Large scale genome-wide association analyses identify novel genetic loci and mechanisms in hypertrophic cardiomyopathy

Hypertrophic cardiomyopathy (HCM) is an important cause of morbidity and mortality with both monogenic and polygenic components. We here report results from the largest HCM genome-wide association study (GWAS) and multi-trait analysis (MTAG) including 5,900 HCM cases, 68,359 controls, and 36,083 UK Biobank (UKB) participants with cardiac magnetic resonance (CMR) imaging. We identified a total of 70 loci (50 novel) associated with HCM, and 62 loci (32 novel) associated with relevant left ventricular (LV) structural or functional traits. Amongst the common variant HCM loci, we identify a novel HCM disease gene, SVIL, which encodes the actin-binding protein supervillin, showing that rare truncating SVIL variants cause HCM. Mendelian randomization analyses support a causal role of increased LV contractility in both obstructive and non-obstructive forms of HCM, suggesting common disease mechanisms and anticipating shared response to therapy. Taken together, the findings significantly increase our understanding of the genetic basis and molecular mechanisms of HCM, with potential implications for disease management.

Genome-Wide Analysis of Left Ventricular Maximum Wall Thickness in the UK Biobank Cohort Reveals a Shared Genetic Background With Hypertrophic Cardiomyopathy

BACKGROUND

Left ventricular maximum wall thickness (LVMWT) is an important biomarker of left ventricular hypertrophy and provides diagnostic and prognostic information in hypertrophic cardiomyopathy (HCM). Limited information is available on the genetic determinants of LVMWT.

METHODS

We performed a genome-wide association study of LVMWT measured from the cardiovascular magnetic resonance examinations of 42 176 European individuals. We evaluated the genetic relationship between LVMWT and HCM by performing pairwise analysis using the data from the Hypertrophic Cardiomyopathy Registry in which the controls were randomly selected from UK Biobank individuals not included in the cardiovascular magnetic resonance sub-study.

RESULTS

Twenty-one genetic loci were discovered at P<5×10-8. Several novel candidate genes were identified including PROX1, PXN, and PTK2, with known functional roles in myocardial growth and sarcomere organization. The LVMWT genetic risk score is predictive of HCM in the Hypertrophic Cardiomyopathy Registry (odds ratio per SD: 1.18 [95% CI, 1.13-1.23]) with pairwise analyses demonstrating a moderate genetic correlation (rg=0.53) and substantial loci overlap (19/21).

CONCLUSIONS

Our findings provide novel insights into the genetic underpinning of LVMWT and highlight its shared genetic background with HCM, supporting future endeavours to elucidate the genetic etiology of HCM.

Phase 2 Study of Aficamten in Patients With Obstructive Hypertrophic Cardiomyopathy

BACKGROUND

Left ventricular outflow tract (LVOT) obstruction is a major determinant of heart failure symptoms in obstructive hypertrophic cardiomyopathy (oHCM). Aficamten, a next-in-class cardiac myosin inhibitor, may lower gradients and improve symptoms in these patients.

OBJECTIVES

This study aims to evaluate the safety and efficacy of aficamten in patients with oHCM.

METHODS

Patients with oHCM and LVOT gradients ≥30 mm Hg at rest or ≥50 mm Hg with Valsalva were randomized 2:1 to receive aficamten (n = 28) or placebo (n = 13) in 2 dose-finding cohorts. Doses were titrated based on gradients and ejection fraction (EF). Safety and changes in gradient, EF, New York Heart Association functional class, and cardiac biomarkers were assessed over a 10-week treatment period and after a 2-week washout.

RESULTS

From baseline to 10 weeks, aficamten reduced gradients at rest (mean difference: -40 ± 27 mm Hg, and -43 ± 37 mm Hg in Cohorts 1 and 2, P = 0.0003 and P = 0.0004 vs placebo, respectively) and with Valsalva (-36 ± 27 mm Hg and -53 ± 44 mm Hg, P = 0.001 and <0.0001 vs placebo, respectively). There were modest reductions in EF (-6% ± 7.5% and -12% ± 5.9%, P = 0.007 and P < 0.0001 vs placebo, respectively). Symptomatic improvement in ≥1 New York Heart Association functional class was observed in 31% on placebo, and 43% and 64% on aficamten in Cohorts 1 and 2, respectively (nonsignificant). With aficamten, N-terminal pro-B-type natriuretic peptide was reduced (62% relative to placebo, P = 0.0002). There were no treatment interruptions and adverse events were similar between treatment arms.

