Citations

Abstract Aims ECG abnormalities are often the first signs of arrhythmogenic right ventricular cardiomyopathy (ARVC) and we hypothesized that an artificial intelligence (AI)-enhanced ECG could help identify patients with ARVC and serve as a valuable disease-detection tool. Methods and results We created a convolutional neural network to detect ARVC using a 12-lead ECG. All patients with ARVC who met the 2010 task force criteria and had disease-causative genetic variants were included. All case ECGs were randomly assigned in an 8:1:1 ratio into training, validation, and testing groups. The case ECGs were age- and sex-matched with control ECGs at our institution in a 1:100 ratio. Seventy-seven patients (51% male; mean age 47.2 ± 19.9), including 56 patients with PKP2, 7 with DSG2, 6 with DSC2, 6 with DSP, and 2 with JUP were included. The model was trained using 61 case ECGs and 5009 control ECGs; validated with 7 case ECGs and 678 control ECGs and tested in 22 case ECGs and 1256 control ECGs. The sensitivity, specificity, positive and negative predictive values of the model were 77.3, 62.9, 3.32, and 99.4%, respectively. The area under the curve for rhythm ECG and median beat ECG was 0.75 and 0.76, respectively. Conclusion Our study found that the model performed well in excluding ARVC and supports the concept that the AI ECG can serve as a biomarker for ARVC if a larger cohort were available for network training. A multicentre study including patients with ARVC from other centres would be the next step in refining, testing, and validating this algorithm.

Abstract Background Cardiac sarcoidosis (CS) is a difficult to diagnose inflammatory heart disease. Certain types of genetic cardiomyopathy have been reported to masquerade as inflammatory cardiomyopathy. The utility of genetic testing in the evaluation of inflammatory cardiomyopathy is not completely explored and data regarding the prevalence of genetic cardiomyopathies in patients with presumed CS is limited. Methods We retrospectively analyzed patients evaluated from May 2020 to October 2022 in our Cardiac Sarcoid Clinic diagnosed with presumed CS as inferred by either fluorodeoxyglucose positron emission tomography (FDG-PET) - computed tomography (CT) or cardiac magnetic resonance (CMR) or both. Pertinent demographic, genetic, electrocardiographic, and imaging data for these patients was extracted from the electronic medical record. Results Genetic testing was obtained in 47 (22%) of the 213 presumed CS patients, among whom 43 (91%) presented with suspected isolated CS, and 4 (9%) with possible cardiac involvement in the setting of systemic sarcoidosis. Among the patients who underwent genetic testing, 10 (21 %) had a pathogenic or likely pathogenic (P/LP) variant(s) in a genetic cardiomyopathy-susceptibility gene, including DSP (n=2), LMNA, FHL1, TPM1, MYBPC3, NRAS, MYH7 (n=2) and TTN (n= 2) genes. All P/LP patients had FDG uptake, and in those with CMR data, 100% had late gadolinium enhancement. The seven patients with P/LP who underwent endomyocardial biopsy had no evidence of granulomatous inflammation. Immunosuppression was initiated in 60% of the P/LP patients before knowledge of genetic results. Conclusion Patients suspected to have CS may have concomitant or primarily genetic cardiomyopathy that may masquerade as an inflammatory phenotype Genetic testing should be considered in these patients, not only to clarify the diagnosis and its prognostic and therapeutic implications, but also to offer cascade screening for the family of patients with P/LP variants who otherwise would not have been considered to have a heritable disease.

