Risk Stratification In Hypertrophic Cardiomyopathy Research Articles

Advances in Multi-Modality Imaging in Hypertrophic Cardiomyopathy

Hypertrophic cardiomyopathy (HCM) is characterized by abnormal growth of the myocardium with myofilament disarray and myocardial hyper-contractility, leading to left ventricular hypertrophy and fibrosis. Where culprit genes are identified, they typically relate to cardiomyocyte sarcomere structure and function. Multi-modality imaging plays a crucial role in the diagnosis, monitoring, and risk stratification of HCM, as well as in screening those at risk. Following the recent publication of the first European Society of Cardiology (ESC) cardiomyopathy guidelines, we build on previous reviews and explore the roles of electrocardiography, echocardiography, cardiac magnetic resonance (CMR), cardiac computed tomography (CT), and nuclear imaging. We examine each modality’s strengths along with their limitations in turn, and discuss how they can be used in isolation, or in combination, to facilitate a personalized approach to patient care, as well as providing key information and robust safety and efficacy evidence within new areas of research.

The challenge of risk stratification in hypertrophic cardiomyopathy: clinical, genetic and imaging insights from a quaternary referral centre

Abstract Background Hypertrophic cardiomyopathy (HCM) is the commonest genetic cardiomyopathy and may result in sudden cardiac death (SCD). Clinical risk stratification scores are utilised to estimate SCD risk and determine potential utility of a primary prevention implantable cardioverter defibrillator (ICD). Methods Patients with a confirmed diagnosis of HCM from a quaternary HCM service were defined according to clinical characteristics, genetic profiles and cardiac imaging results. European Risk-SCD score and American Heart Association / American College of Cardiology (AHA/ACC) Score were calculated. The primary outcome was cardiac arrest. Results 380 patients with HCM were followed up for a median of 6.4 years. 18 patients (4.7%) experienced cardiac arrest, with predictive factors being younger age (37.2 vs 54.4 years, p=0.0041), unexplained syncope (33.3% vs 9.4%, p=0.007), non-sustained ventricular tachycardia (50.0% vs 12.7%, p<0.0001), increased septal thickness (21.5 vs 17.5mm, p=0.0003), and presence of a sarcomeric gene mutation (100.0% vs 65.8%, p=0.038). The Risk-SCD and AHA/ACC scores had poor agreement (kappa coefficient 0.38). Risk-SCD score had poor sensitivity (44.4%), classifying 55.6% of patients with cardiac arrest as low-risk but was highly specific (93.7%). AHA/ACC risk score did not discriminate between groups significantly. 20 patients (5.3%) died, with most >60-year-olds having a non-cardiac cause of death (p=0.0223). Conclusion This study highlights limited (38%) agreement between the Risk-SCD and AHA/ACC scores. Most cardiac arrests occurred in ostensibly low or medium-risk patients under both scores. Appropriate ICD selection remains challenging. Utilising newer markers such as cardiac MRI and genetic findings may assist future risk refinement.

Abstract 14514: Hypertrophic Cardiomyopathy - Genotype Distribution and Genotype-Phenotype Correlations - A Unique Perspective From a Single Center Study

Background: The role of genotype in risk stratification of hypertrophic cardiomyopathy (HCM) is unclear. Hypothesis: Genotype status affects phenotype and associated outcomes. Aims: To evaluate genotype-phenotype correlations in all adult HCM patients seen at our Cardiac Specialty Center over 13 years and associated outcomes. Methods: We evaluated genotype-phenotype correlations, all-cause mortality, and a composite outcome, including mortality, stroke, implantable cardioverter-defibrillator placement, heart failure hospitalization, LV assist device implantation, heart transplant, septal myectomy, and alcohol septal ablation. Results: Of 827 HCM patients, genotyping was completed in 754 (91.2%), which included 27% genotype-positive (Gen-P), 22% variants of unknown significance (VUS), and 51% genotype-negative (Gen-N) patients with a mean age of 47, 57, and 58 years, respectively. The most common gene implicated was MYBPC3 (63%). LV hypertrophy on electrocardiogram was more frequent in Gen-N than Gen-P patients. Gen-P patients had more frequent non-sustained ventricular tachycardia on Holter monitoring (25% vs 10%), grade III diastolic dysfunction (12% vs 7%), elevated ProBNP (71% vs 61%), and lower ejection fraction (66% vs 69%) than Gen-N patients (P <.05 for all comparisons). All heart transplantations (N=5) were performed in Gen-P patients. LVOT obstruction was more frequent in Gen-N than Gen-P patients (48% vs 26%, P <.01). Distribution of outcomes is shown in Panels A-H. The composite outcome was worse in Gen-P vs Gen-N patients (HR 1.84, P <.01). The other independent predictors of poor composite outcome were old age, male sex, obesity, and atrial fibrillation. A separate analysis of mortality showed similar survival in all groups. Conclusion: Differences exist in phenotype and outcomes based on the genotype status, with more severe phenotype and poorer outcomes in Gen-P patients in our single-state single-center experience.