CONCLUSIONS

Aficamten resulted in substantial reductions in LVOT gradients with most patients experiencing improvement in biomarkers and symptoms. These results highlight the potential of sarcomere-targeted therapy for treatment of oHCM.

Circulating Biomarkers in Hypertrophic Cardiomyopathy

Hypertrophic cardiomyopathy is the most common genetic heart disease. Biomarkers, molecules measurable in the blood, could inform the clinician by aiding in diagnosis, directing treatment, and predicting outcomes. We present an updated review of circulating biomarkers in hypertrophic cardiomyopathy representing key pathologic processes including wall stretch, myocardial necrosis, fibrosis, inflammation, hypertrophy, and endothelial dysfunction, in addition to their clinical significance.

Medicine 2032: The future of cardiovascular disease prevention with machine learning and digital health technology

Machine learning (ML) refers to computational algorithms that iteratively improve their ability to recognize patterns in data. The digitization of our healthcare infrastructure is generating an abundance of data from electronic health records, imaging, wearables, and sensors that can be analyzed by ML algorithms to generate personalized risk assessments and promote guideline-directed medical management. ML's strength in generating insights from complex medical data to guide clinical decisions must be balanced with the potential to adversely affect patient privacy, safety, health equity, and clinical interpretability. This review provides a primer on key advances in ML for cardiovascular disease prevention and how they may impact clinical practice.

Machine learning evaluation of LV outflow obstruction in hypertrophic cardiomyopathy using three-chamber cardiovascular magnetic resonance

Left ventricular outflow tract obstruction (LVOTO) is common in hypertrophic cardiomyopathy (HCM), but relationships between anatomical metrics and obstruction are poorly understood. We aimed to develop machine learning methods to evaluate LVOTO in HCM patients and quantify relationships between anatomical metrics and obstruction. This retrospective analysis of 1905 participants of the HCM Registry quantified 11 anatomical metrics derived from 14 landmarks automatically detected on the three-chamber long axis cine CMR images. Linear and logistic regression was used to quantify strengths of relationships with the presence of LVOTO (defined by resting Doppler pressure drop of > 30 mmHg), using the area under the receiver operating characteristic (AUC). Intraclass correlation coefficients between the network predictions and three independent observers showed similar agreement to that between observers. The distance from anterior mitral valve leaflet tip to basal septum (AML-BS) was most highly correlated with Doppler pressure drop (R2 = 0.19, p < 10-5). Multivariate stepwise regression found the best predictive model included AML-BS, AML length to aortic valve diameter ratio, AML length to LV width ratio, and midventricular septal thickness metrics (AUC 0.84). Excluding AML-BS, metrics grouped according to septal hypertrophy, LV geometry, and AML anatomy each had similar associations with LVOTO (AUC 0.71, 0.71, 0.68 respectively, p = ns), significantly less than their combination (AUC 0.77, p < 0.05 for each). Anatomical metrics derived from a standard three-chamber CMR cine acquisition can be used to highlight risk of LVOTO, and suggest further investigation if necessary. A combination of geometric factors is required to provide the best risk prediction.

Cardiac magnetic resonance defines mechanisms of sex-based differences in outcomes following cardiac resynchronization therapy

Background

Mechanisms of sex-based differences in outcomes following cardiac resynchronization therapy (CRT) are poorly understood.

Objective

To use cardiac magnetic resonance (CMR) to define mechanisms of sex-based differences in outcomes after CRT and describe distinct CMR-based phenotypes of CRT candidates based on sex and non-ischemic/ischemic cardiomyopathy type.

Materials and methods

In a prospective study, sex-based differences in three short-term CRT response measures [fractional change in left ventricular end-systolic volume index 6 months after CRT (LVESVI-FC), B-type natriuretic peptide (BNP) 6 months after CRT, change in peak VO₂ 6 months after CRT], and long-term survival were evaluated with respect to 39 baseline parameters from CMR, exercise testing, laboratory testing, electrocardiograms, comorbid conditions, and other sources. CMR was also used to quantify the degree of left-ventricular mechanical dyssynchrony by deriving the circumferential uniformity ratio estimate (CURE-SVD) parameter from displacement encoding with stimulated echoes (DENSE) strain imaging. Statistical methods included multivariable linear regression with evaluation of interaction effects associated with sex and cardiomyopathy type (ischemic and non-ischemic cardiomyopathy) and survival analysis.

