Citations

Abstract Background and Aims Incidence and types of secondary tricuspid regurgitation (TR) are not well defined in atrial fibrillation (AFib) and sinus rhythm (SR). Atrial secondary TR (A-STR) is associated with pre-existing AFib; however, close to 50% of patients with A-STR do not have AFib. The aim of this study was to assess incidence, types, and outcomes of ≥ moderate TR in AFib vs. SR. Methods Adults with and without new-onset AFib without structural heart disease or ≥ moderate TR at baseline were followed for the development of ≥ moderate TR. Tricuspid regurgitation types were pacemaker, left-sided valve disease, left ventricular (LV) dysfunction, pulmonary hypertension (PH), isolated ventricular, and A-STR. Results Among 1359 patients with AFib and 20 438 in SR, 109 and 378 patients developed ≥ moderate TR, respectively. The individual types of TR occurred more frequently in AFib related to the higher pacemaker implantation rates (1.12 vs. 0.19 per 100 person-years, P < .001), larger right atrial size (median 78 vs. 53 mL, P < .001), and higher pulmonary pressures (median 30 vs. 28 mmHg, P < .001). The most common TR types irrespective of rhythm were LV dysfunction-TR and A-STR. Among patients in SR, those with A-STR were older, predominantly women with more diastolic abnormalities and higher pulmonary pressures. All types of secondary TR were associated with all-cause mortality, highest in PH-TR and LV dysfunction-TR. Conclusions New-onset AFib vs. SR conferred a higher risk of the individual TR types related to sequelae of AFib and higher pacemaker implantation rates, although the distribution of TR types was similar. Secondary TR was universally associated with increased mortality.

Abstract Background and Aims Arrhythmic mitral valve prolapse (AMVP) is linked to life-threatening ventricular arrhythmias (VAs), and young women are considered at high risk. Cases of AMVP in women with malignant VA during pregnancy have emerged, but the arrhythmic risk during pregnancy is unknown. The authors aimed to describe features of women with high-risk AMVP who developed malignant VA during the perinatal period and to assess if pregnancy and the postpartum period were associated with a higher risk of malignant VA. Methods This retrospective international multi-centre case series included high-risk women with AMVP who experienced malignant VA and at least one pregnancy. Malignant VA included ventricular fibrillation, sustained ventricular tachycardia, or appropriate shock from an implantable cardioverter defibrillator. The authors compared the incidence of malignant VA in non-pregnant periods and perinatal period; the latter defined as occurring during pregnancy and within 6 months after delivery. Results The authors included 18 women with AMVP from 11 centres. During 7.5 (interquartile range 5.8–16.6) years of follow-up, 37 malignant VAs occurred, of which 18 were pregnancy related occurring in 13 (72%) unique patients. Pregnancy and 6 months after delivery showed increased incidence rate of malignant VA compared to the non-pregnancy period (univariate incidence rate ratio 2.66, 95% confidence interval 1.23–5.76). Conclusions The perinatal period could impose increased risk of malignant VA in women with high-risk AMVP. The data may provide general guidance for pre-conception counselling and for nuanced shared decision-making between patients and clinicians.

