Abraham, Theodore P.

Importance Current risk prediction guidelines for hypertrophic cardiomyopathy predict only sudden cardiac death and are imperfect, leading to avoidable deaths and unnecessary implantable cardioverter defibrillators. Objective To combine prospectively collected clinical history, imaging, genetic, and biomarker data to improve risk prediction of adverse events in hypertrophic cardiomyopathy. Design, Setting, and Participants A total of 2750 patients with hypertrophic cardiomyopathy were prospectively enrolled in the registry-based study from 44 sites in North America and Europe with expertise in hypertrophic cardiomyopathy and cardiac magnetic resonance (CMR) imaging. Participants were enrolled from April 1, 2014, to April 7, 2017. Exposures Patients underwent a health history questionnaire, blood sampling for biomarkers and genotyping, and contrast-enhanced CMR. Patients were followed up yearly by telephone and through records review regarding event documentation. Main Outcomes and Measures The predefined composite adjudicated primary end point was time to first event for hypertrophic cardiomyopathy–related deaths; nonfatal sustained ventricular arrhythmias (VAs) requiring cardioversion or defibrillation; and left ventricular (LV) assist device implant or heart transplant. A secondary end point was a composite of sudden cardiac death and nonfatal VA events. The elastic-net method identified the most important predictors. Cox proportional hazards regression assessed associations with time to the first end point. Results Of the 2750 prospectively enrolled patients, 2698 (98%) had analyzable data after 9 were excluded because they had hypertrophic cardiomyopathy phenocopies and 43 withdrew. Of these remaining patients, 1919 (71%) were male, mean age was 50 years (SD, 11 years), and 423 (16%) were from underrepresented racial and minority groups. The mean follow-up was 6.9 years (SD, 2.1 years). The primary event model in 104 patients included LV scar as a percentage of LV mass by late gadolinium enhancement (LGE%; hazard ratio [HR], 1.86; 95% CI, 1.58-2.20; P < .001), LV mass index (HR, 1.09; 95% CI, 1.01-1.17; P = .03), LV end-systolic volume index (HR, 1.28; 95% CI, 1.12-1.46; P < .001 ), all per 10-unit increase, history of heart failure at study entry (HR, 2.89; 95% CI, 1.75-4.77; P < .001), and log N-terminal pro–B-type natriuretic peptide (NT-proBNP; HR, 1.41; 95% CI, 1.17-1.70; P < .001) level per log unit, (C index for all, 0.77). An LGE percentage of the LV mass of 9% or higher substantially increased the primary composite event rate ( P = .001). The secondary sudden cardiac death and VA risk factor model (in 69 patients) included LGE%, LV mass index, LV ejection fraction, and log(NT-proBNP) (C index, 0.76). Conclusions and Relevance These results provide prospective evidence for incorporating cardiac magnetic resonance and NT-proBNP in the evaluation of patients with hypertrophic cardiomyopathy. Trial Registration ClinicalTrials.gov Identifier: NCT01915615

BACKGROUND: Although chronic obstructive pulmonary disease (COPD) and heart failure with preserved ejection fraction often coexist with overlapping clinical features, they are usually studied separately. The SPIROMICS HF (Subpopulations and Intermediate Outcome Measures in COPD and Heart Failure Study) is testing hypotheses that new computed tomography emphysema subtypes are associated with specific cardiovascular phenotypes (eg, cor pulmonale , cor pulmonale parvus ), common airway branch variants are associated with right heart dysfunction, and symptomatic tobacco-exposed persons with preserved spirometry have signs of increased left ventricular afterload. METHODS: SPIROMICS is a multicenter observational study of COPD with extensive pulmonary phenotyping of participants with ≥20 pack-years smoking and nonsmoking controls. COPD and COPD severity were defined by standard spirometric criteria and symptomatic tobacco-exposed persons with preserved spirometry by ≥20 pack-years, normal spirometry, and COPD Assessment Test score >10. SPIROMICS HF selected all participants in SPIROMICS visit 5 at major sites. Its comprehensive speckle-tracking echocardiography, which included physiological perturbations of leg raise and low-intensity exercise, was harmonized prospectively with the Multi-Ethnic Study of Atherosclerosis Early Heart Failure and HeartSHARE (Combining Omics, Deep Phenotyping, and Electronic Health Records for Heart Failure Subtypes and Treatment Targets) studies. The cardiopulmonary magnetic resonance imaging protocol with gadolinium administration included myocardial fibrosis sequences, pulmonary angiography, time-resolved 3-dimensional cine magnetic resonance imaging (4-dimensional flow) of venous return, and metronome-paced tachypnea to induce dynamic hyperinflation. Coronary artery calcium was assessed on computed tomography scans. The Kansas City Cardiomyopathy Questionnaire was administered. RESULTS: Of the final sample of 753 participants, 57% had COPD (15% mild, 27% moderate, and 15% severe), 18% had symptomatic tobacco-exposed persons with preserved spirometry, 16% were smoking controls, and 8% were nonsmoking controls. Reproducibility of the main measures from speckle-tracking echocardiography (intraclass correlation coefficient, 0.83–0.99), exercise echocardiography (intraclass correlation coefficient, 0.71–0.99) and magnetic resonance imaging (intraclass correlation coefficient, 0.57–0.99) were good-to-excellent, including in severe COPD. CONCLUSIONS: SPIROMICS HF aims to characterize and understand cardiopulmonary interactions in COPD and COPD-related phenotypes to inform targeted treatments for combined cardiopulmonary failure.

