; 95% CI, 1.01-1.12; P = .03). Genetically predicted HDPs were also associated with a higher risk of ischemic stroke (OR, 1.27; 95% CI, 1.12-1.44; P = 2.87 × 10-4). Mediation analysis revealed a partial attenuation of the effect of HDPs on coronary artery disease after adjustment for systolic blood pressure (total effect OR, 1.24; direct effect OR, 1.10; 95% CI, 1.02-1.08; P = .02) and type 2 diabetes (total effect OR, 1.24; direct effect OR, 1.16; 95% CI, 1.04-1.29; P = .008). No associations were noted between genetically predicted HDPs and heart failure (OR, 0.97; 95% CI, 0.76-1.23; P = .79) or atrial fibrillation (OR, 1.11; 95% CI, 0.65-1.88; P = .71).

Obesity as a risk factor for cardiac arrhythmias.

Obesity is global health problem with an estimated three billion people worldwide being classified as overweight or obese. In addition to being associated with a range of adverse health outcomes, obesity is linked to higher risks of atrial and ventricular arrhythmias, as well as sudden cardiac death. Obesity is a multifactorial disease that often co-exists with hypertension, diabetes, and sleep apnoea, which are also independent risk factors for cardiac arrhythmias. Nevertheless, compelling evidence suggests that increasing adiposity is an independent proarrhythmic risk factor and that weight loss can be a mitigating and preventative intervention to reduce arrhythmia incidence. This review briefly outlines the economic and social burden of obesity and summarises evidence for the direct and indirect effects of increasing adiposity on risk of atrial and ventricular arrhythmias. The paper also summarises the evidence for electrocardiographic changes indicative of obesity-related atrial and ventricular remodelling and how weight reduction and management of comorbidity might reduce arrhythmic burden.

Increasing Adiposity Is Associated With QTc Interval Prolongation and Increased Ventricular Arrhythmic Risk in the Context of Metabolic Dysfunction: Results From the UK Biobank.

Background: Small-scale studies have linked obesity (Ob) and metabolic ill-health with proarrhythmic repolarisation abnormalities. Whether these are observed at a population scale, modulated by individuals' genetics, and confer higher risks of ventricular arrhythmias (VA) are not known. Methods and Results: Firstly, using the UK Biobank, the association between adiposity and QTc interval was assessed in participants with a resting 12-lead ECG (n = 23,683), and a polygenic risk score (PRS) was developed to investigate any modulatory effect of genetics. Participants were also categorised into four phenotypes according to the presence (+) or absence (-) of Ob, and if they were metabolically unhealthy (MU+) or not (MU-). QTc was positively associated with body mass index (BMI), body fat (BF), waist:hip ratio (WHR), and hip and waist girths. Individuals' genetics had no significant modulatory effect on QTc-prolonging effects of increasing adiposity. QTc interval was comparably longer in those with metabolic perturbation without obesity (Ob-MU+) and obesity alone (Ob+MU-) compared with individuals with neither (Ob-MU-), and their co-existence (Ob+MU+) had an additive effect on QTc interval. Secondly, for 502,536 participants in the UK Biobank, odds ratios (ORs) for VA were computed for the four clinical phenotypes above using their past medical records. Referenced to Ob-MU-, ORs for VA in Ob-MU+ men and women were 5.96 (95% CI: 4.70-7.55) and 5.10 (95% CI: 3.34-7.80), respectively. ORs for Ob+MU+ were 6.99 (95% CI: 5.72-8.54) and 3.56 (95% CI: 2.66-4.77) in men and women, respectively. Conclusion: Adiposity and metabolic perturbation increase QTc to a similar degree, and their co-existence exerts an additive effect. These effects are not modulated by individuals' genetics. Metabolic ill-health is associated with a higher OR for VA than obesity.

Maternal Hypertension Increases Risk of Preeclampsia and Low Fetal Birthweight: Genetic Evidence From a Mendelian Randomization Study.

BACKGROUND: Maternal cardiovascular risk factors have been associated with adverse maternal and fetal outcomes. Given the difficulty in establishing causal relationships using epidemiological data, we applied Mendelian randomization to explore the role of cardiovascular risk factors on risk of developing preeclampsia or eclampsia, and low fetal birthweight. METHODS: Uncorrelated single-nucleotide polymorphisms associated systolic blood pressure (SBP), body mass index, type 2 diabetes, LDL (low-density lipoprotein) with cholesterol, smoking, urinary albumin-to-creatinine ratio, and estimated glomerular filtration rate at genome-wide significance in studies of 298 957 to 1 201 909 European ancestry participants were selected as instrumental variables. A 2-sample Mendelian randomization study was performed with primary outcome of preeclampsia or eclampsia (PET). Risk factors associated with PET were further investigated for their association with low birthweight. RESULTS: Higher genetically predicted SBP was associated increased risk of PET (odds ratio [OR] per 1-SD SBP increase 1.90 [95% CI=1.45-2.49]; P=3.23×10-6) and reduced birthweight (OR=0.83 [95% CI=0.79-0.86]; P=3.96×10-18), and this was not mediated by PET. Body mass index and type 2 diabetes were also associated with PET (respectively, OR per 1-SD body mass index increase =1.67 [95% CI=1.44-1.94]; P=7.45×10-12; and OR per logOR increase type 2 diabetes =1.11 [95% CI=1.04-1.19]; P=1.19×10-3), but not with reduced birthweight. CONCLUSIONS: Our results provide evidence for causal effects of SBP, body mass index, and type 2 diabetes on PET and identify that SBP is associated with reduced birthweight independently of PET. The results provide insight into the pathophysiological basis of PET and identify hypertension as a potentially modifiable risk factor amenable to therapeutic intervention.

