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OBJECTIVESTo elucidate the optimal septal reduction therapy for obstructive hypertrophic cardiomyopathy, we conducted a meta-analysis comparing alcohol septal ablation (ASA) and septal myectomy.METHODSMEDLINE, EMBASE and Cochrane CENTRAL were searched to identify studies investigating the outcomes of ASA and septal myectomy in patients with obstructive hypertrophic cardiomyopathy in January 2023. The primary outcome of interest was all-cause mortality in studies with ≥1 year of follow-up. The secondary outcomes of interest comprised left ventricular outflow tract (LVOT) pressure gradient reduction and reoperations of LVOT. A subgroup analysis of all-cause mortality including studies with follow-up ≥5 years was performed.RESULTS27 observational studies were included (15 968 patients). Analysis demonstrated similar all-cause mortality [hazard ratio (HR) (95% confidence interval) (CI) 1.24 (0.88–1.76); P = 0.21; I2 = 56%]. In contrast, ASA was associated with less reduction of LVOT pressure gradient and a reoperation rate [weighted mean difference (95% CI) 11.04 mmHg (5.60–16.48); P CONCLUSIONSAlthough both septal reduction therapies were associated with similar all-cause mortality, ASA was associated with a higher rate of reoperation and less reduction of LVOT pressure gradient. Furthermore, all-cause mortality with follow-up ≥5 years showed favourable outcomes with septal myectomy, although the result is only hypothesis-generating given a subgroup analysis.

Background: Hypertrophic cardiomyopathy often causes major adverse cardiovascular events (MACE), for example, arrhythmias, stroke, heart failure, and sudden cardiac death. Currently, there are no models available to predict MACE. Furthermore, it remains unclear which signaling pathways mediate MACE. Therefore, we aimed to prospectively determine protein biomarkers that predict MACE in hypertrophic cardiomyopathy and to identify signaling pathways differentially regulated in patients who subsequently develop MACE. Methods: In this multi-centre prospective cohort study of patients with hypertrophic cardiomyopathy, we conducted plasma proteomics profiling of 4979 proteins upon enrollment. We developed a proteomics-based model to predict MACE using data from one institution (training set). We tested the predictive ability in independent samples from the other institution (test set) and performed time-to-event analysis. Additionally, we executed pathway analysis of predictive proteins using a false discovery rate threshold of Results: The study included 245 patients (n=174 in the training set and n=71 in the test set). Using the proteomics-based model to predict MACE derived from the training set, the area under the receiver-operating-characteristic curve was 0.81 (95% CI, 0.68–0.93) in the test set. In the test set, the high-risk group determined by the proteomics-based predictive model had a significantly higher rate of developing MACE (hazard ratio, 13.6 [95% CI, 1.7–107]; P =0.01). The Ras -MAPK (mitogen-activated protein kinase) pathway was upregulated in patients who subsequently developed MACE (false discovery rate-7 ). Pathways involved in inflammation and fibrosis—for example, the TGF (transforming growth factor)-β pathway—were also upregulated. Conclusions: This study serves as the first to demonstrate the ability of proteomics profiling to predict MACE in hypertrophic cardiomyopathy, exhibiting both novel (eg, Ras -MAPK) and known (eg, TGF-β) pathways differentially regulated in patients who subsequently experience MACE.

Septal reduction therapy (SRT) -i.e. septal myectomy and alcohol septal ablation-has been performed to treat medically refractory hypertrophic cardiomyopathy (HCM) for decades. However, it is largely unknown whether SRT prevents HCM-related cardiovascular events or death. The objective was to examine the effects of SRT on acute cardiovascular events and all-cause mortality in HCM. We performed a propensity score (PS) -matched study using databases that capture all hospitalizations and outpatient visits in New York state. We identified patients with HCM who underwent SRT between 2007 and 2014 (i.e. the SRT group) and those who had never had SRT but had at least one hospitalization for HCM during the same period (i.e. the control group). We performed PS matching at a 1:1 ratio. The primary outcome was a composite of acute cardiovascular events and all-cause mortality during 0-180 days and 181-360 days. The secondary outcome was 180- and 360-day all-cause mortality. We included 846 patients with HCM (423 PS-matched pairs). Patients who underwent SRT had a lower risk of the primary outcome event (0-180 days: odds ratio [OR], 0.54; 95% confidence intervals (CI), 0.37-0.80; P = 0.002 and 181-360 days: OR, 0.33; 95% CI, 0.22-0.51; P < 0.0001). Furthermore, the risk of all-cause mortality was lower at 180 days (OR, 0.37; 95% CI, 0.22-0.63; P = 0.0003) and 360 days post-SRT (OR, 0.32; 95% CI, 0.20-0.51; P < 0.0001). In conclusion, our PS-matched study using population-based datasets demonstrated that SRT was associated with a reduced risk of a composite of acute cardiovascular events and all-cause mortality in HCM during the first post-SRT year.

Endotyping is an emerging concept in which diseases are classified into distinct subtypes based on underlying molecular mechanisms. Heart failure (HF) is a complex clinical syndrome that encompasses multiple endotypes with differential risks of adverse events, and varying responses to treatment. Identifying these distinct endotypes requires molecular-level investigation involving multi-"omics" approaches, including genomics, transcriptomics, proteomics, and metabolomics. The derivation of these HF endotypes has important implications in promoting individualized treatment and facilitating more targeted selection of patients for clinical trials, as well as in potentially revealing new pathways of disease that may serve as therapeutic targets. One challenge in the integrated analysis of high-throughput omics and detailed clinical data is that it requires the ability to handle "big data", a task for which machine learning is well suited. In particular, unsupervised machine learning has the ability to uncover novel endotypes of disease in an unbiased approach. In this review, we will discuss recent efforts to identify HF endotypes and cover approaches involving proteomics, transcriptomics, and genomics, with a focus on machine-learning methods.