Abstract Background Atrial fibrillation (AF) is associated with increased risk of incident tricuspid regurgitation (TR), but types of incident TR in AF versus sinus rhythm (SR) are not well-defined. Purpose We aimed to compare the risk of the different types of incident ≥moderate TR in AF and SR. Methods Adults first diagnosed with AF (2010-2021) who had a transthoracic echocardiogram (TTE) within 30 days after AF and adults with no diagnosis of AF who had a TTE in the same period were identified. Patients with previous cardiac surgeries, congenital heart disease, cardiomyopathy, cardiac devices, primary valve disease, previous or current ejection fraction (EF) <50%, severe diastolic dysfunction (SDD), ≥moderate left-sided valve disease (LVD), right ventricular systolic pressure (RVSP) ≥50 mmHg, ≥moderate TR, any tricuspid stenosis, or with no follow-up TTE ≥6 months from baseline were excluded. Patients were followed for the development of ≥moderate TR, the type of which was identified in a hierarchal order: 1) pacemaker-associated TR, 2) LVD-associated TR in the setting of ≥moderate LVD, 3) low EF or SDD-related TR, 4) pulmonary hypertension (PH)-associated TR if RVSP was ≥50 mmHg, 5) other ventricular functional TR (VFTR) if there was >mild RV enlargement or dysfunction, and 6) atrial functional TR (AFTR) when none of the previous was present. Patients were also followed for the occurrence of risk factors for TR (pacemaker insertion, ≥moderate LVD, low EF or SDD, PH, >mild RV enlargement or dysfunction) in a hierarchal order, and both the prevalence and future risk of the corresponding type of ≥moderate TR was determined at the onset of these conditions in AF and SR. Results Overall, 1,360 patients with new-onset AF (median age 67 years, 34% females) and 20,438 patients in SR (median age 60 years; 54% females) were included. Over median 3.8 (IQR 1.8-6.6) years, incident ≥moderate TR occurred in 110 patients with new-onset AF [2.13 per 100-person years] compared to 378 patients in SR [0.41 per 100-person years, p <.001]. All types of incident ≥moderate TR occurred more frequently in AF (p <.001 for all). The distribution and incidence of each type of TR in AF and SR are shown in Figure 1. The incidence of risk factors associated with the development of TR was higher in the AF group, except for pre-capillary PH, Figure 2A. At time of diagnosis or occurrence of these conditions, the prevalence of the corresponding TR types was higher in AF, except for pacemaker-TR, Figure 2B. The incidence of the corresponding TR type after occurrence of TR risk factors was higher in the AF group for LVD-TR and low EF/SDD-associated TR (p ≤0.03); although numerically higher in AF, the association was only borderline for PH-TR (p =0.05), Figure 2C. Conclusion Incident ≥moderate TR of all types occurred more frequently in patients with AF vs. SR and the distribution of TR types differed by rhythm. Patients with AF may benefit from a closer follow-up.Distribution and incidence rates of TRIncidence of TR risk factors & TR after

Abstract Background/Introduction Arrhythmogenic mitral valve prolapse syndrome (AMVPS) is a female-predominant sudden cardiac death (SCD)-predisposing disorder characterized clinically by myxomatous mitral valve prolapse (MVP), inferolateral T-wave inversions and complex ventricular ectopy. However, insights into the pathogenesis and potential genetic basis of AMVPS are currently lacking. Purpose Considering recent case reports that suggest a potential role for genetic cardiomyopathies in the pathogenesis of AMVPS, we sought to determine the yield of pathogenic/likely pathogenic (P/LP) genetic variants in strong evidence cardiomyopathy-susceptibility genes amongst AMVPS patients who underwent clinical genetic testing. Methods In this retrospective study, the medical records of 4,907 patients referred to our cardiovascular genetics clinic was used to identify those patients with a clinical phenotype consistent with AMVPS. After exclusion of individuals with severe mitral valve regurgitation, pertinent clinical, electrocardiographic, imaging and genetic testing data was extracted from the electronic record. For those AMVPS that underwent a form of genetic testing that encompassed 23 Clinical Genome Resource-defined strong/definitive evidence cardiomyopathy-susceptibility genes, ultra-rare (minor allele frequency ≤ 0.00005 in the Genome Aggregation Database [n=141,456 individuals]) non-synonymous variants identified within these genes were adjudicated independently as P, LP or variant of uncertain significance with the assistance of Varsome. The frequency of P/LP variants was then compared to a previously published cohort of 973 ostensibly healthy control exomes. Results Overall, 56 unrelated patients with suspected AMVPS were identified (82% female; average age at presentation of 31 ± 13 years; 32% with a family history of MVP and/or SCD). Of these, 24/56 (43%) underwent a form of clinical genetic testing that encompassed the pre-defined panel of cardiomyopathy-susceptibility genes. In comparison to control exomes (n=973), P/LP variants in strong/definitive evidence cardiomyopathy-susceptibility genes were over-represented in AMVPS patients [4/24 (16.7%) vs 20/973 (2.1%); p=0.002]. Interestingly, this enrichment was driven in large part by an excess number of A-band-localizing P/LP truncating variants in TTN-encoded titin in AMVPS cases [3/24 (12.5%) versus 4/973 (0.4%); p=0.0004]. Conclusion This study provides further evidence that a subset of AMVPS may arise secondary to a "two-hit" model whereby an underlying cardiomyopathic genetic substrate is exacerbated by the mechanical force generated by genetically unrelated myxomatous MVP resulting in maladaptive and ventricular arrhythmia-predisposing fibrosis within the inferobasal left ventricle and posteromedial papillary muscles. Larger studies are needed to better understand the potential role of genetic testing in the diagnosis, risk-stratification and management of patients with suspected AMVPS.

