BACKGROUND:Young people taking beta-blockers for long QT syndrome (LQTS) have concerns about exercise performance. OBJECTIVES:This study sought to determine whether objective measures of cardiopulmonary fitness are influenced by beta-blocker dose in LQTS. METHODS:In a retrospective chart review of treadmill cardiopulmonary exercise tests (CPETs), we measured peak oxygen consumption (Vo2), respiratory exchange ratio (RER), blood pressure, and percent predicted heart rate at peak exertion (%PHR), each analyzed with a linear mixed-effects model. We analyzed nadolol data (noncardioselective) as our primary analysis, then analyzed a validation cohort of atenolol data (cardioselective). RESULTS:We evaluated 220 CPETs in 93 patients with LQTS. The mean age at first CPET was 12 ± 3.9 years. In multivariable analysis, %PHR decreased by 13% for every 1 mg/kg/d increase in beta-blocker dose, demonstrating physiologic beta-blocker effects. However, we identified no correlation between nadolol dose and measures of cardiopulmonary fitness. Neither peak Vo2 nor peak RER was correlated with nadolol dose. Only mild blood pressure changes were observed (<9 mm Hg decrease at peak exertion per 1 mg/kg increase in nadolol dose). Increased atenolol dose was also associated with stable peak Vo2 and peak RER. CONCLUSIONS:In children with LQTS, we did not observe any relationship between higher nadolol doses and objective measures of effort (peak RER) or cardiopulmonary fitness (peak Vo2), despite a linear dose-response between nadolol dose and %PHR. These results suggest that treatment with nadolol for LQTS does not affect most patients' peak exercise performance. These data were validated in patients from an earlier era who had been prescribed atenolol.

Abstract Pediatric patients with epicardial cardiac implantable electronic devices (CIEDs) are frequently excluded from the Magnetic Resonance Imaging (MRI) primarily due to RF heating safety concerns. In this study we evaluate RF heating of two bipolar epicardial leads during MRI at 0.55 T and 1.5 T under different termination conditions. Our findings showed that the mean RF heating was significantly reduced at 0.55 T MRI compared to that at 1.5 T. Similarly, the RF heating at 0.55 T MRI was highest for full system whereas, during MRI at 1.5 T, the RF heating was highest for the capped abandoned lead, showing dependence of RF heating pattern on MRI field strength. While RF heating at both fields surpassed the safety limit, the capped abandoned leads at 1.5 T MRI showed significantly higher RF heating with temperature rise surpassing 50°C in some of the cases. These results highlight the difference in RF heating of bipolar epicardial leads compared to the previously reported findings for monopolar epicardial lead which showed smallest heating for capped abandoned lead at both field strengths. These findings emphasize the necessity of device-specific evaluations at each field-strength to inform clinical decision-making and expand MRI access for this vulnerable population.

Purpose:RF-induced heating remains a major barrier to MRI access for patients with epicardial cardiac implantable electronic devices (CIEDs). Although ISO/TS 10974 Tier-3 transfer function (TF) methods are established for unbranched leads, no analogous framework exists for bifurcated leads, in which branch asymmetry and inter-branch coupling may substantially alter heating. We developed and validated a cumulative transfer function (cTF) framework to address this gap. Methods:Following ISO/TS 10974 Tier-3 formalism, we measured, calibrated, and validated cTFs for a commercial 35 cm bipolar epicardial lead at 1.5 T. The framework explicitly accounts for branch-specific response and cross-branch coupling. Validation was performed with 24 canonical lead configurations in a homogeneous phantom and, without recalibration, in a heterogeneous anthropomorphic pediatric phantom with clinically derived trajectories. A single-branch TF approximation served as a comparator. The validated cTF was applied to predict RF heating across adult and pediatric human models at multiple imaging landmarks. Results:Compared with the single-branch TF approximation, the cTF reduced prediction error by nearly 70% in the primary validation dataset. In secondary validation, the cTF maintained low error across clinically relevant trajectories and imaging landmarks. In human models, the framework revealed marked anatomy- and landmark-dependent variation in predicted heating for the tested 35 cm lead, with low predicted heating in pediatric models and substantially higher heating in selected adult chest and upper abdominal imaging scenarios. Conclusion:The cTF provides a validated framework for RF-heating assessment of bifurcated leads and substantially improves prediction accuracy over single-branch TF approximations that neglect branch coupling.