Introduction: Asymptomatic LV systolic dysfunction is often underdiagnosed, leading to missed opportunities for treatment. In a recently completed pragmatic RCT, an AI algorithm performed on the ECGs ordered as part of routine practice increased early diagnosis of low EF. The current study aimed to understand whether the effectiveness of the AI algorithm integrated into routine care differed by the socioeconomic status of the patient. Methods: The main findings of the RCT were previously published. Clinicians in the intervention group had access to AI results (i.e., a positive or negative screening result, with positive results indicating a high likelihood of low EF). When a positive result was found, clinicians in the intervention group received an alert that encouraged them to order TTE if considered clinically appropriate. Clinicians in the control group did not have access or received alerts. Area deprivation index (ADI) was used to measure area-level social determinants of health. This study included 16,992 patients (control 8,225; intervention: 8,767) who had ECG performed for any indications between 8/5/2019 and 3/31/2020, no prior HF, and a valid address to derive ADI. The primary endpoint was a new diagnosis of EF≤50% within 3 months. Results: The mean age was 60.5±17.6 y. AI increased the diagnosis of low EF in the overall cohort (OR 1.42 [1.13, 1.78], p=0.01). The magnitude of benefit was greater in patients with higher socioeconomic status, e.g., living in an area that is less deprived (OR 1.88 [1.16, 3.05]), with higher median income, lower poverty rate, higher education level, better housing conditions, and higher proportion of white-collar workers, although the interaction was not statistically significant (Figure). Conclusions: AI enables early diagnosis of low EF and the magnitude of benefit might be numerically greater in patients with higher socioeconomic status, possibly due to variations in access to or referral for subsequent testing.

Abstract Aims Mobile devices such as smartphones and watches can now record single-lead electrocardiograms (ECGs), making wearables a potential screening tool for cardiac and wellness monitoring outside of healthcare settings. Because friends and family often share their smart phones and devices, confirmation that a sample is from a given patient is important before it is added to the electronic health record. Methods and results We sought to determine whether the application of Siamese neural network would permit the diagnostic ECG sample to serve as both a medical test and biometric identifier. When using similarity scores to discriminate whether a pair of ECGs came from the same patient or different patients, inputs of single-lead and 12-lead medians produced an area under the curve of 0.94 and 0.97, respectively. Conclusion The similar performance of the single-lead and 12-lead configurations underscores the potential use of mobile devices to monitor cardiac health.

Abstract Aims Recently, deep learning artificial intelligence (AI) models have been trained to detect cardiovascular conditions, including hypertrophic cardiomyopathy (HCM), from the 12-lead electrocardiogram (ECG). In this external validation study, we sought to assess the performance of an AI-ECG algorithm for detecting HCM in diverse international cohorts. Methods and results A convolutional neural network-based AI-ECG algorithm was developed previously in a single-centre North American HCM cohort (Mayo Clinic). This algorithm was applied to the raw 12-lead ECG data of patients with HCM and non-HCM controls from three external cohorts (Bern, Switzerland; Oxford, UK; and Seoul, South Korea). The algorithm’s ability to distinguish HCM vs. non-HCM status from the ECG alone was examined. A total of 773 patients with HCM and 3867 non-HCM controls were included across three sites in the merged external validation cohort. The HCM study sample comprised 54.6% East Asian, 43.2% White, and 2.2% Black patients. Median AI-ECG probabilities of HCM were 85% for patients with HCM and 0.3% for controls (P < 0.001). Overall, the AI-ECG algorithm had an area under the receiver operating characteristic curve (AUC) of 0.922 [95% confidence interval (CI) 0.910–0.934], with diagnostic accuracy 86.9%, sensitivity 82.8%, and specificity 87.7% for HCM detection. In age- and sex-matched analysis (case–control ratio 1:2), the AUC was 0.921 (95% CI 0.909–0.934) with accuracy 88.5%, sensitivity 82.8%, and specificity 90.4%. Conclusion The AI-ECG algorithm determined HCM status from the 12-lead ECG with high accuracy in diverse international cohorts, providing evidence for external validity. The value of this algorithm in improving HCM detection in clinical practice and screening settings requires prospective evaluation.