It is unclear how hypertrophic cardiomyopathy (HCM) affects cardiac metabolic pathways at rest and with exercise. This case–control study compared 15 cases with HCM to 2 control groups without HCM. Metabolomic profiling of 210 metabolites was carried out at rest and at peak exercise. The 50 most discriminant metabolites differentially regulated during exercise were selected using partial least squares discriminant analysis. Pathway enrichment analysis was also performed. At rest, no significant difference was observed in metabolomic profiling of HCM cases as compared to controls. By contrast, there were significant differences in metabolomic profiling in response to exercise (p

In 2011, a multidisciplinary hypertrophic cardiomyopathy (HCM) program with a dedicated myectomy surgeon was implemented at our institution. We hypothesized that a dedicated approach allows better identification and management of mitral regurgitation (MR) during septal myectomy (SM) for obstructive HCM with significant mitral regurgitation. Between 2006 and 2018, 181 patients had SM at our institution. This study consists of 53 patients with preoperative moderate or greater MR associated with systolic anterior motion who underwent isolated SM with or without mitral intervention. Patients were divided into those who underwent SM by a dedicated myectomy surgeon (group D, n = 31) or by a non-dedicated surgeon (group ND, n = 22). Primary outcome of interest was rate of mitral valve replacement (MVR) at SM. Secondary outcomes include in-hospital mortality, need for permanent pacemaker, mitral valve reoperation, and residual MR and left ventricular outflow tract gradient on postoperative echocardiography. 12 patients (55%) had a concomitant MVR during septal myectomy in group ND compared to 2 patients (6%) in group D (p

Objective: Mitral regurgitation (MR) induced by systolic anterior motion in patients with hypertrophic cardiomyopathy (HCM) can frequently be abolished with a proficient septal myectomy (SM) without the need for mitral-valve replacement (MVR). ACC guidelines stress the importance of volume in improving outcomes after SM, but there is a lack of data measuring the impact of volume on the need for MVR during SM. This study was designed to assess the impact of institutional volume on MVR rates using national outcomes data. Methods: The Nationwide Inpatient Sample was queried from 1998 to 2011 and a total of 6,207 patients had a diagnosis of HCM and a procedure code for SM. Outcomes were compared between patients who underwent SM (group I) and SM and MVR (group II). Furthermore, patients were stratified into 3 groups based on the number of SMs at the performing institution: low experience (1–24 cumulative SMs), medium experience (25–49 SMs), and high experience (>50 SMs). These patients underwent multivariable analysis to determine the impact of institutional volume on MVR rate. Results: The total MVR rate was 26%. Perioperative outcomes were worse, i.e., there were higher rates of mortality, kidney injury, and urinary complications, in group II than in group I. Only 37.6% of patients were operated on at institutions meeting the guideline criteria of >50 cumulative SMs. When compared to patients in the high-experience group, patients in the low- (OR 2.7, 95% CI 2.3–3.2, p < 0.05) and medium-experience (OR 3.0, 95% CI 2.5–3.6, p < 0.05) groups were more likely to undergo MVR. Conclusion: Compared to reports from SM reference centers, national data suggest that MVR rates are quite high at SM. Patients undergoing SM at centers that do not meet the guideline standard have >2.5× the odds of undergoing MVR compared to those operated on at guideline-endorsed centers.

ObjectiveHypertrophic cardiomyopathy (HCM) is a heterogeneous disease, likely encompassing several subtypes of disease with distinct biological mechanisms (ie, molecular subtypes). Current models based solely on clinical data have yielded limited accuracy in predicting the risk of major adverse cardiovascular events (MACE). Our aim in this study was to derive molecular subtypes in our multicentre prospective cohort of patients with HCM using proteomics profiling and to examine their longitudinal associations with MACE.MethodsWe applied unsupervised machine learning methods to plasma proteomics profiling data of 1681 proteins from 258 patients with HCM who were prospectively followed for a median of 2.8 years. The primary outcome was MACE, defined as a composite of arrhythmia, heart failure, stroke and sudden cardiac death.ResultsWe identified four molecular subtypes of HCM. Time-to-event analysis revealed significant differences in MACE-free survival among the four molecular subtypes (plogrank=0.007). Compared with the reference group with the lowest risk of MACE (molecular subtype A), patients in molecular subtype D had a higher risk of subsequently developing MACE, with an HR of 3.41 (95% CI 1.54 to 7.55, p=0.003). Pathway analysis of proteins differentially regulated in molecular subtype D demonstrated an upregulation of the Ras/mitogen-activated protein kinase and associated pathways, as well as pathways related to inflammation and fibrosis (eg, transforming growth factor-β pathway).ConclusionsOur prospective plasma proteomics study not only exhibited the presence of HCM molecular subtypes but also identified pathobiological mechanisms associated with a distinct high-risk subtype of HCM.