Atrial fibrillation (AF), the most common sustained arrhythmia, has a complex genetic basis; however, the molecular mechanisms linking rare and common variants remain poorly understood. Polygenic risk score (PRS) analysis in the UK Biobank and All of Us cohorts reveals that carriers of protein-altering LMNA variants (PAVs) have a significantly higher risk of incident AF than predicted by PRS alone, supporting an additive effect of common polymorphisms and LMNA variants. Induced pluripotent stem cell derived atrial cardiomyocytes (iPSC-aCMs) from individuals carrying the pathogenic missense variant p.S143P in LMNA exhibit widespread disruption of chromatin architecture and perturbation of atrial gene regulatory networks, particularly at loci harboring AF-associated variants and transcription factors essential for atrial rhythm control and contractility. Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-based epigenetic editing validates the function of several AF-associated regulatory elements and their downstream targets. Notably, reduced accessibility at an intronic SCN10A enhancer harboring the AF-associated SNP rs6801957 is associated with reduced sodium current in p.S143P iPSC-aCMs. These findings are reproduced in iPSC-aCMs derived from an additional individual carrying a distinct pathogenic LMNA variant, supporting a broader mechanism in which rare LMNA variants and common polymorphisms converge on shared regulatory networks to influence AF susceptibility and highlighting the value of integrating both in arrhythmia risk assessment.

Pediatric patients with cardiac implantable electronic devices (CIEDs) face limited MRI access due to RF-induced heating, and computational modeling is increasingly used to characterize this risk. The validity of these simulations, however, depends on pairing body models with clinically realistic lead configurations, guidance that is currently lacking. We retrospectively analyzed 302 CIED surgeries in 281 pediatric patients to derive weight-based constraints for simulation design. Weight alone discriminated epicardial from endocardial lead implantation with AUC = 0.90, and adding age and height yielded no improvement, supporting weight as a sufficient single-parameter selection metric. The probabilistic crossover between approaches occurred at 44 kg, substantially higher than the 10 to 15 kg threshold commonly cited in the literature, with a broad transition zone of 21 to 66 kg in which both lead types were routinely used. Lead length was likewise weight-constrained: only 25 cm leads were observed in patients below 6 kg, and leads of 45 cm or longer were uncommon below 50 kg. These findings yield a three-tier framework, with epicardial-only configurations below 21 kg, dual configurations within 21 to 66 kg, and weight-thresholded lead lengths throughout, enabling MRI safety simulations to focus on clinically realizable anatomy and device combinations.

Introduction: Relatives of a victim of sudden cardiac death in the young (SCDY) may be at-risk for hereditary cardiomyopathies and arrhythmias; effective communication of cardiac risk is imperative. Family leaders are often responsible for communicating risk to surviving family during a difficult time. Cascade screening uptake is low among at-risk family members; identifying barriers of risk communication can help improve strategies. Purpose: Explore barriers and facilitators to communication about cascade screening in families who have lost a family member to SCDY. Methods: Semi-structured interviews (n = 14) were conducted with family members of a SCDY decedent. Participants were recruited from the Sudden Arrhythmia Death Syndrome advocacy group. Interviews explored the facilitators, challenges and proposed interventions at different stages of risk communication. Interviews were conducted until data saturation was reached. Interviews were audio recorded, transcribed, and analyzed using conventional content analysis. Results: Five categories were identified from the interviews: 1. Participants understood fundamental risks but the clinical variability in arrhythmia and cardiomyopathy was difficult to interpret and convey; 2. Family leaders felt some family disregarded risk information; 3. Grief interfered with family leader’s ability to understand and communicate risk information; 4. Communication aids were insufficient stand-alone interventions; 5. Families advocated for a “genetic family navigator”. Conclusion: This is the first study to evaluate cardiac risk communication between adult family members after a SCDY. Five categories provide practical strategies to improve clinical care and communication for families after SCDY and emphasize the need for genetic family navigators to facilitate cascade screening.

BACKGROUND:Genetic variation contributes to atrial fibrillation (AF), but its impact may vary with age. The All of Us Research Program contains whole-genome sequencing of data from 100 574 adult participants with linked electronic health records. METHODS:We assessed clinical, monogenic, and polygenic associations with AF in a cross-sectional analysis, stratified by age: <45 years (n=22 290), 45 to 60 years (n=26 805), and >60 years (n=51 659). AF was defined as ≥2 Systematized Nomenclature of Medicine-Clinical Terms codes on separate days. We identified pathogenic/likely pathogenic variants in 145 cardiac genes with dominant inheritance and calculated a previously established polygenic risk score. Adjusted for known clinical factors, multivariable analysis quantified associations between monogenic and polygenic factors and AF in each age group. RESULTS:Among 100 574 participants (mean age 59±16 years), 7811 (7.8%) had AF, while 92 763 (92%) did not. Monogenic pathogenic/likely pathogenic variants were associated with AF across all age groups, most strongly in participants aged <45 years (odds ratio, 2.1 [95% CI, 1.2-3.2]; P=0.007). In contrast, the polygenic risk score was not associated with AF in this youngest group (odds ratio, 1.0 [95% CI, 0.9-1.2]; P=0.650) but was in older groups (odds ratio 1.3 [95% CI, 1.2-1.4]; P<0.001 for both ages 45-60 and >60 years). Clinical factors were significantly associated with AF (C-index, 0.84 [0.83-0.84]; P<0.001), with marginal improvement when monogenic and polygenic data were added (C-index, 0.86 [0.86-0.87]; P<0.001). In hazard-based time-to-event analysis, monogenic variants were associated with earlier onset, whereas the polygenic risk score was not associated with age of onset. CONCLUSIONS:In this large cross-sectional study, monogenic variants were associated with AF throughout life, particularly in younger participants, whereas polygenic risk was associated with AF only in older participants. While genetic information added only marginal improvements to AF risk discrimination beyond existing clinical risk factors, monogenic variants were associated with an earlier age of onset in participants with AF.