Background: Multimorbidity is common in atrial fibrillation (AF), particularly among older patients who generally have multiple cardiovascular and non-cardiovascular chronic conditions. However, less is known about the accumulation of chronic conditions in younger patients with AF. Methods: Patients aged <65 with incident AF from 2013-2019 from a 27-county region in the Midwest (N=4907) were matched 1:1 on age (±5 years) and sex to referents from the same community. The index date for the matched pair was the date of first diagnosis of AF. Diagnosis of 20 other chronic conditions was ascertained from 3 years prior to index through 12/31/2022. Mean cumulative function curves were used to visualize the accumulation of conditions; Andersen-Gill models estimated associations between AF/referent status and accumulation of conditions. Results: The mean age was 55 years for both patients with AF and matched referents; 71% were male. In the 3 years leading up to AF diagnosis, only 4% of patients with AF had no additional chronic conditions and 69% had ≥3 chronic conditions. In contrast, 35% of referents had 0 and 32% had ≥3 chronic conditions. The accumulation of chronic conditions was accelerated in patients with AF compared to referents prior to AF diagnosis/index (Figure). After index, patients with AF had increased accumulation of chronic conditions (HR (95% CI): 1.93 (1.71-2.20), 1.82 (1.62-2.05), 1.68 (1.55-1.83), and 1.53 (1.44-1.64) for ages <50, 50-54, 55-59, and 60-64 years, respectively). After 1 year, the differences were attenuated in all age groups with no difference observed between patients with AF and referents in the oldest age group (1.26 (1.08-1.46), 1.28 (1.11-1.47), 1.13 (1.02-1.24), and 1.05 (0.97-1.13) for ages <50, 50-54, 55-59, and 60-64 years). Conclusion: Patients <65 years with AF have an increased accumulation of chronic conditions compared to those without AF, in particular prior to their AF diagnosis and within the first year after AF diagnosis.

Abstract Background Atrial fibrillation (AF) is common in hypertrophic cardiomyopathy (HCM). There is limited data regarding the outcomes of AF catheter ablation in HCM patients. In this study, we aimed to synthesize all available evidence on the effectiveness of ablation of AF in patients with HCM compared to those without HCM. Methods and results We systematically reviewed bibliographic databases to identify studies published through February 2023. We included cohort studies with available quantitative information on rates of recurrent atrial arrhythmias, anti-arrhythmic drug (AAD) therapy, and repeat ablation procedures after initial AF ablation in patients with vs without HCM. Estimates were combined using random-effects meta-analysis models and reported as risk ratios (RR) and 95% confidence intervals (CI). Eight studies were included in quantitative synthesis (262 HCM and 642 non-HCM patients). During median follow-up 13–54 months across studies, AF recurrence rates ranged from 13.3% to 92.9% in HCM and 7.6% to 58.8% in non-HCM patients. The pooled RR for recurrent atrial arrhythmia after the first AF ablation in HCM patients compared to non-HCM controls was 1.498 (95% CI = 1.305–1.720; P &lt; 0.001). During follow-up, HCM patients more often required AAD therapy (RR = 2.844; 95% CI = 1.713–4.856; P &lt; 0.001) and repeat AF ablation (RR = 1.544; 95% CI = 1.070–2.228; P = 0.02). The pooled RR for recurrent atrial arrhythmias after the last AF ablation was higher in patients with HCM than those without HCM (RR = 1.607; 95% CI = 1.235–2.090; P &lt; 0.001). Conclusions Compared to non-HCM patients, those with HCM had higher rates of recurrent atrial arrhythmias, AAD use, and need for repeat AF ablation after initial ablation of AF.

Background: An electrocardiogram (ECG)-based artificial intelligence (AI) algorithm has shown good performance in detecting hypertrophic cardiomyopathy (HCM AI-score). However, its clinical application may be challenging due to the low disease prevalence and potentially high false-positive rate when screening unenriched cohorts. Aims: To identify clinical characteristics associated with false-positive HCM AI-score results to improve screening tool application. Methods: From a cohort of 20,677 patients with a digital 12-lead ECG in routine clinical practice in 2021, we performed a detailed chart review of the 200 patients with highest HCM AI-score to determine their HCM status and collect clinical data. Stepwise forward logistic regression was used to create a clinical variable-based “candidacy for HCM screening” score (CHS score), differentiating true- and likely true-positive from likely false-positive HCM AI-score results. We then validated the CHS score in 200 patients with the highest HCM AI-scores from an independent cohort of 15,147 patients with an ECG in 2022. Results: Among the 200 patients in 2021 (median age 71 years, 48% female), 96 (48%) were likely false-positive HCM AI-score results, 71 (36%) definite or likely true-positive results, and 33 (16%) indeterminate. The CHS score included a history of surgical septal myectomy, coronary artery bypass graft surgery, cardiac valve replacement, and pacemaker, and had an AUC of 0.88 (95% CI 0.83-0.92) for the differentiation of true- versus false-positive AI results. In the 2022 cohort, the CHS score had an AUC of 0.82 (95% CI 0.76 - 0.88). After limiting the cohort to HCM candidates identified by the CHS score, the false-positive results rate was reduced to 27/114 (24%). Conclusions: By applying the CHS score to patients with positive HCM AI-screening results, the false-positive rate decreased from 49% to 24%. Utilizing a clinical model used in tandem with an AI model improved diagnostic yield.