Background: Hypertrophic cardiomyopathy (HCM) is caused by mutations in the genes essential in normal myocardial contraction. However, it remains unclear through which signaling pathways gene mutations mediate the development of HCM. Growing evidence indicates that small non-coding RNAs (snRNAs) play important roles in post-transcriptional regulation of gene expression. Hypothesis: Comprehensive sequencing of snRNAs in plasma reveals circulating HCM biomarkers and differentially regulated signaling pathways. Methods: We conducted a multicenter case-control study of cases with HCM and age-, sex-, and body mass index-matched controls with hypertensive left ventricular hypertrophy. We carried out RNA-seq of 3293 snRNAs in plasma. We performed a sparse partial least squares discriminant analysis to develop snRNA-based discrimination model using samples retrieved during the first two-thirds of the study period (the training set). We prospectively tested the discriminative ability in independent samples that were collected thereafter (the test set). We also identified signaling pathways associated with snRNAs that were significantly dysregulated in HCM with Bonferroni-adjusted P Results: The study included 324 patients (165 cases and 159 controls; n=224 in the training set, n=100 in the test set). Using the transcriptomics-based model derived from the training set, the area under the receiver-operating-characteristic curve in the test set was 0.89 (95%CI 0.81-0.96; Figure ). Pathway analysis revealed that the Ras-MAPK pathway was upregulated in HCM (false discovery rate [FDR]=0.000002). Pathways involved in inflammation and fibrosis - e.g., TNF (FDR=0.000003) and TGF-β (FDR=0.002) - were also upregulated. Conclusions: This study serves as the largest-scale investigation to reveal circulating snRNA biomarkers of HCM and exhibits both novel (e.g., Ras-MAPK) and known (e.g., TNF, TGF-β) pathways that are differentially regulated in HCM.

Background Prior studies have suggested causal relationships between obesity and acute cardiovascular events (e.g., acute coronary syndrome, hypertensive crisis, and heart failure exacerbation). It has been known that the risk of cardiovascular events is reduced by bariatric surgery, the most effective method for substantial and sustained weight loss. However, little is known about whether bariatric surgery lowers the risk of acute cardiovascular events in the hypertrophic cardiomyopathy (HCM) population. Purpose To test the hypothesis that patients with obesity and HCM who underwent bariatric surgery have lower risk of developing acute cardiovascular events than those who did not. Methods In this population-based study of adults with obesity and HCM, the bariatric surgery group consisted of patients who underwent bariatric surgery from January 2004 to December 2014, whereas the control group included those who received non-bariatric elective intra-abdominal surgery during the same period. The outcome was an acute cardiovascular event – defined as emergency department (ED) visit or unplanned hospitalization for cardiovascular disease – during a 1-year post-surgery period. We used the SPARCS database, a population-based ED and inpatient database that captures all the ED visits and hospitalizations in New York State. We constructed logistic regression models with generalized estimating equations to compare the risk of the outcome events during sequential 6-month periods. We conducted multivariable analysis, adjusting for age, sex, number of ED visits and hospitalizations for cardiovascular disease within 2 years before the index surgery, and the Elixhauser comorbidity measures. We also performed additional analyses with propensity score (PS)-matching at 2:1 ratio and inverse probability treatment weighting (IPTW) using these variables. Results The analytic cohort consisted of 207 adults with obesity and HCM, including 147 patients who underwent bariatric surgery and 60 who had non-bariatric elective intra-abdominal surgery. In the 7–12 months post-surgery period, the risk of acute cardiovascular event was significantly lower in the bariatric surgery group (adjusted OR 0.23; 95% CI, 0.068–0.71; P=0.01; Figure) compared to the control group. In the PS-matched cohort (n=82 vs. 47), there were no significant differences in the baseline characteristics (P>0.50 for all comparisons). Similar to the main analysis, the PS-matched analysis demonstrated lower risk of the outcome event in the bariatric surgery group in the 7–12 months post-surgery period (OR 0.26; 95% CI, 0.083–0.73; P=0.01). The IPTW analysis also replicated the findings (OR 0.33; 95% CI, 0.16–0.71; P=0.004 during the 7–12 months post-surgery period). Conclusion In this population-based study of 207 adults with obesity and HCM, bariatric surgery was associated with a lower risk of acute cardiovascular events in the 7–12 months post-surgery period in real-world settings. Funding Acknowledgement Type of funding sources: Public grant(s) – National budget only. Main funding source(s): National Institute of Health (USA) and American Heart Association

Septal reduction therapy (SRT) -i.e. septal myectomy and alcohol septal ablation-has been performed to treat medically refractory hypertrophic cardiomyopathy (HCM) for decades. However, it is largely unknown whether SRT prevents HCM-related cardiovascular events or death. The objective was to examine the effects of SRT on acute cardiovascular events and all-cause mortality in HCM. We performed a propensity score (PS) -matched study using databases that capture all hospitalizations and outpatient visits in New York state. We identified patients with HCM who underwent SRT between 2007 and 2014 (i.e. the SRT group) and those who had never had SRT but had at least one hospitalization for HCM during the same period (i.e. the control group). We performed PS matching at a 1:1 ratio. The primary outcome was a composite of acute cardiovascular events and all-cause mortality during 0-180 days and 181-360 days. The secondary outcome was 180- and 360-day all-cause mortality. We included 846 patients with HCM (423 PS-matched pairs). Patients who underwent SRT had a lower risk of the primary outcome event (0-180 days: odds ratio [OR], 0.54; 95% confidence intervals (CI), 0.37-0.80; P = 0.002 and 181-360 days: OR, 0.33; 95% CI, 0.22-0.51; P0.0001). Furthermore, the risk of all-cause mortality was lower at 180 days (OR, 0.37; 95% CI, 0.22-0.63; P = 0.0003) and 360 days post-SRT (OR, 0.32; 95% CI, 0.20-0.51; P0.0001). In conclusion, our PS-matched study using population-based datasets demonstrated that SRT was associated with a reduced risk of a composite of acute cardiovascular events and all-cause mortality in HCM during the first post-SRT year.