PurposeClinical genetic testing is increasingly integrated in managing and diagnosing cardiac conditions and disease. It is important to identify ongoing challenges. This study aimed to better understand how genetic testing is integrated into pediatric cardiac care and identify barriers and opportunities for improvement.MethodsWe conducted qualitative interviews with pediatric cardiology clinicians (N = 12). Following a journey mapping approach to data analysis, we described genetic testing workflow phases, participants’ thoughts and behaviors within each phase, and barriers and opportunities for improvement.ResultsParticipants described several challenges across the genetic testing workflow, from identifying patients for testing to disclosing results to the patients. Testing logistics, decision-making, and collaboration emerged as the most prominent challenges. Variation remains in the utilization of genetic testing, partially driven by case complexity and type of testing and attributable to other factors, like the level of interaction with genetics experts and inconsistent processes within the electronic medical record.ConclusionClinical genetic pediatric cardiology requires more systematic integration of genetic testing and transparent processes. Major opportunities include the interplay between clinicians, genetic experts, and the EMR. Incorporating process mapping results into clinical logistics may eradicate some barriers experienced by pediatric cardiologists and increase clinical efficiency.

Background Simple biometrics such as peak heart rate and exercise duration remain core predictors of cardiovascular disease (CVD). Commercial wearable devices track physical and cardiac electrical activity. Detailed, longitudinal data collection from wearables presents a valuable opportunity to identify new factors associated with CVD. Methods and Results This cross‐sectional study analyzed 6947 participants in the Fitbit Bring‐Your‐Own‐Device Project, a subset of the All of Us Research Program. The primary exposure daily heart rate per step (DHRPS) was defined as the average daily heart rate divided by steps per day. Our analysis correlated DHRPS with established CVD factors (type 2 diabetes, hypertension, stroke, heart failure, coronary atherosclerosis, myocardial infarction) as primary outcomes. We also performed a DHRPS‐based phenome‐wide association study on the spectrum of human disease traits for all 1789 disease codes across 17 disease categories. Secondary outcomes included maximum metabolic equivalents achieved on cardiovascular treadmill exercise stress testing. We examined 5.8 million person‐days and 51 billion total steps of individual‐level Fitbit data paired with electronic health record data. Elevated DHRPS was associated with type 2 diabetes (odds ratio [OR], 2.03 [95% CI, 1.70–2.42]), hypertension (OR, 1.63 [95% CI, 1.32–2.02]), heart failure (OR, 1.77 [95% CI, 1.00–3.14]), and coronary atherosclerosis (OR, 1.44 [95% CI, 1.14–1.82]), even after adjusting for daily heart rate (DHR) and step count. DHRPS also had stronger correlations with maximum metabolic equivalents achieved on exercise stress testing compared with steps per day (∆ρ=0.04, P<0.001) and heart rate (∆ρ=0.31, P<0.001). Lastly, DHRPS‐based phenome‐wide association study demonstrated stronger associations with CVD factors (P<1×10−55) compared with daily heart rate or step count. Conclusions In the All of Us Research Program Fitbit Bring‐Your‐Own‐Device Project, DHRPS was an easy‐to‐calculate wearables metric and was more strongly associated with cardiovascular fitness and CVD outcomes than DHR and step count.

Cardiac ventricular arrhythmias can cause sudden death. Despite known genomic contributions, multigenic risk predictors are limited. The genetics of arrhythmias and cardiomyopathies overlap, with additional overlap with epilepsy. To improve genetic risk prediction, we assemble a cohort with non-ischemic ventricular arrhythmias and controls lacking cardiac diagnoses. Here, we integrate 18 polygenic scores; variants from clinical gene panels for coding regions of cardiomyopathy, arrhythmia, and epilepsy genes; and noncoding regulatory regions mapping to those genes. Polygenic scores alone hold prognostic value. Rare coding variants identify cumulative risk extending beyond known pathogenic/likely pathogenic variants. We also find enrichment of ultrarare regulatory variation. A risk predictor that combines all variant classes outperforms any single class or subset and replicates in a validation cohort. This combined genomic arrhythmia propensity score (GAPS) identifies high-risk individuals even among those who lack known primary pathogenic variants. This integrated approach serves as a model for other complex traits.

This study compared the diagnostic yield of wideband late gadolinium enhancement and perfusion pulse sequences to their standard cardiovascular MRI counterparts in pediatric participants using an implantable pulse generator taped at anatomically correct locations to mimic both endocardial and epicardial cardiac implantable electronic device systems.