Results

Among 200 patients, the 54 female patients (27%) pre-CRT had a smaller CMR-based LVEDVI (p = 0.04), more mechanical dyssynchrony based on the validated CMR CURE-SVD parameter (p = 0.04), a lower frequency of both late gadolinium enhancement (LGE) and ischemic cardiomyopathy (p < 0.0001), a greater RVEF (p = 0.02), and a greater frequency of LBBB (p = 0.01). After categorization of patients into four groups based on cardiomyopathy type (ischemic/non-ischemic cardiomyopathy) and sex, female patients with non-ischemic cardiomyopathy had the lowest CURE-SVD (p = 0.003), the lowest pre-CRT BNP levels (p = 0.01), the lowest post-CRT BNP levels (p = 0.05), and the most favorable LVESVI-FC (p = 0.001). Overall, female patients had better 3-year survival before adjustment for cardiomyopathy type (p = 0.007, HR = 0.45) and after adjustment for cardiomyopathy type (p = 0.009, HR = 0.67).

Conclusion

CMR identifies distinct phenotypes of female CRT patients with non-ischemic and ischemic cardiomyopathy relative to male patients stratified by cardiomyopathy type. The more favorable short-term response and long-term survival outcomes in female heart failure patients with CRT were associated with lower indexed CMR-based LV volumes, decreased presence of scar associated with prior myocardial infarction and ICM, and greater CMR-based dyssynchrony with the CURE-SVD.

The prognostic value of right ventricular ejection fraction by cardiovascular magnetic resonance in heart failure: A systematic review and meta-analysis

BACKGROUND

Cardiac magnetic resonance (CMR) is considered the gold standard for the assessment of right ventricular ejection fraction (RVEF). Previous studies have suggested that RVEF may be a predictor of adverse outcomes in heart failure (HF). In this study, we aimed to systematically review the prognostic value of RVEF, evaluated by CMR, across the spectrum of left ventricular systolic function in patients with HF.

METHODS

Electronic databases were searched for studies investigating the prognostic value of RVEF in HF, irrespective of left ventricular ejection fraction (LVEF). A random-effects meta-analysis was conducted for mortality and HF hospitalization. Subgroup analyses were also performed based on the presence of reduced (<50%) or preserved LVEF (≥50%).

RESULTS

In total, 46 studies enrolling 14,344 patients were included. In the pooled analyses, impaired RVEF was a powerful predictor of mortality (HR: 1.26, 95% CI: 1.18-1.33, I²: 13%, per 10% decrease in RVEF) and death or HF hospitalization (HR: 1.31, 95% Cl: 1.2-1.42, I²: 27%, per 10% decrease in RVEF). A decrease in RVEF was strongly associated with increased risk of mortality or hospitalization both in HF with reduced EF (HR: 1.24, 95% CI: 1.13-1.36, I²: 2%, per 10% decrease in RVEF) and in HF with preserved EF (HR: 1.24, 95% CI: 1.09-1.40, I²: 0%, per 10% decrease in RVEF).

CONCLUSION

Impaired RVEF on CMR strongly predicts adverse outcomes in patients with HF regardless of LVEF. RV systolic function should be carefully evaluated in these patients. Prospero Registration: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021256967.

Chemical Exchange Saturation Transfer Magnetic Resonance Imaging Identifies Abnormal Calf Muscle-Specific Energetics in Peripheral Artery Disease

BACKGROUND

Peripheral artery disease (PAD) results in exercise-induced ischemia in leg muscles. ³¹Phosphorus (P) magnetic resonance spectroscopy demonstrates prolonged phosphocreatine recovery time constant after exercise in PAD but has low signal to noise, low spatial resolution, and requires multinuclear hardware. Chemical exchange saturation transfer (CEST) is a quantitative magnetic resonance imaging method for imaging substrate (CEST asymmetry [CEST_asym]) concentration by muscle group. We hypothesized that kinetics measured by CEST could distinguish between patients with PAD and controls.