Performance of 2020 AHA/ACC HCM Guidelines and Incremental Value of Myocardial Strain for Predicting SCD

BackgroundThe 2020 American Heart Association (AHA)/American College of Cardiology (ACC) guidelines for sudden cardiac death (SCD) risk stratification in hypertrophic cardiomyopathy (HCM) need further international validation. ObjectivesPerformance of the guidelines and the incremental value of myocardial strain for predicting SCD in HCM were investigated. MethodsIn 1,416 HCM patients, SCD risk was stratified according to the 2020 AHA/ACC and 2014 European Society of Cardiology (ESC) guidelines. Left ventricular (LV) global longitudinal strain (GLS) and left atrial reservoir strain (LARS) were measured. The main outcome consisted of SCD events. ResultsOverall, 29.1% had major risk factors (RFs), and 14.7% had nonmajor RFs in the absence of major RFs; estimated 5-year SCD event rates were 6.8% and 2.3%, respectively. SCD risk was significantly increased in the former group but not in the latter. When stratified by the number of RFs, 5-year SCD event rates were 1.9%, 3.0%, 4.9%, and 18.4% for patients with 0, 1, 2, and 3 or more RFs, respectively. SCD risk was elevated in patients with multiple RFs but not in those with a single RF. Performance of the AHA/ACC and ESC guidelines did not differ significantly over 10 years (5-year time-dependent area under the curve: 0.677 vs 0.724; P = 0.235). Decreased LV GLS and LARS were independently associated with SCD events with optimal cutoffs of LV GLS <13% and LARS <21%. Adding LV GLS and LARS to the guidelines had incremental predictive value. ConclusionsThe 2020 AHA/ACC guidelines were predictive of SCD events with modest power in a large Asian HCM cohort. Implantable cardioverter-defibrillators are reasonable in patients with multiple RFs, and consideration of myocardial strain can improve SCD prediction.

Improving sudden cardiac death risk stratification in hypertrophic cardiomyopathy using established clinical variables and genetic information

Background and aimsThe cardiac societies of Europe and the United States have established different risk models for preventing sudden cardiac death (SCD) in hypertrophic cardiomyopathy (HCM). The aim of this study is to validate current SCD risk prediction methods in a German HCM cohort and to improve them by the addition of genotype information.MethodsHCM patients without prior SCD or equivalent arrhythmic events ≥ 18 years of age were enrolled in an expert cardiomyopathy center in Germany. The primary endpoint was defined as SCD/-equivalent within 5 years of baseline evaluation. 5-year SCD-risk estimates and recommendations for ICD implantations, as defined by the ESC and AHA/ACC guidelines, were analyzed. Multivariate cox proportional hazards analyses were integrated with genetic findings as additive SCD risk.Results283 patients were included and followed for in median 5.77 years (2.92; 8.85). A disease-causing variant was found in 138 (49%) patients. 14 (5%) patients reached the SCD endpoint (5-year incidence 4.9%). Kaplan–Meier survival analysis shows significantly lower overall SCD event-free survival for patients with an identified disease-causing variant (p < 0.05). The ESC HCM Risk-SCD model showed an area-under-the-curve (AUC) of 0.74 (95% CI 0.68–0.79; p < 0.0001) with a sensitivity of 0.29 (95% CI 0.08–0.58) and specificity of 0.83 (95% CI 0.78–0.88) for a risk estimate ≥ 6%/5-years. By comparison, the AHA/ACC HCM SCD risk stratification model showed an AUC of 0.70 (95% CI 0.65–0.76; p = 0.003) with a sensitivity of 0.93 (95% CI, 0.66–0.998) and specificity of 0.28 (95% CI 0.23–0.34) at the respective cut-off. The modified SCD Risk Score with genetic information yielded an AUC of 0.76 (95% CI 0.71–0.81; p < 0.0001) with a sensitivity of 0.86 (95% CI 0.57–0.98) and specificity of 0.69 (95% CI 0.63–0.74). The number-needed-to-treat (NNT) to prevent 1 SCD event by prophylactic ICD-implantation is 13 for the ESC model, 28 for AHA/ACC and 9 for the modified Genotype-model.ConclusionThis study confirms the performance of current risk models in clinical decision making. The integration of genetic findings into current SCD risk stratification methods seem feasible and can add in decision making, especially in borderline risk-groups. A subgroup of patients with high SCD risk remains unidentified by current risk scores.Graphical abstract