Background: Hypertrophic cardiomyopathy (HCM) is caused by mutations in the genes coding for proteins essential in normal myocardial contraction. However, it remains unclear through which molecular pathways gene mutations mediate the development of HCM. The objectives were to determine plasma protein biomarkers of HCM and to reveal molecular pathways differentially regulated in HCM. Methods: We conducted a multicenter case-control study of cases with HCM and controls with hypertensive left ventricular hypertrophy. We performed plasma proteomics profiling of 1681 proteins. We performed a sparse partial least squares discriminant analysis to develop a proteomics-based discrimination model with data from 1 institution (ie, the training set). We tested the discriminative ability in independent samples from the other institution (ie, the test set). As an exploratory analysis, we executed pathway analysis of significantly dysregulated proteins. Pathways with false discovery rate Results: The study included 266 cases and 167 controls (n=308 in the training set; n=125 in the test set). Using the proteomics-based model derived from the training set, the area under the receiver operating characteristic curve was 0.89 (95% CI, 0.83–0.94) in the test set. Pathway analysis revealed that the Ras-MAPK (mitogen-activated protein kinase) pathway, along with its upstream and downstream pathways, was upregulated in HCM. Pathways involved in inflammation and fibrosis—for example, the TGF (transforming growth factor)-β pathway—were also upregulated. Conclusions: This study serves as the largest-scale investigation with the most comprehensive proteomics profiling in HCM, revealing circulating biomarkers and exhibiting both novel (eg, Ras-MAPK) and known (eg, TGF-β) pathways differentially regulated in HCM.

Background: Genetic testing can determine family screening strategies and has prognostic and diagnostic value in hypertrophic cardiomyopathy (HCM). However, it can also pose a significant psychosocial burden. Conventional scoring systems offer modest ability to predict genotype positivity. The aim of our study was to develop a novel prediction model for genotype positivity in patients with HCM by applying machine learning (ML) algorithms. Methods: We constructed 3 ML models using readily available clinical and cardiac imaging data of 102 patients from Columbia University with HCM who had undergone genetic testing (the training set). We validated model performance on 76 patients with HCM from Massachusetts General Hospital (the test set). Within the test set, we compared the area under the receiver operating characteristic curves (AUROCs) for the ML models against the AUROCs generated by the Toronto HCM Genotype Score (the Toronto score) and Mayo HCM Genotype Predictor (the Mayo score) using the Delong test and net reclassification improvement. Results: Overall, 63 of the 178 patients (35%) were genotype positive. The random forest ML model developed in the training set demonstrated an AUROC of 0.92 (95% CI, 0.85–0.99) in predicting genotype positivity in the test set, significantly outperforming the Toronto score (AUROC, 0.77 [95% CI, 0.65–0.90], P =0.004, net reclassification improvement: P P =0.01, net reclassification improvement: P =0.001). The gradient boosted decision tree ML model also achieved significant net reclassification improvement over the Toronto score ( P P =0.03), with an AUROC of 0.87 (95% CI, 0.75–0.99). Compared with the Toronto and Mayo scores, all 3 ML models had higher sensitivity, positive predictive value, and negative predictive value. Conclusions: Our ML models demonstrated a superior ability to predict genotype positivity in patients with HCM compared with conventional scoring systems in an external validation test set.

The purpose of this study is to determine whether or not left ventricular remodeling can be induced after septal myectomy in patients with obstructive hypertrophic cardiomyopathy, and if so, how it occurs, using gated cardiac computed tomography.Fifty patients with hypertrophic obstructive cardiomyopathy who underwent septal myectomy along the septal band between March 2016 and July 2020 were retrospectively reviewed. Recent consecutive 19 patients underwent postoperative cardiac computed tomography. In these patients, volumes of the septal band and thickness of 17 left ventricular myocardial segments were measured to determine the changes after surgery.The resection volume predicted by preoperative computed tomography and the actual resection volume were 6.7 ± 3.3 mL and 6.4 ± 2.7 mL. In-hospital mortality was 0%. Moderate or greater mitral valve regurgitation and systolic anterior motion decreased from 56% to 6% and 86% to 6%, respectively. Median preoperative ventricular septal thickness and left ventricular outflow tract pressure gradient at rest decreased from 20.0 mm (interquartile range, 17.0-24.0 mm) and 74.0 mm Hg (interquartile range, 42.5-92.5 mm Hg) to 14.0 mm (interquartile range, 11.5-16.0 mm) and 15.5 mm Hg (interquartile range, 12.1-21.5 mm Hg), respectively. Postoperative computed tomography confirmed a reduction in septal band volume of 5.7 ± 2.8 mL. Total left ventricular myocardial volume was reduced by 12.9 ± 8.8 mL, which exceeded the volume reduction of the resected septal band. All segments except the basal inferior and basal inferolateral regions showed a significant decrease in wall thickness by a median of 6.4%.Properly performed septal myectomy may induce remodeling of the entire left ventricle, not just the resected area.