METHODS

Patients with PAD and age-matched normal subjects were imaged at 3T with a transmit-receive coil around the calf. Four CEST mages were acquired over 24-second intervals. The subjects then performed plantar flexion exercise on a magnetic resonance imaging-compatible ergometer until calf exhaustion. Twenty-five CEST images were obtained at end exercise. Regions of interest were drawn around individual muscle groups, and (CEST_asym) decay times were fitted by exponential curve to CEST values. In 10 patients and 11 controls, ³¹P spectra were obtained 20 minutes later after repeat exercise. Five patients and 5 controls returned at a mean of 1±1 days later for repeat CEST studies.

RESULTS

Thirty-five patients with PAD (31 male, age 66±8 years) and 29 controls (11 male, age 63±8 years) were imaged with CEST. The CEST_asym decay times for the whole calf (341±332 versus 153±72 seconds; P<0.03) as well as for the gastrocnemius and posterior tibialis were longer in patients with PAD. Agreement between CEST_asym decay and phosphocreatine recovery time constant was good.

CONCLUSIONS

CEST is a magnetic resonance imaging method that can distinguish energetics in patients with PAD from age-matched normal subjects on a per muscle group basis. CEST agrees reasonably well with the gold standard ³¹P magnetic resonance spectroscopy. Moreover, CEST has higher spatial resolution, creates an image, and does not require multinuclear hardware and thus may be more suitable for clinical studies in PAD.

Machine learning for multidimensional response and survival after cardiac resynchronization therapy using features from cardiac magnetic resonance

Background

Cardiac resynchronization therapy (CRT) response is complex, and better approaches are required to predict survival and need for advanced therapies.

Objective

The objective was to use machine learning to characterize multidimensional CRT response and its relationship with long-term survival.

Methods

Associations of 39 baseline features (including cardiac magnetic resonance [CMR] findings and clinical parameters such as glomerular filtration rate [GFR]) with a multidimensional CRT response vector (consisting of post-CRT left ventricular end-systolic volume index [LVESVI] fractional change, post-CRT B-type natriuretic peptide, and change in peak VO₂) were evaluated. Machine learning generated response clusters, and cross-validation assessed associations of clusters with 4-year survival.

Results

Among 200 patients (median age 67.4 years, 27.0% women) with CRT and CMR, associations with more than 1 response parameter were noted for the CMR CURE-SVD dyssynchrony parameter (associated with post-CRT brain natriuretic peptide [BNP] and LVESVI fractional change) and GFR (associated with peak VO₂ and post-CRT BNP). Machine learning defined 3 response clusters: cluster 1 (n = 123, 90.2% survival [best]), cluster 2 (n = 45, 60.0% survival [intermediate]), and cluster 3 (n = 32, 34.4% survival [worst]). Adding the 6-month response cluster to baseline features improved the area under the receiver operating characteristic curve for 4-year survival from 0.78 to 0.86 (P = .02). A web-based application was developed for cluster determination in future patients.

Conclusion

Machine learning characterizes distinct CRT response clusters influenced by CMR features, kidney function, and other factors. These clusters have a strong and additive influence on long-term survival relative to baseline features.

A Slice-Low-Rank Plus Sparse (slice-L + S) Reconstruction Method for k-t Undersampled Multiband First-Pass Myocardial Perfusion MRI

Purpose

The synergistic use of k‐t undersampling and multiband (MB) imaging has the potential to provide extended slice coverage and high spatial resolution for first‐pass perfusion MRI. The low‐rank plus sparse (L + S) model has shown excellent performance for accelerating single‐band (SB) perfusion MRI.

Methods

A MB data consistency method employing ESPIRiT maps and through‐plane coil information was developed. This data consistency method was combined with the temporal L + S constraint to form the slice‐L + S method. Slice‐L + S was compared to SB L + S and the sequential operations of split slice‐GRAPPA and SB L + S (seq‐SG‐L + S) using synthetic data formed from multislice SB images. Prospectively k‐t undersampled MB data were also acquired and reconstructed using seq‐SG‐L + S and slice‐L + S.

Results

Using synthetic data with total acceleration rates of 6–12, slice‐L + S outperformed SB L + S and seq‐SG‐L + S (N = 7 subjects) with respect to normalized RMSE and the structural similarity index (P < 0.05 for both). For the specific case with MB factor = 3 and rate 3 undersampling, or for SB imaging with rate 9 undersampling (N = 7 subjects), the normalized RMSE values were 0.037 ± 0.007, 0.042 ± 0.005, and 0.031 ± 0.004; and the structural similarity index values were 0.88 ± 0.03, 0.85 ± 0.03, and 0.89 ± 0.02 for SB L + S, seq‐SG‐L + S, and slice‐L + S, respectively (P < 0.05 for both). For prospectively undersampled MB data, slice‐L + S provided better image quality than seq‐SG‐L + S for rate 6 (N = 7) and rate 9 acceleration (N = 7) as scored by blinded experts.