The challenge of risk stratification in hypertrophic cardiomyopathy: Clinical, genetic and imaging insights from a quaternary referral centre

BackgroundHypertrophic cardiomyopathy (HCM) is the commonest genetic cardiomyopathy and may result in sudden cardiac death (SCD). Clinical risk stratification scores are utilised to estimate SCD risk and determine potential utility of a primary prevention implantable cardioverter defibrillator (ICD). MethodsPatients with a confirmed diagnosis of HCM from a quaternary HCM service were defined according to clinical characteristics, genetic profiles and cardiac imaging results. European Risk-SCD score and American Heart Association / American College of Cardiology (AHA/ACC) Score were calculated. The primary outcome was cardiac arrest. Results380 patients with HCM were followed up for a median of 6.4 years. 18 patients (4.7%) experienced cardiac arrest, with predictive factors being younger age (37.2 vs 54.4 years, p = 0.0041), unexplained syncope (33.3% vs 9.4%, p = 0.007), non-sustained ventricular tachycardia (50.0% vs 12.7%, p < 0.0001), increased septal thickness (21.5 vs 17.5 mm, p = 0.0003), and presence of a sarcomeric gene mutation (100.0% vs 65.8%, p = 0.038). The Risk-SCD and AHA/ACC scores had poor agreement (kappa coefficient 0.38). Risk-SCD score had poor sensitivity (44.4%), classifying 55.6% of patients with cardiac arrest as low-risk but was highly specific (93.7%). AHA/ACC risk score did not discriminate between groups significantly. 20 patients (5.3%) died, with most >60-year-olds having a non-cardiac cause of death (p = 0.0223). ConclusionThis study highlights limited (38%) agreement between the Risk-SCD and AHA/ACC scores. Most cardiac arrests occurred in ostensibly low or medium-risk patients under both scores. Appropriate ICD selection remains challenging. Incorporating newer risk markers such as HCM genotyping and myocardial fibrosis quantification by cardiac MRI may assist future risk refinement.

The Challenge of Risk Stratification in Hypertrophic Cardiomyopathy: Clinical, Genetic and Imaging Insights From a Quaternary Referral Centre

The Challenge of Risk Stratification in Hypertrophic Cardiomyopathy: Clinical, Genetic and Imaging Insights From a Quaternary Referral Centre

The value of cardiac MRI in the risk stratification in patients with hypertrophic cardiomyopathy