Introduction: Artificial intelligence applied to electrocardiograms (ECG-AI) enables early and efficient detection of cardiovascular disease. The technical and clinical impact of different approaches to designing ECG-AI remains under-explored. We consider left ventricular hypertrophy (LVH) and examine the impact of disease-specific labeling of minority etiologies of left ventricular wall thickening- hypertrophic cardiomyopathy (HCM) and cardiac amyloidosis (CA) - on ECG-AI performance. Hypothesis: ECG-AI designed to detect HCM or CA outperforms ECG-AI broadly trained to identify LVH due to differences in attention to key ECG features associated with HCM or CA. Methods: Independent neural networks were trained to identify HCM, CA, and LVH. HCM and CA patients were identified using the full depth of EHR data and validated via clinician adjudication (N = 3,025 and 4,251 patients, respectively). Moderate and severe LVH patients (N = 98,144) were identified using echocardiogram results and international LVH criteria. We compared the ability of disease-specific ECG-AI vs. LVH ECG-AI to detect HCM (or CA) by examining model performance within each of the three test sets. Results: 52.6% of HCM patients and 49.5% of CA patients met LVH criteria. Within the HCM test set, the AUROC, sensitivity, specificity, and positive predictive value (PPV) of the HCM ECG-AI were 0.94, 0.88, 0.85, and 60%, respectively, whereas the same for LVH ECG-AI were 0.83, 0.83, 0.64, and 37%. Within the CA test set, CA ECG-AI achieved AUROC, sensitivity, specificity, and PPV of 0.94, 0.81, 0.91, and 69%, respectively, whereas the same for LVH ECG-AI were 0.75, 0.73, 0.68, and 31%. ECGs positive for HCM exhibited higher P wave area, QRS deflection and R wave amplitude compared to LVH-positive ECGs (Cohen's D > 0.75). ECGs positive for CA exhibited lower R wave amplitude/area, QRS deflection and QRS areas (Cohen's D > 0.6). Conclusion: Models trained using carefully labeled HCM or CA identify distinct signals associated with the diseases, resulting in improved disease discrimination compared to a model trained to identify echocardiographic left ventricular thickening. Labeling choices should be communicated transparently to clinicians to ensure safe and effective use of ECG-AI.

Introduction: Disease-causative variants in LMNA -encoded lamin A/C cause a penetrant dilated cardiomyopathy associated with conduction disease (CD) and ventricular arrhythmias (VA). Prior studies show conflicting results regarding the effect of sex, variant type, and CD on severity and sudden death risk in cardiac laminopathy. Methods: In this retrospective study, we utilized a single-center genetic arrhythmogenic cardiomyopathy registry (N=432) to identify patients with ultra-rare LMNA variants and ascertain the effect of sex, mutation type, and clinical presentation on disease severity. Advanced heart failure (AHF) events were defined as ventricular assist device placement or cardiac transplantation whereas VA events were defined as sudden cardiac arrest, sustained ventricular arrhythmia, or appropriate implantable cardioverter-defibrillator shock. Results: The LMNA variant-positive cohort (N=83) had an age of diagnosis of 36 ± 10 years with 80% showing a cardiac phenotype. No difference in the age at diagnosis (37 vs. 34 years; p=0.3) or prevalence of AHF events (14% vs. 18%; p=0.8) and VA events (34% vs. 36%; p=0.9) was observed between females (N=50) and males (N=33). Furthermore, there was no difference in age of diagnosis (37 vs. 33 years; p=0.1) or prevalence of AHF (14% vs. 12%; p=0.9) and VA events (33% vs. 34%; p=0.9) between individuals with missense (N=42) or frameshift (N=32) variants. Interestingly, in comparison to individuals that presented with isolated CD (N=11) those that first presented with left ventricular dysfunction or arrhythmias (atrial or ventricular) (N=41) were more likely to have VA events (9% vs. 53%; p=0.01) and AHF events (0% vs 29%; p=0.05). In addition, those with structural/arrhythmic presentation had earlier time to VA events (15 years vs. 22 years; p=0.04) and AHF events (23 vs undefined; p=0.09) than those with CD. Conclusions: Contrary to prior studies, in this large single-center cardiac laminopathy study, sex and mutation type were not associated with increased risk of AHF or VA events. However, patients presenting with isolated CD had a lower risk of AHF and VA events. Contemporary multi-center studies are needed to better ascertain risk factors associated with AHF and VA events in cardiac laminopathy.