Background and ObjectiveThe Food and Drug Administration (FDA) relies on advice from scientific and medical experts to make approval decisions about new prescription medications and medical devices. Therefore, it is crucial that FDA Advisory Committees (ACs) include the most knowledgeable scientists and clinicians in the decision-making process. However, to ensure that the advice is free from biases, current FDA policy often excludes those most qualified from participating in ACs due to perceived conflicts of interest (COI). The objective of the present study is to elicit opinion among subject matter experts regarding current FDA COI rules and regulations.MethodsWe conducted a cross-sectional study using formal, self-administered online survey consisting of 14 questions, 3 of which addressed perceived implications of current FDA COI policy. We send a formal online survey to study subjects via Qualtrics. Study subjects were 1) individuals who participated in FDA ACs and 2) those who were interested in participating in ACs and had completed FDA COI paperwork but rejected by the FDA due to COI. The outcome measure is response to the 3 questions about the perceived implications of current FDA COI policy. Responses were scored on a 5-point Likert-type scale.ResultsAmong 403 study subjects (200 AC members and 203 individuals who were rejected due to COI), 145 (36%) responded to the survey including 90 AC members and 55 rejected individuals. Respondents included 41 (28%) females. 97% were holding MD or PhD degrees. 88% were age 46 and over, and 66% had more than 25 years in practice. The primary findings were that 49% of respondents agreed that the current FDA regulations lead to a lower quality of experts on ACs, 72% agreed that current policies exclude qualified experts from serving on ACs, and 48% agreed that FDA policy lowers the overall quality of AC input, to at least a “moderate” extent (19%-37% to a “high” or “very high” extent).ConclusionsThe prevailing opinion among respondents to the formal survey is that current FDA COI policy has the potential effects to lowering quality of experts, excluding qualified experts, and lowering overall quality of AC input. The present report elucidates a potential need for the FDA to discuss the benefit and risk of the current AC COI policies.

Introduction: Genotyping may provide valuable insights into family screening strategies and prognosis in patients with hypertrophic cardiomyopathy (HCM). On the other hand, genotyping is expensive. Thus, it is important to identify patients who are more likely to be genotype positive. However, conventional prediction models (e.g., the Mayo score) based on clinical and echocardiographic parameters offer only modest accuracy and are subject to inter-observer variability. Hypothesis: Deep convolutional neural network (DCNN) analysis of echocardiographic images improves the ability to predict genotype positivity in HCM compared to the conventional model. Methods: We included 99 patients with HCM who underwent genetic testing for diagnostic and/or family screening purposes. The age at diagnosis was 46±20 years and 65% were male. In each case, we obtained parasternal short- and long-axis as well as all apical images at end-systole. The DCNN underwent 100 steps to develop the model to predict genotype positivity. In each step, we used 80% of the cohort as the training set and the remaining 20% as the test set (i.e., 5-fold cross-validation). We used the Mayo score as the reference model. We compared the area under the receiver operating characteristics curve (AUC) between a combined model using the reference model plus the DCCN-derived probability and the reference model. We calculated the p value by performing 1,000 bootstrapping. Results: Overall, 45 patients (45%) were genotype positive. The model combining the reference and the DCNN-derived models significantly outperformed the reference model (AUC 0.79 [95% CI 0.69-0.87] with the combined model vs. 0.72 [0.61-0.82] with the reference model; p=0.006; Figure). Conclusion: Compared to a conventional model based on clinical and echocardiographic parameters, our new model combining the conventional and DCNN-derived models demonstrated superior ability to predict positive genotype in patients with HCM.

Introduction: Septal reduction therapy (SRT) - i.e., septal myectomy and alcohol septal ablation - has been used to treat medically-refractory obstructive hypertrophic cardiomyopathy (HOCM) for a few decades. However, the effects of SRT on the risk of acute cardiovascular (CV) events and all-cause mortality are largely unknown. Hypothesis: SRT is associated with a long-term decrease in acute CV events and a short-term increase in all-cause mortality in patients with HOCM. Methods: We performed a propensity score (PS)-matched study using all-payer databases that capture all hospitalizations and outpatient visits in New York State. We identified patients with HOCM who underwent SRT between January 1, 2007 and December 31, 2014 (i.e., the SRT group) and those who have never had SRT but had at least one hospitalization for HOCM during the same period (i.e., the control group). We performed 1:1 PS matching using age, sex, race/ethnicity, source of payment, season and year of starting event follow-up (i.e., the day of SRT or the index hospitalization), and Elixhauser comorbidity measures. The primary outcomes were (1) acute CV event (i.e., emergency department visit or unplanned hospitalization for CV disease) during 1-360 days and 361-720 days and (2) 7-, 15-, 30-, 180-, and 360-day all-cause mortality. We compared the risk of the outcome event using logistic regression models. Results: The analytic cohort consisted of 690 patients with HOCM (i.e., 345 PS-matched pairs). The SRT group had a lower risk of acute CV event during 361-720 days (OR 0.44; 95% CI, 0.20-0.97; P=0.04) but a higher risk of 7-day mortality (11 vs. 2 in the control group; P=0.03). The SRT group had a non-significant trend towards lower all-cause mortality in longer terms ( Figure ). Conclusion: In this population-based PS-matched study of patients with HOCM, SRT was associated with a reduced risk of acute CV events in the second post-procedure year at the sacrifice of a short-term increase in all-cause mortality.