Objective: To explore the value of cardiac magnetic resonance imaging (CMR) in the risk stratification of hypertrophic cardiomyopathy (HCM). Methods: HCM patients who underwent CMR examination in Fuwai Hospital between March 2012 and May 2013 were retrospectively enrolled. Baseline clinical and CMR data were collected and patient follow-up was performed using telephone contact and medical record. The primary composite endpoint was sudden cardiac death (SCD) or and equivalent event. The secondary composite endpoint was all-cause death and heart transplant. Patients were divided into SCD and non-SCD groups. Cox regression was used to explore risk factors of adverse events. Receiver operating characteristic (ROC) curve analysis was used to assess the performance and the optimal cut-off of late gadolinium enhancement percentage (LGE%) for the prediction of endpoints. Kaplan-Meier and log-rank tests were used to compare survival differences between groups. Results: A total of 442 patients were enrolled. Mean age was (48.5±12.4) years and 143(32.4%) were female. At (7.6±2.5) years of follow-up, 30 (6.8%) patients met the primary endpoint including 23 SCD and 7 SCD equivalent events, and 36 (8.1%) patients met the secondary endpoint including 33 all-cause death and 3 heart transplant. In multivariate Cox regression, syncope(HR=4.531, 95%CI 2.033-10.099, P<0.001), LGE% (HR=1.075, 95%CI 1.032-1.120, P=0.001) and left ventricular ejection fraction (LVEF) (HR=0.956, 95%CI 0.923-0.991, P=0.013) were independent risk factors for primary endpoint; Age (HR=1.032, 95%CI 1.001-1.064, P=0.046), atrial fibrillation (HR=2.977, 95%CI 1.446-6.131, P=0.003),LGE% (HR=1.075, 95%CI 1.035-1.116, P<0.001) and LVEF (HR=0.968, 95%CI 0.937-1.000, P=0.047) were independent risk factors for secondary endpoint. ROC curve showed the optimal LGE% cut-offs were 5.1% and 5.8% for the prediction of primary and secondary endpoint, respectively. Patients were further divided into LGE%=0, 0<LGE%<5%, 5%≤LGE%<15% and LGE%≥15% groups. There were significant survival differences between these 4 groups whether for primary endpoint or secondary endpoint (all P<0.001) and the accumulated incidence of primary endpoint was 1.2% (2/161), 2.2% (2/89), 10.5% (16/152) and 25.0% (10/40), respectively. Conclusion: LGE is an independent risk factor for SCD events as well as all-cause death and heart transplant. LGE is of important value in the risk stratification in patients with HCM.

Arrhythmic Risk Stratification among Patients with Hypertrophic Cardiomyopathy.

Hypertrophic cardiomyopathy (HCM) is a cardiac muscle disorder characterized by generally asymmetric abnormal hypertrophy of the left ventricle without abnormal loading conditions (such as hypertension or valvular heart disease) accounting for the left ventricular wall thickness or mass. The incidence of sudden cardiac death (SCD) in HCM patients is about 1% yearly in adults, but it is far higher in adolescence. HCM is the most frequent cause of death in athletes in the Unites States of America. HCM is an autosomal-dominant genetic cardiomyopathy, and mutations in the genes encoding sarcomeric proteins are identified in 30-60% of cases. The presence of this genetic mutation carries more than 2-fold increased risk for all outcomes, including ventricular arrhythmias. Genetic and myocardial substrate, including fibrosis and intraventricular dispersion of conduction, ventricular hypertrophy and microvascular ischemia, increased myofilament calcium sensitivity and abnormal calcium handling, all play a role as arrhythmogenic determinants. Cardiac imaging studies provide important information for risk stratification. Transthoracic echocardiography can be helpful to evaluate left ventricular (LV) wall thickness, LV outflow-tract gradient and left atrial size. Additionally, cardiac magnetic resonance can evaluate the prevalence of late gadolinium enhancement, which when higher than 15% of LV mass is a prognostic maker of SCD. Age, family history of SCD, syncope and non-sustained ventricular tachycardia at Holter ECG have also been validated as independent prognostic markers of SCD. Arrhythmic risk stratification in HCM requires careful evaluation of several clinical aspects. Symptoms combined with electrocardiogram, cardiac imaging tools and genetic counselling are the modern cornerstone for proper risk stratification.