Conclusion

Slice‐L + S outperformed SB‐L + S and seq‐SG‐L + S and provides 9 slice coverage of the left ventricle with a spatial resolution of 1.5 mm × 1.5 mm with good image quality.

DEep learning-based rapid Spiral Image REconstruction (DESIRE) for high-resolution spiral first-pass myocardial perfusion imaging

The objective of the current study was to develop and evaluate a DEep learning-based rapid Spiral Image REconstruction (DESIRE) technique for high-resolution spiral first-pass myocardial perfusion imaging with whole-heart coverage, to provide fast and accurate image reconstruction for both single-slice (SS) and simultaneous multislice (SMS) acquisitions. Three-dimensional U-Net-based image enhancement architectures were evaluated for high-resolution spiral perfusion imaging at 3 T. The SS and SMS MB = 2 networks were trained on SS perfusion images from 156 slices from 20 subjects. Structural similarity index (SSIM), peak signal-to-noise ratio (PSNR), and normalized root mean square error (NRMSE) were assessed, and prospective images were blindly graded by two experienced cardiologists (5: excellent; 1: poor). Excellent performance was demonstrated for the proposed technique. For SS, SSIM, PSNR, and NRMSE were 0.977 [0.972, 0.982], 42.113 [40.174, 43.493] dB, and 0.102 [0.080, 0.125], respectively, for the best network. For SMS MB = 2 retrospective data, SSIM, PSNR, and NRMSE were 0.961 [0.950, 0.969], 40.834 [39.619, 42.004] dB, and 0.107 [0.086, 0.133], respectively, for the best network. The image quality scores were 4.5 [4.1, 4.8], 4.5 [4.3, 4.6], 3.5 [3.3, 4], and 3.5 [3.3, 3.8] for SS DESIRE, SS L1-SPIRiT, MB = 2 DESIRE, and MB = 2 SMS-slice-L1-SPIRiT, respectively, showing no statistically significant difference (p = 1 and p = 1 for SS and SMS, respectively) between L1-SPIRiT and the proposed DESIRE technique. The network inference time was ~100 ms per dynamic perfusion series with DESIRE, while the reconstruction time of L1-SPIRiT with GPU acceleration was ~ 30 min. It was concluded that DESIRE enabled fast and high-quality image reconstruction for both SS and SMS MB = 2 whole-heart high-resolution spiral perfusion imaging.

Cardiovascular Magnetic Resonance for Patients With COVID-19

COVID-19 is associated with myocardial injury caused by ischemia, inflammation, or myocarditis. Cardiovascular magnetic resonance (CMR) is the noninvasive reference standard for cardiac function, structure, and tissue composition. CMR is a potentially valuable diagnostic tool in patients with COVID-19 presenting with myocardial injury and evidence of cardiac dysfunction. Although COVID-19-related myocarditis is likely infrequent, COVID-19-related cardiovascular histopathology findings have been reported in up to 48% of patients, raising the concern for long-term myocardial injury. Studies to date report CMR abnormalities in 26% to 60% of hospitalized patients who have recovered from COVID-19, including functional impairment, myocardial tissue abnormalities, late gadolinium enhancement, or pericardial abnormalities. In athletes post-COVID-19, CMR has detected myocarditis-like abnormalities. In children, multisystem inflammatory syndrome may occur 2 to 6 weeks after infection; associated myocarditis and coronary artery aneurysms are evaluable by CMR. At this time, our understanding of COVID-19-related cardiovascular involvement is incomplete, and multiple studies are planned to evaluate patients with COVID-19 using CMR. In this review, we summarize existing studies of CMR for patients with COVID-19 and present ongoing research. We also provide recommendations for clinical use of CMR for patients with acute symptoms or who are recovering from COVID-19.