Background: Catheter ablation is an effective tool to reduce ventricular tachycardia (VT) burden. There is a lack of robust data studying the characteristics and outcomes of VT ablation in patients with ischemic (ICM) versus non-ischemic cardiomyopathy (NICM). Aims: The aim of this study was to assess the impact of ICM vs NICM on outcomes of VT ablation. Methods: A single-center, retrospective study of patients undergoing catheter ablation for VT was conducted. Results: A total of 168 patients, undergoing 200 VT ablation procedures, were included in this study. NICM group (112 procedures) was compared to ICM group (88 procedures). Patients in the ICM group were older (66.6 ± 13.4 vs 58.9 ± 14.4 years) and had higher rates of prior myocardial infarction (65.9% vs 3.6) and coronary artery bypass graft surgery (40.9% vs 1.8%). Overall, ICM group had more comorbidities like hypertension (80.7% vs 52.7%), diabetes mellitus (23.9% vs 12.5%), chronic kidney disease (45.5% vs 35.7%), stroke (17% vs 7.1%), and lower left ventricular ejection fraction (36.8 ± 13.2% vs 43.1 ± 14.7%). The ICM group had lower incidence of prior cardiac valvular surgery (9.1% vs 29.5%). The inducibility of VT (93% vs 93.5%; p= 1.0) and the number of different VT morphologies induced during the case (1.9 ± 1.5 vs 2.3 ± 2.5; p=0.19) was similar between the two groups. There was no acute mortality in either group. There was a non-significant trend towards greater VT recurrence in the NICM group (43.2% vs 33.3%, p= 0.19). However, patients with NICM had a lower VT-free survival as determined by Kaplan-Meier analysis (p=0.05) [Figure]. Long term mortality was higher in ICM group when compared to NICM group (18.2% vs 8.9%, p<0.01). Conclusion: Patients undergoing VT ablation in the NICM group when compared to the ICM group were noted to be younger, had fewer comorbidities, and lower long-term mortality. However, they had significantly less VT-free survival, likely owing to more challenging substrate responsible for VT.

Introduction: Advanced imaging with cardiac magnetic resonance (CMR) or computed tomography (CCT) can be helpful for planning of ventricular tachycardia (VT) ablation procedures by defining the arrhythmogenic substrate. The frequency with which these modalities are utilized in the pre-ablation setting and the associated outcomes remain poorly studied. Objectives: (1) Determine the utilization of advanced cardiac imaging prior to structural VT ablation; (2) establish factors associated with improved VT ablation outcomes Methods: We retrospectively evaluated all VT ablations performed in patients with structural heart disease at a tertiary referral institution during a 2.5 year period (1/2020 - 7/2022). We documented pre-ablation use of cardiac imaging modalities and investigated their association with acute and long-term ablation outcomes. The primary outcome was time to VT recurrence, cardiac transplant, or death. Results: Our dataset included n = 129 subjects. Median post-ablation follow-up was 17 months. Recent echocardiogram, CMR, or CCT (<3 months pre-ablation) had been performed in 113 (88%), 48 (37%), and 31 (24%) patients, respectively. CMR was not associated with procedural success, post-ablation VT recurrence (p = 1), or the composite primary outcome (p = 0.72). Similarly, recent CCT was not associated with procedural success (p = 0.5), VT recurrence (p = 0.3), or the composite primary outcome (p = 0.31). When adjusted for other variables, EF (p = 0.048), recent echo (p = 0.02), and procedural success (p = 0.013) were associated with the primary outcome, but recent CCT (p = 0.11) and CMR (p = 0.4) were not. These results did not differ significantly in patients with ischemic and non-ischemic cardiomyopathy. Conclusions: In this large tertiary care ablation center, CMR and CCT were utilized in only a fraction of patients prior to VT ablations. In multivariate analysis, CMR or CCT were not associated with improved acute or long-term ablation outcomes.