Cardiac index: A superior parameter of cardiac function than left ventricular ejection fraction in risk stratification of hypertrophic cardiomyopathy

An appropriate indicator of cardiac function in the risk stratification of hypertrophic cardiomyopathy (HCM) patients is urgently needed. Cardiac index that reflects cardiac pumping function may be suitable. To investigate the clinical significance of reduced cardiac index in HCM patients. A total of 927 HCM patients were enrolled. The primary endpoint was cardiovascular death; the secondary endpoints were sudden cardiac death (SCD) and all-cause death. Combination models were constructed by adding reduced cardiac index and reduced left ventricular ejection fraction (LVEF) to the HCM risk-SCD model. Predictive accuracy was determined by C-statistics. Reduced cardiac index was defined as cardiac index of ≤2.42 L/min/m2. During a median follow-up period of 4.3 years, 51 patients reached the endpoint. The reduced cardiac index independently increased the risk of cardiovascular death (adjusted HR [aHR] 2.976, P=0.007), SCD (aHR 6.385, P=0.001), and all-cause death (aHR 2.428, P=0.010). By adding reduced cardiac index to the HCM risk-SCD model, the model C-statistic increased from 0.691 to 0.762, with an integrated discrimination improvement of 0.021 (P=0.018) and a net reclassification improvement of 0.560 (P=0.007); the addition of reduced LVEF failed to improve the original model. Better predictive accuracy for all endpoints was also indicated in reduced cardiac index than in reduced LVEF. Reduced cardiac index is an independent predictor of poor prognoses in HCM patients. Combining reduced cardiac index rather than reduced LVEF improved the HCM risk-SCD stratification strategy. The reduced cardiac index showed better predictive accuracy than reduced LVEF for all endpoints.

The Value of Myocardial Fibrosis Parameters Derived from Cardiac Magnetic Resonance Imaging in Risk Stratification for Patients with Hypertrophic Cardiomyopathy

The aim of the study was to determine whether myocardial fibrosis parameters of cardiac magnetic resonance imaging (MRI) has added value in the risk stratification of hypertrophic cardiomyopathy (HCM) patients. In this retrospective study, 108 patients with HCM (mean age ± standard deviation, 55.5 ± 13.4 years) were included from January 2019 to April 2022, and were followed up for 2 years to record sudden cardiac death (SCD) adverse events. All HCM patients underwent cardiac MRI and were divided into a training cohort (n=81; mean age, 56.1 ± 13.0 years) and a validation cohort (n=27; mean age, 57.8 ± 13.9 years). According to the presence of SCD risk factors defined by the 2020 AHA/ACC guidelines, HCM patients were classified into low-risk and high-risk groups. Cardiac MRI features, including late gadolinium enhancement (LGE), T1 mapping, and extracellular volume fraction (ECV), were assessed and compared between the two groups. Logistic regression analysis was used to select the optimal predictors of SCD from cardiac MRI features and HCM Risk-SCD score to construct prediction models. Receiver operating curve (ROC) analysis was used to assess the predictive performance of the constructed prediction model. Cox regression analysis was also used to determine the optimal predictors of SCD adverse events. Multivariate logistic analysis showed that the global ECV was the single myocardial fibrosis parameter predictive of the risk of SCD (p < 0.001). The areas under the ROC curves (AUC) of global ECV were higher than those of LGE, global native T1, global postcontrast T1, and HCM Risk-SCD (AUC=0.85 vs. 0.74, 0.77, 0.63, 0.78). An integrative risk stratification model combining global ECV (odds ratio, 1.36 [95% CI: 1.16-1.60]; p < 0.001) and HCM Risk-SCD score (odds ratio, 1.63 [95% CI: 1.08-2.47]; p< 0.001) achieved an AUC of 0.89 (95% CI: 0.81-0.96) in the training cohort, which was significantly higher than that of HCM Risk-SCD score alone (p=0.03). The AUC of the integrative model was 0.93 (95% CI: 0.84-1.00) in the validation cohort. Multivariate Cox regression analysis also showed that the global ECV was an independent predictor of SCD adverse events (hazard ratio, 1.27 [95% CI: 1.10-1.47]). The ECV derived from cardiac MRI is comparable to the HCM Risk-SCD scale in predicting the SCD risk stratification in patients with HCM.