Background: Only a subset of patients with hypertrophic cardiomyopathy (HCM) develop adverse cardiac events – e.g., end-stage heart failure, cardiovascular death. Current risk stratification methods are imperfect, limiting identification of high-risk patients with HCM. Our aim was to improve the prediction of adverse cardiac events in patients with HCM using machine learning methods. Methods: We applied modern machine learning methods to a prospective cohort of adults with HCM. The outcome was a composite of death due to heart failure, heart transplant, and sudden death. As the reference model, we constructed logistic regression model using known predictors. We determined 20 predictive characteristics based on random forest classification and a priori knowledge, and developed 4 machine learning models. Results Of 183 patients in the cohort, the mean age was 53 (SD = 17) years and 45% were female. During the median follow-up of 2.2 years (interquartile range, 0.6–3.8), 33 subjects (18%) developed an outcome event, the majority of which (85%) was heart transplant. The predictive accuracy of the reference model was 73% (sensitivity 76%, specificity 72%) while that of the machine learning model was 85% (e.g., sensitivity 88%, specificity 84% with elastic net regression). All 4 machine learning models significantly outperformed the reference model – e.g., area under the receiver-operating-characteristic curve 0.79 with the reference model vs. 0.93 with elastic net regression (p Conclusions: Compared with conventional risk stratification, the machine learning models demonstrated a superior ability to predict adverse cardiac events. These modern machine learning methods may enhance identification of high-risk HCM subpopulations.

It is unclear how hypertrophic cardiomyopathy (HCM) affects cardiac metabolic pathways at rest and with exercise. This case-control study compared 15 cases with HCM to 2 control groups without HCM. Metabolomic profiling of 210 metabolites was carried out at rest and at peak exercise. The 50 most discriminant metabolites differentially regulated during exercise were selected using partial least squares discriminant analysis. Pathway enrichment analysis was also performed. At rest, no significant difference was observed in metabolomic profiling of HCM cases as compared to controls. By contrast, there were significant differences in metabolomic profiling in response to exercise (p 0.05) in the following metabolic pathways: the aminoacyl-tRNA biosynthesis pathway; the nitrogen metabolism pathway; the glycine, serine, and threonine metabolism pathway; and the arginine and proline metabolism pathway. The present study demonstrates differential regulation of several metabolic pathways in patients with HCM in the setting of exercise stress.

Background The clinical characteristics associated with elevated right atrial pressure (RAP) in hypertrophic cardiomyopathy (HCM) are unknown. Few data exist as to whether elevated RAP has prognostic implications in patients with HCM. This study investigated the clinical correlates and prognostic value of elevated RAP in HCM.Methods and Results:This retrospective cohort study was performed on 180 patients with HCM who underwent right heart catheterization between 1997 and 2014. Elevated RAP was defined as >8 mmHg. Baseline characteristics, mean pulmonary artery pressure, and mean pulmonary capillary wedge pressure (PCWP) were assessed for association with elevated RAP. The predictive value of elevated RAP for all-cause mortality and the development of atrial fibrillation (AF), ventricular tachycardia/fibrillation (VT/VF), and stroke was evaluated. Elevated RAP was associated with higher New York Heart Association class, dyspnea on exertion, orthopnea, edema, jugular venous distention, larger left atrial size, right ventricular hypertrophy, higher pulmonary artery pressure, and higher PCWP. RAP independently predicted all-cause mortality (adjusted hazard ratio [aHR] 2.18 per 5-mmHg increase, 95% confidence interval [CI] 1.05-4.50, P=0.04) and incident AF (aHR 1.85 per 5-mmHg increase, 95% CI 1.20-2.85, P=0.005). Elevated RAP did not predict VT/VF (P=0.36) or stroke (P=0.28). Conclusions Elevated RAP in patients with HCM is associated with left-sided heart failure and is an independent predictor of all-cause mortality and new-onset AF.

Therapeutic hypothermia is used in select patients after out-of-hospital cardiac arrest (OHCA) to improve neurologic outcome. Rebound hyperthermia (RH) is commonly observed post-treatment. Previous studies analyzing the association of RH with clinical outcome have reported conflicting results. The purpose of this study is to examine the impact of RH after completion of therapeutic hypothermia in patients postcardiac arrest. We analyzed a retrospective cohort from our institution. All adults who underwent therapeutic hypothermia post-OHCA were divided into two cohorts depending on the presence/absence of fever (T 38°C) within 24 hours of completing hypothermia protocol. Clinical outcomes were analyzed at hospital discharge or death. Among 306 patients admitted with OHCA, 117 underwent hypothermia, 97 survived 24 hours postrewarming. Twenty-seven patients (50%) with RH died compared with 20 (47%) without RH (OR, 1.15; 95% CI, 0.52-2.57). Twenty-six patients (67%) with RH had a poor neurologic outcome compared with 27 (63%) without RH (OR 1.19, 95% CI, 0.51-2.74). RH is common after completion of therapeutic hypothermia in comatose patients due to cardiac arrest and is associated with poor neurologic outcomes. We found no significant clinical impact of rebound hypothermia on neurologic outcome or mortality, but our study was underpowered to reveal such impact if it exists.