Cardiovascular Imaging for Ischemic Heart Disease in Women: Time for a Paradigm Shift

Heart disease is the leading cause of death among men and women. Women have a unique phenotype of ischemic heart disease with less calcified lesions, more nonobstructive plaques, and a higher prevalence of microvascular disease compared with men, which may explain in part why current risk models to detect obstructive coronary artery disease (CAD) may not work as well in women. This paper summarizes the sex differences in the functional and anatomical assessment of CAD in women presenting with stable chest pain and provides an approach for using multimodality imaging for the evaluation of suspected ischemic heart disease in women in accordance to the recently published American Heart Association/American College of Cardiology guidelines for the evaluation and diagnosis of chest pain. A paradigm shift in the approach to imaging ischemic heart disease women is needed including updated risk models, a more profound understanding of CAD in women where nonobstructive disease is more prevalent, and algorithms focused on the evaluation of ischemia with nonobstructive CAD and myocardial infarction with nonobstructive CAD.

Utility of Ischemia Testing Prior to Ablation for Sustained Monomorphic Ventricular Tachycardia

The aim of this study was to determine the relationship between ischemia testing prior to ablation for sustained monomorphic ventricular tachycardia (VT) (SMVT) and post-ablation mortality and VT recurrence. As SMVT is generally caused by myocardial scar and not active ischemia, the utility of ischemia testing prior to SMVT ablation is unclear. Patients who underwent ablation for SMVT at 2 tertiary care centers between January 2016 and July 2018 were included in a retrospective study. A Kaplan-Meier survival analysis was performed, stratifying patients by pre-ablation ischemia testing for the endpoints of mortality and VT recurrence. A Cox multivariable regression analysis was performed to identify predictors of post-ablation VT recurrence. A total of 163 patients were included, with 46 (28%) patients undergoing ischemia testing prior to ablation. Only 5 of the 46 patients (11%) received revascularization pre-ablation. After a median follow-up period of 625 days (interquartile range, 292-982 days) following ablation, 97 of 163 patients (60%) had VT recurrence, and 32 patients (20%) had died. There was no difference in mortality or VT recurrence between patients who did or did not experience ischemia testing or revascularization. In the multivariable regression analysis, predictors of VT recurrence were the number of anti-arrhythmics failed, non-ischemic cardiomyopathy, sex, and cardiac magnetic resonance imaging pre-ablation. Neither ischemia testing nor revascularization was a significant predictor of VT recurrence in univariable or multivariable regression analysis. In conclusion, ischemia testing is frequently ordered prior to SMVT ablation but infrequently leads to revascularization and is not associated with post-ablation outcomes. The findings support adopting an individualized approach rather than performing routine ischemia testing.

Predictors of Major Atrial Fibrillation Endpoints in the National Heart, Lung, and Blood Institute HCMR

OBJECTIVES

This study sought to identify predictors of major clinically important atrial fibrillation endpoints in hypertrophic cardiomyopathy.

BACKGROUND

Atrial fibrillation (AF) is a common morbidity associated with hypertrophic cardiomyopathy (HCM). The HCMR (Hypertrophic Cardiomyopathy Registry) trial is a prospective natural history study of 2,755 patients with HCM with comprehensive phenotyping.

METHODS

All patients received yearly telephone follow-up. Major AF endpoints were defined as requiring electrical cardioversion, catheter ablation, hospitalization for >24 h, or clinical decisions to accept permanent AF. Penalized regression via elastic-net methodology identified the most important predictors of major AF endpoints from 46 variables. This was applied to 10 datasets, and the variables were ranked. Predictors that appeared in all 10 sets were then used in a Cox model for competing risks and analyzed as time to first event.

RESULTS

Data from 2,631 (95.5%) patients were available for analysis after exclusions. A total of 127 major AF endpoints events occurred in 96 patients over 33.3 ± 12.4 months. In the final model, age, body mass index (BMI), left atrial (LA) volume index, LA contractile percent (active contraction), moderate or severe mitral regurgitation (MR), and history of arrhythmia the most important. BMI, LA volume index, and LA contractile percent were age-dependent. Obesity was a stronger risk factor in younger patients. Increased LA volume, reduced LA contractile percent, and moderate or severe MR put middle-aged and older adult patients at increased risk.

CONCLUSIONS

The major predictors of major AF endpoints in HCM include older age, high BMI, moderate or severe MR, history of arrhythmia, increased LA volume, and reduced LA contractile percent. Prospective testing of a risk score based on these parameters may be warranted.