Introduction: Deep-learning artificial intelligence (AI) algorithms can identify hypertrophic cardiomyopathy (HCM) from the electrocardiogram (ECG). Preliminary data indicate that AI-ECG may also track treatment response in HCM patients (pts) receiving mavacamten (Mava). In this placebo-controlled analysis, we investigated the performance of AI-ECG in HCM detection and its changes during Mava treatment compared to placebo in the phase 3, EXPLORER-HCM trial. Methods: Pts with non-paced ECGs enrolled in EXPLORER-HCM, evaluating Mava over 30 weeks of treatment, were included. All pts had a 12-lead ECG pre-treatment, at each study visit, and 8 weeks after treatment end. Two independently developed AI-ECG convolutional neural network algorithms from the Mayo Clinic and the University of California, San Francisco (UCSF) were applied to all ECGs suitable for analysis. Serial AI-ECG-predicted scores, which correlate with HCM likelihood (range 0-1), were examined between Mava and placebo groups. Results: A total of 101 Mava and 110 placebo pts were included (mean age 58.6, female 40%). At baseline, the mean Mayo and UCSF AI-ECG scores for HCM were 0.82 and 0.65, with 94% and 88% of pts exceeding the respective diagnostic thresholds of 0.11 (Mayo) and 0.4 (UCSF). During 30 weeks of follow-up in the Mava group, the algorithms showed a mean AI-ECG score reduction of 0.32 (Mayo) and 0.17 (UCSF) in all pts between start and end of treatment. In comparison, AI-ECG scores decreased by 0.05 (Mayo) and increased by 0.02 (UCSF) in the placebo group (Mava vs placebo, t-test p-values <0.001 for both algorithms; Figure ) Conclusion: In the EXPLORER-HCM trial population, two independent deep-learning AI-ECG algorithms correctly identified most HCM pts and demonstrated significant reductions in predicted HCM scores after treatment with Mava when compared to placebo. This relative normalization of the ECG suggests disease-modifying properties of Mava, deserving further investigation.

Introduction: Cardiac resynchronization therapy (CRT) has known benefit for heart failure (HF) with reduced left ventricular ejection fraction (LVEF) and dyssynchrony. However, very little is known about its benefit in infiltrative cardiomyopathies such as cardiac amyloidosis (CA) due to relative rarity of these conditions. Methods: This retrospective case series (2003-2021) comprised patients with HF due to transthyretin wild-type CA with (case) or without (control) CRT implant. Only controls with an indication for CRT or LVEF <40% were included. To further match disease severity, cases were 1:1 matched (propensity score tolerance 0.04) to controls for age, NYHA class, and CA stage (UK Staging). Primary outcome was MACE (major adverse cardiac events) which included stroke, myocardial infarction, HF hospitalization and cardiac mortality during a 3-year follow-up. Loss to follow-up was censored as per last visit date. LVEF and NYHA were noted closest to 1-year follow-up. Survival analysis for MACE was performed with Kaplan-Meier (KM) and multivariable cox regression models. Results: Study Cohort (n=160) had a mean age of 75.5 (SD 7.8) years and 97.5% were males. A majority had NYHA class 2 or 3 (92.3%) and CA stage 2 (42.2.%). Notably, median LVEF at baseline was lower in controls (33.5 vs 36.5; P = .001) and 77.5% of controls had an indication for CRT device. A total of 79 MACE events occurred, most frequent being HF hospitalization (n=45). KM curves were comparable for MACE events in the two groups (log-rank test; P = .059). Even after adjusting, as in table, CRT device was not associated with MACE events (adjusted HR 0.66; 95% CI 0.40-1.09; P = .106). Lastly, change in LVEF ( P = .84) and NYHA ( P = .86) at follow-up was similar in cases vs controls. Conclusions: The findings of this largest yet observational study to examine this question suggest that CRT in patients with transthyretin wild-type CA does not favorably impact outcomes for MACE events, improve LVEF or NYHA functional class.