A fully-automated paper ECG digitisation algorithm using deep learning.

There is increasing focus on applying deep learning methods to electrocardiograms (ECGs), with recent studies showing that neural networks (NNs) can predict future heart failure or atrial fibrillation from the ECG alone. However, large numbers of ECGs are needed to train NNs, and many ECGs are currently only in paper format, which are not suitable for NN training. We developed a fully-automated online ECG digitisation tool to convert scanned paper ECGs into digital signals. Using automated horizontal and vertical anchor point detection, the algorithm automatically segments the ECG image into separate images for the 12 leads and a dynamical morphological algorithm is then applied to extract the signal of interest. We then validated the performance of the algorithm on 515 digital ECGs, of which 45 were printed, scanned and redigitised. The automated digitisation tool achieved 99.0% correlation between the digitised signals and the ground truth ECG (n = 515 standard 3-by-4 ECGs) after excluding ECGs with overlap of lead signals. Without exclusion, the performance of average correlation was from 90 to 97% across the leads on all 3-by-4 ECGs. There was a 97% correlation for 12-by-1 and 3-by-1 ECG formats after excluding ECGs with overlap of lead signals. Without exclusion, the average correlation of some leads in 12-by-1 ECGs was 60-70% and the average correlation of 3-by-1 ECGs achieved 80-90%. ECGs that were printed, scanned, and redigitised, our tool achieved 96% correlation with the original signals. We have developed and validated a fully-automated, user-friendly, online ECG digitisation tool. Unlike other available tools, this does not require any manual segmentation of ECG signals. Our tool can facilitate the rapid and automated digitisation of large repositories of paper ECGs to allow them to be used for deep learning projects.

Neural networks applied to 12-lead electrocardiograms predict body mass index, visceral adiposity and concurrent cardiometabolic ill-health.

BACKGROUND: Obesity is associated with electrophysiological remodeling, which manifests as detectable changes on the surface electrocardiogram (ECG). OBJECTIVE: To develop neural networks (NN) to predict body mass index (BMI) from ECGs and test the hypothesis that discrepancies between NN-predicted BMI and measured BMI are indicative of underlying adiposity and/or concurrent cardiometabolic ill-health. METHODS: NN models were developed using 36,856 12-lead resting ECGs from the UK Biobank. Two architectures were developed for continuous and categorical BMI estimation (normal weight [BMI <25 kg/m2] vs overweight/obese [BMI ≥25 kg/m2]). Models for male and female participants were trained and tested separately. For each sex, data were randomly divided into 4 folds, and models were evaluated in a leave-1-fold-out manner. RESULTS: ECGs were available for 17,807 male and 19,049 female participants (mean ages: 61 ± 7 and 63 ± 8 years; mean BMI 26 ± 5 kg/m2 and 27 ± 4 kg/m2, respectively). NN models detected overweight/obese individuals with average accuracies of 75% and 73% for male and female subjects, respectively. The magnitudes of difference between NN-predicted BMI and actual BMI were significantly correlated with visceral adipose tissue volumes. Concurrent hypertension, diabetes, dyslipidemia, and/or coronary heart disease explained false-positive classifications (ie, calculated BMI <25 kg/m2 misclassified as ≥25 kg/m2 by NN model, P < .001). CONCLUSION: NN models applied to 12-lead ECGs predict BMI with a reasonable degree of accuracy. Discrepancies between NN-predicted and calculated BMI may be indicative of underlying visceral adiposity and concomitant cardiometabolic perturbation, which could be used to identify individuals at risk of cardiometabolic disease.

The subcutaneous ICD-current evidence and challenges.

The subcutaneous implantable cardioverter-defibrillator (S-ICD) represents an exciting development in ICD technology. It has relative advantages over traditional transvenous systems, particularly for young patients in whom the lifetime risk of device-related complications may be deemed to be unacceptably high. While data relating to device longevity and long term safety profile is yet to be accrued, several recent studies have demonstrated good clinical efficacy comparable to transvenous ICDs. Indeed, new techniques have also been developed to simplify the S-ICD implantation procedure and attempts have been made to address challenges pertaining to T-wave oversensing to reduce the delivery of inappropriate shocks. The impact of inappropriate shocks and lack of anti-tachycardia pacing (ATP) function are not only contentious matters, but also have important implications for patients in whom the S-ICD would be suitable. It is envisaged that subsequent models of this device will be less cumbersome, with the possibility that an entirely leadless pacemaker-defibrillator will one day be possible. Although the S-ICD may not completely replace transvenous devices in its current form, evidence suggests that it is a viable alternative particularly in preventing sudden cardiac death in non-pacing dependent patients.