OBJECTIVES We aimed to investigate the efficacy and safety of different antithrombotic strategies in patients undergoing transcatheter aortic valve implantation (TAVI) using network meta-analyses. BACKGROUND Meta-analyses comparing single antiplatelet therapy (SAPT) vs. dual antiplatelet therapy (DAPT), ± oral anticoagulant (OAC) was conducted to determine the appropriate post TAVI antithrombotic regimen. However, there was limited direct comparisons across the different therapeutic strategies. METHODS MEDLINE and EMBASE were searched through December 2018 to investigate the efficacy and safety of different antithrombotic strategies (SAPT, DAPT, OAC, OAC + SAPT, and OAC + DAPT) in patients undergoing TAVI. The main outcome were all-cause mortality, major or life-threatening bleeding events, and stroke. RESULTS Our search identified 3 randomized controlled trials and 10 nonrandomized studies, a total of 20,548 patients who underwent TAVI. All OACs were vitamin K antagonists. There was no significant difference on mortality except that OAC + DAPT had significantly higher rates of mortality compared with others (p < .05, I2 = 0%). SAPT had significantly lower rates of bleeding compared with DAPT, OAC+SAPT, and OAC+DAPT (hazard ratio [HR]: 0.59 [0.46-0.77], p < .001, HR: 0.58 [0.34-0.99], p = .045, HR: 0.41 [0.18-0.93], p = .033, respectively, I2 = 0%). There was no significant difference on stroke among all antithrombotic strategies. CONCLUSION Patients who underwent TAVI had similar all-cause mortality rates among different antithrombotic strategies except OAC+DAPT. Patients on SAPT had significantly lower bleeding risk than those on DAPT, OAC + SAPT, and OAC + DAPT. Our results suggest SAPT is the preferred regimen when there is no indication for DAPT or OAC. When DAPT or OAC is indicated, DAPT + OAC should be avoided.

Patients with asthma have a high incidence of acute myocardial infarction and ischemic stroke.To investigate the acute effect of asthma exacerbation on these cardiovascular events.Using population-based inpatient data of 3 geographically diverse US states (Florida, Nebraska, and New York) during the period 2011 to 2014, we conducted a self-controlled case series study of adults (aged ≥40 years) hospitalized with asthma exacerbation. The primary outcome was a composite of acute myocardial infarction and ischemic stroke. We used conditional Poisson regression to compare each patient's incidence rate of the outcome during 3 sequential risk periods (1-7, 8-14, and 15-28 days after asthma exacerbation) with that of the reference period (ie, summed period before and after the 3 risk periods).We identified 4607 adults hospitalized for asthma exacerbation who had a first episode of acute myocardial infarction or ischemic stroke. During the reference period, the incidence rate of acute myocardial infarction or ischemic stroke was 25.0/100 person-years. Compared with the reference period, the incidence rate significantly increased during the first risk period (129.1/100 person-years), with a corresponding adjusted incidence rate ratio of 5.04 (95% CI, 4.29-5.88; P.001). In the 2 subsequent risk periods, the incidence rate declined but remained high-50.1/100 person-years (adjusted incidence rate ratio, 1.96; 95% CI, 1.51-2.48; P.001) and 38.0/100 person-years (adjusted incidence rate ratio, 1.48; 95% CI, 1.20-1.81; P .001), respectively. The findings were similar when the 2 outcomes were examined separately.In this population-based study of adults with asthma, the risk of acute myocardial infarction and ischemic stroke increased significantly after asthma exacerbation.

Alcohol septal ablation (ASA) and ventricular septal myectomy (VSM) are 2 options of ventricular septal reduction therapy (VSRT) for obstructive hypertrophic cardiomyopathy (HC). We hypothesized that patients with HC who underwent ASA have a higher risk of acute care use (i.e., emergency department [ED] visit or unplanned hospitalization) for cardiovascular disease (CVD) than VSM. We performed a comparative effectiveness study of ASA versus VSM (reference group) among patients with HC who underwent VSRT, using population-based ED and inpatient databases in 3 states, 2005 to 2014. The outcome was acute care use for CVD during a 2-year post-VSRT period. We constructed univariable and multivariable logistic regression models to compare the risk during sequential 6-month periods. We also performed sensitivity analysis with propensity score-matching at 1:1 ratio. We identified 850 patients with HC who underwent VSRT, including 393 with ASA and 457 with VSM. During 13 to 18 months after VSRT, there was a nonsignificantly higher risk with ASA than VSM (adjusted odds ratio [OR] 1.73; 95% confidence interval [CI] 0.83 to 3.60; p = 0.14). Patients who had ASA had a significantly higher risk in the 19 to 24 months post-VSRT period (adjusted OR 2.12; 95% CI 1.06 to 4.23; p = 0.03). Similarly, the propensity score-matched analysis demonstrated a higher risk with ASA than VSM during 13 to 18 months (OR 2.97; 95% CI 1.04 to 8.46; p = 0.04) and 19 to 24 months (OR 7.06; 95% CI 2.04 to 24.36; p = 0.002) after VSRT. In conclusion, among 850 patients with HC who underwent VSRT, the risk of acute care use for CVD was higher after ASA than VSM during the second post-VSRT year.