983 COMPARISON OF DEMOGRAPHIC, CLINICAL, BIOCHEMICAL AND IMAGING AND IMAGING FINDINGS IN HYPERTROPHIC CARDIOMYOPATHY PROGNOSIS: A NETWORK META-ANALYSES

Abstract Background Despite hypertrophic cardiomyopathy (HCM) being the most common inherited heart disease and conferring increased risk for heart failure (HF) and sudden cardiac death (SCD), risk assessment in HCM patients is still largely unresolved. Objective To synthesize and compare the prognostic impact of demographic, clinical, biochemical, and imaging findings in patients with HCM. Methods We searched PubMed, Embase, and Cochrane Library for studies published from inception to November 2020, and the endpoints were: i) all-cause death; ii) an arrhythmic endpoint including SCD, sustained ventricular tachycardia, ventricular fibrillation, or aborted SCD; iii) a composite endpoint including i) or ii) plus hospitalization for HF or cardiac transplantation. We performed a pairwise meta-analysis obtaining the pooled estimate separately for the association between baseline variables and study endpoints. A random-effects network meta-analysis (NMA) was subsequently used to comparatively assess the prognostic value of outcome predictors. Results One-hundred-eleven studies with 56,792 HCM patients were included. Among others, increased BNP/NT-proBNP, late-gadolinium-enhancement (LGE), positive genotype, impaired global longitudinal strain and presence of apical aneurysm conferred increased risk for the composite endpoint. At NMA, LGE showed the highest prognostic value for all endpoints and was superior to all other predictors except NYHA class≥II. A multiparametric imaging-based model was superior in predicting the composite endpoint compared to a pre-specified model based on conventional risk factors. Conclusions This network meta-analysis supports the development of multiparametric risk prediction algorithms, including advanced imaging markers additively to conventional risk factors, for refined risk stratification in HCM.

Comparison of Demographic, Clinical, Biochemical, and Imaging Findings in Hypertrophic Cardiomyopathy Prognosis: A Network Meta-Analysis

BackgroundDespite hypertrophic cardiomyopathy (HCM) being the most common inherited heart disease and conferring increased risk for heart failure (HF) and sudden cardiac death (SCD), risk assessment in HCM patients is still largely unresolved. ObjectivesThis study aims to synthesize and compare the prognostic impact of demographic, clinical, biochemical, and imaging findings in patients with HCM. MethodsThe authors searched PubMed, Embase, and Cochrane Library for studies published from 1955 to November 2020, and the endpoints were: 1) all-cause death; 2) an arrhythmic endpoint including SCD, sustained ventricular tachycardia, ventricular fibrillation, or aborted SCD; and 3) a composite endpoint including (1) or (2) plus hospitalization for HF or cardiac transplantation. The authors performed a pairwise meta-analysis obtaining the pooled estimate separately for the association between baseline variables and study endpoints. A random-effects network meta-analysis was subsequently used to comparatively assess the prognostic value of outcome associates. ResultsA total of 112 studies with 58,732 HCM patients were included. Among others, increased brain natriuretic peptide/N-terminal pro–B-type natriuretic peptide, late gadolinium enhancement (LGE), positive genotype, impaired global longitudinal strain, and presence of apical aneurysm conferred increased risk for the composite endpoint. At network meta-analysis, LGE showed the highest prognostic value for all endpoints and was superior to all other associates except New York Heart Association functional class >class II. A multiparametric imaging-based model was superior in predicting the composite endpoint compared to a prespecified model based on conventional risk factors. ConclusionsThis network meta-analysis supports the development of multiparametric risk prediction algorithms, including advanced imaging markers additively to conventional risk factors, for refined risk stratification in HCM. (Long-term prognosis of hypertrophic cardiomyopathy according to genetic, clinical, biochemical and imaging findings: a systemic review and meta-analysis; CRD42020185219)

Entropy of left ventricular late gadolinium enhancement and its prognostic value in hypertrophic cardiomyopathy a new CMR assessment method