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: Obstructive hypertrophic cardiomyopathy (oHCM) is characterized by dynamic LV outflow tract (LVOT) obstruction resulting from ventricular hypertrophy and mitral valve systolic anterior motion (SAM), and by elevated left ventricular (LV) filling pressures, all of which result in a significant morbidity despite medical therapy. Mavacamten (Mava) is a novel inhibitor of cardiac myosin that significantly reduces LVOT gradients in oHCM, noted initially in the phase 2 PIONEER and more recently in the phase 3 EXPLORER-HCM studies. Additional echocardiographic analyses were performed to investigate the effect of Mava on focused measures of cardiac structure and function in oHCM. Methods: EXPLORER-HCM (NCT03470545) was a multicenter, double-blind, placebo-controlled, phase 3 study that randomized symptomatic oHCM patients (LV ejection fraction ≥55% and resting and/or provoked LVOT gradient ≥50 mmHg) 1:1 to Mava vs placebo for 30 weeks. Echocardiograms were performed serially every 2-4 weeks over 30 weeks. Results: In total, 251 patients with oHCM were enrolled and 244 patients completed the study (mean age 58.5; 40.6% female). Compared to placebo, 30-week treatment with Mava led to significant reductions in LA volume index (-7.5 ml/m 2 , p<0.0001), lateral E/e’ (-3.8, p<0.0001), septal E/e’ (-3.4, p<0.0001), and LV mass index (-15.5 g/m 2 , p<0.0001) ( Table ). Significantly more Mava-treated patients achieved resolution of mitral valve SAM compared to placebo (80.9% vs 34.0% of patients; difference of 46.8%; p<0.0001) and mitral regurgitation (MR) (9.0% vs 0.0% of patients; difference of 9.0%; p=0.0006). Conclusions: Treatment with Mava for 30 weeks led to improvement in LV hypertrophy and markers of left-sided filling pressures (LA volume and E/e’). Furthermore, Mava treatment was associated with reduction of SAM and MR. These findings suggest that Mava has beneficial effects on several adverse pathophysiologic processes that are hallmarks of oHCM.

Background — Regional myocardial function assessment is essential in the management of coronary artery disease (CAD). Tissue Doppler imaging (TDI) by depicting local myocardial motion can potentially quantify regional myocardial function. Strain rate imaging (SRI) that depicts regional deformation is less susceptible to cardiac translation and tethering and may be superior to TDI for regional function analysis. We examined regional myocardial function using TDI and SRI in a unique clinical model of a small, discrete myocardial infarction. Method and Results — Ten patients with severely symptomatic septal hypertrophy underwent basal septal ablation via intracoronary alcohol injection and had TDI and SRI pre- and postablation. Invasive hemodynamics showed no appreciable change in global function. Peak systolic strain rate was significantly lower postablation versus preablation (−0.5 versus −1.2 s −1 , P <0.001) and when comparing infarct and noninfarct areas (−0.5 versus −1.5 s −1 , P <0.001). In contrast, peak systolic tissue velocities were similar pre- and postablation (3.9 versus 2.9 cm/s, P =0.16) and between infarct and noninfarct areas (2.9 versus 2.2 cm/s, P =0.13). SRI analysis demonstrated reduced systolic function in the peri-infarct zone and preserved systolic function in the remote nonischemic zone. Conclusion — In the clinical setting of a small, discrete infarct unaccompanied by changes in global function, SRI accurately depicted changes in regional function. These data suggest that SRI may be the optimal method for objective, quantitative assessment of regional myocardial dysfunction.