High-throughput proteomics profiling has never been applied to discover biomarkers in patients with hypertrophic cardiomyopathy (HCM). The objective was to identify plasma protein biomarkers that can distinguish HCM from controls. We performed a case-control study of patients with HCM (n = 15) and controls (n = 22). We carried out plasma proteomics profiling of 1129 proteins using the SOMAscan assay. We used the sparse partial least squares discriminant analysis to identify 50 most discriminant proteins. We also determined the area under the curve (AUC) of the receiver operating characteristic curve using the Monte Carlo cross validation with balanced subsampling. The average AUC was 0.94 (95% confidence interval, 0.82–1.00) and the discriminative accuracy was 89%. In HCM, 13 out of the 50 proteins correlated with troponin I and 12 with New York Heart Association class. Proteomics profiling can be used to elucidate protein biomarkers that distinguish HCM from controls.

Background Myocardial contraction fraction (MCF), the ratio of left ventricular stroke volume to myocardial volume, is a novel parameter that can distinguish between pathologic and physiologic hypertrophy. However, its prognostic value in hypertrophic cardiomyopathy (HCM) has never been examined. The objective was to determine if MCF is associated with functional capacity and predicts adverse cardiovascular outcomes in patients with HCM and normal left ventricular ejection fraction (LVEF). Methods and Results We conducted a prospective cohort study of 137 patients with HCM and LVEF ≥55%. Patients were followed for 2.7 ± 2.5 years. We examined association of MCF with New York Heart Association (NYHA) functional class and a composite outcome of embolic stroke, heart transplantation, and cardiac death. We performed time-to-event analysis with the use of Cox proportional hazards modeling and stepwise elimination. The average age was 52 ± 18 years. The average MCF was 26 ± 11%. MCF was inversely correlated with NYHA functional class (P = .001). A total of 20 subjects experienced an outcome event with an event rate of 5.6% per patient-year. MCF independently predicted the outcome (adjusted hazard ratio 0.50 per 10% increase, 95% confidence interval 0.28–0.90, adjusted P = .02). Conclusions In patients with HCM and normal LVEF, MCF is associated with functional capacity and independently predicts adverse cardiovascular outcomes.

Background Transforming growth factor-β1 (TGF-β1) reportedly acts as a tumor suppressor in tumorigenesis. However, little is known as to how TGF-β1 concentrations change prior to the development of hepatocellular carcinoma (HCC) in humans. We examined the association between the serum TGF-β1 concentrations and death from HCC to determine whether the serum TGF-β1 can be a predictor of incident HCC. Methods We conducted a nested case-controlled study of participants in the Japan Collaborative Cohort Study for Evaluation of Cancer Risk. We used a conditional logistic regression analysis to estimate the adjusted relative risks (aRRs) of death from HCC according to the serum TGF-β1 concentrations among 1940 participants including 83 patients with HCC and 1857 controls matched for age, sex, and hepatitis C virus (HCV)-antibody seropositivity. Findings When serum TGF-β1 was modelled as a continuous variable, the aRR of death from HCC associated with a decrement of 7.9 ng/mL (one standard deviation) in the serum TGF-β1 concentrations was 2.3 (95% CI 1.7–3.0, P, Highlights • We studied whether TGF-β1 concentration predicts incident HCC. • TGF-β1 concentration was significantly associated with new HCC occurrence. • TGF-β1 concentration improved HCC risk classification. Hepatocellular carcinoma (HCC) is the third most common cause of cancer death worldwide and has a poor prognosis. HCC is difficult to diagnose early enough to perform a radical treatment. Nowadays there are several biomarkers, such as alpha-fetoprotein (AFP), but it is difficult to detect HCC in the early stage with those markers. To address this knowledge gap, we conducted a nested case-controlled study to find the predictor for HCC. We found that TGF-β1 concentrations were inversely associated with HCC occurrence. Our data demonstrates that low levels of TGF-β1 can identify patients who are at higher risk of developing HCC. TGF-β1 may be a predictor that becomes altered well before the development of clinically detectable malignancy.

Background Concerns raised regarding adverse cardiovascular (CV) outcomes with new therapies for type 2 diabetes mellitus (T2DM) have led to several large-scale CV outcome trials. The EXAMINE trial confirmed noninferiority of the dipeptidyl dipeptidase 4 inhibitor alogliptin to placebo on major adverse cardiac event rates in a post–acute coronary syndrome (ACS) T2DM population. We present data on additional ischemic cardiac events and CV hospitalizations in EXAMINE. Methods Patients with T2DM and an ACS event in the previous 15 to 90 days were randomly assigned to alogliptin or placebo on a background of standard treatment for diabetes. The incident rates of a 5-component composite end point of CV death, stroke, myocardial infarction, unstable angina, and coronary revascularization as well as CV hospitalization were calculated in all participants and according to macrovascular disease at baseline. Results There were no significant differences between alogliptin (n = 2,701) and placebo (n = 2,679) in the event rate of the 5-component composite endpoint with median follow-up 533 days (21.0% vs 21.5%, hazard ratio [HR] 0.98 [0.87-1.10], P = .72). No differences were observed in terms of CV hospitalization (25.0% vs 25.4%, HR 0.98 [0.88-1.09], P = .70) or coronary revascularization (10.6% vs 10.2%, HR 1.05 [0.88-1.09], P = .60). No interactions were observed for treatment and prior macrovascular disease. Conclusions EXAMINE demonstrates that there was no increase in the risk of cardiac ischemic events and CV hospitalizations with alogliptin in a high-risk post-ACS patient population. Because these are major driver of overall health care costs, these data suggest that there would be no adverse impact on health care resource utilization.