PurposeAs a novel metric, entropy generated from late gadolinium enhancement (LGE) cardiac magnetic resonance (CMR) can be utilized to assess tissue heterogeneity. However, it is unknown if it can be utilized for risk stratification in hypertrophic cardiomyopathy (HCM). In addition, it is unknown if LGE entropy correlates with LGE mass%, which is commonly utilized for fibrosis assessment. This research was done to investigate these issues. Materials and methodsPatients with HCM who underwent 3.0-T CMR between January 2015 and January 2020 were prospectively enrolled and classified into low- and high-risk groups according to the AHA/ACC risk stratification guideline for 2020. The LGE entropy was automatically estimated using a generic Python package algorithm. On CMR imaging, the LGE mass% was determined using the CVI 42 software. Endpoint events included sudden cardiac death (SCD), hospital readmission owing to heart failure, and implantable cardioverter defibrillator (ICD) treatment for ventricular arrhythmias. ResultsA total of 109 HCM participants (70 males) were included. During the follow-up (23 ± 7 months), the patients in the high-risk group had higher LGE entropy (p < 0.001) and LGE mass% (p < 0.001) than those in the low-risk group, and patients with endpoint events had higher LGE entropy (p < 0.001) and LGE mass% (p < 0.001) than those without endpoint events. In all participants, there was a link between LGE entropy and LGE mass%, according to the Spearman rank correlation analysis (p < 0.001; r = 0.667). In ROC analysis, the area under the curve (AUC) of LGE entropy was 0.893 (95% CI, 0.794–0.993; P<0.001), AUC of LGE mass% was 0.826 (95% CI, 0.737–0.914; P<0.001), AUC of LVEF was 0.610 (95% CI, 0.473–0.748; P = 0.117) and AUC of 2020 AHA/ACC guideline for risk stratification was 0.716 (95% CI, 0.617–0.815; P = 0.002). According to Kaplan-Meier curves, HCM with a higher LGE entropy (≥cutoff value (<5.873) or ≥ thied tertile (5.540)) were more likely to experience the endpoint events. Following adjustment for the 2020 AHA/ACC guideline for risk categorization, LGE mass%, or decreased LVEF, Cox analysis showed that LGE entropy was independently linked with endpoint events. ConclusionsThe variability and extent of LGE pictures can be reflected by LGE entropy, which is a reliable, usable, and repeatable metric for risk classification in HCM. It is a prognostic indicator of endpoint events that is independent of other risk indicators.

Abstract 10095: Association of Plasma Adiponectin and Leptin Levels With All-Cause Mortality and New-Onset Ventricular Tachyarrhythmias in Patients With Hypertrophic Cardiomyopathy

Introduction: Hypertrophic cardiomyopathy (HCM) is one of the leading causes of sudden cardiac death in the young. The current models to predict ventricular tachycardia/fibrillation (VT/VF) and mortality perform poorly. Adipokines are secreted from the adipose tissue and regulate cardiac inflammation, fibrosis, and hypertrophy. Among the adipokines, adiponectin and leptin are related to cardiac remodeling in HCM. The present study examined the association of plasma adiponectin and leptin levels with all-cause mortality and VT/VF in patients with HCM. Hypothesis: Plasma adiponectin and leptin levels at enrollment are associated with all-cause mortality and VT/VF in patients with HCM. Methods: We performed a multicenter prospective cohort study of patients with HCM. We measured plasma adiponectin and leptin levels at enrollment. The outcome was a composite of all-cause mortality and new-onset VT/VF. After dividing the cohort into four groups according to the adiponectin and leptin levels, we compared the risk of the outcome event using the Cox proportional hazards model adjusting for age, body mass index, left atrium diameter, and maximum left ventricular wall thickness, using the largest group as a reference. Results: During a median follow-up of 3.3 years, the outcome event occurred in 37 out of 402 patients. The four groups divided by adiponectin and leptin levels had different risks of the outcome event (log-rank P &lt;0.001). The Cox proportional hazards model revealed that the High-Adiponectin, Low-Leptin group had a significantly higher risk (adjusted HR 5.02, 95% CI 1.63-15.47, P =0.005. Figure ) compared with the reference (Low-Adiponectin, High-Leptin) group. Conclusions: The combination of high plasma adiponectin and low leptin levels is independently associated with mortality and new-onset VT/VF in patients with HCM. These adipokines have a potential to become novel biomarkers for risk stratification in HCM to improve the current prediction models.

Additional prognostic values of strain and strain rate over late gadolinium enhancement in hypertrophic cardiomyopathy patients

BackgroundLate gadolinium enhancement (LGE) has some shortcomings in the risk stratification in hypertrophic cardiomyopathy (HCM). Myocardial strain/strain rate (SR) can be acquired from unenhanced cardiovascular magnetic resonance (CMR) images and detect cardiac dysfunction sensitively. The present study aimed to evaluate the additional prognostic values of myocardial strain/SR beyond LGE for the risk stratification in patients with HCM. Methods293 patients with HCM who underwent CMR were enrolled in this prospective study. LGE/left ventricular (LV) mass, LV global strain, and SR were acquired based on CMR. Also, conventional clinical, echocardiography, and CMR parameters and established risk factors for HCM were evaluated. Results14/293 patients had major adverse cardiovascular events (MACEs) during the median follow-up of 15.0 months, including eight all-cause deaths, four resuscitated cardiac arrests and two cardiac transplantations. Peak systolic (PS)-global longitudinal SR (GLSR) was independently associated with MACEs (hazard ratio: 15.297, P < 0.001) after adjusting for conventional clinical characteristics, echocardiography, and CMR parameters. The model constructed by conventional variables plus PS-GLSR had significantly stronger predictive ability than the model constructed by conventional variables plus LGE/LV mass (C-statistic: 0.850 vs 0.708, P = 0.030). The addition of PS-GLSR to the conventional model also significantly improved the sensitivity (92.9% vs 71.4%) and specificity (71.0% vs 57.3%), and lowered false positives (81 patients vs 119 patients) compared to the addition of LGE/LV mass. ConclusionLV PS-GLSR derived from CMR has the potential to be a novel biomarker for risk stratification of HCM and provide additional prognostic value over LGE/LV mass.

Natural language processing for identification of hypertrophic cardiomyopathy patients from cardiac magnetic resonance reports

BackgroundCardiac magnetic resonance (CMR) imaging is important for diagnosis and risk stratification of hypertrophic cardiomyopathy (HCM) patients. However, collection of information from large numbers of CMR reports by manual review is time-consuming, error-prone and costly. Natural language processing (NLP) is an artificial intelligence method for automated extraction of information from narrative text including text in CMR reports in electronic health records (EHR). Our objective was to assess whether NLP can accurately extract diagnosis of HCM from CMR reports.MethodsAn NLP system with two tiers was developed for information extraction from narrative text in CMR reports; the first tier extracted information regarding HCM diagnosis while the second extracted categorical and numeric concepts for HCM classification. We randomly allocated 200 HCM patients with CMR reports from 2004 to 2018 into training (100 patients with 185 CMR reports) and testing sets (100 patients with 206 reports).ResultsNLP algorithms demonstrated very high performance compared to manual annotation. The algorithm to extract HCM diagnosis had accuracy of 0.99. The accuracy for categorical concepts included HCM morphologic subtype 0.99, systolic anterior motion of the mitral valve 0.96, mitral regurgitation 0.93, left ventricular (LV) obstruction 0.94, location of obstruction 0.92, apical pouch 0.98, LV delayed enhancement 0.93, left atrial enlargement 0.99 and right atrial enlargement 0.98. Accuracy for numeric concepts included maximal LV wall thickness 0.96, LV mass 0.99, LV mass index 0.98, LV ejection fraction 0.98 and right ventricular ejection fraction 0.99.ConclusionsNLP identified and classified HCM from CMR narrative text reports with very high performance.

Comparison of Nonclassic and Classic Phenotype of Hypertrophic Cardiomyopathy Focused on Prognostic Cardiac Magnetic Resonance Parameters: A Single-Center Observational Study.

Patients with nonclassic phenotypes (NCP)—more advanced stages of hypertrophic cardiomyopathy (HCM)—constitute an intriguing and heterogeneous group that is difficult to diagnose, risk-stratify, and treat, and often neglected in research projects. We aimed to compare cardiac magnetic resonance (CMR) parameters in NCP versus classic phenotypes (CP) of HCM with special emphasis given to the parameters of established and potential prognostic importance, including numerous variables not used in everyday clinical practice. The CMR studies of 88 patients performed from 2011 to 2019 were postprocessed according to the study protocol to obtain standard and non-standard parameters. In NCP, the late gadolinium enhancement extent expressed as percent of left ventricular mass (%LGE) and left ventricular mass index (LVMI) were higher, left atrium emptying fraction (LAEF) was lower, minimal left atrial volume (LAV min) was greater, and myocardial contraction fraction (MCF) and left ventricular global function index (LVGFI) were lower than in CP (p < 0.001 for all). In contrast, HCM risk score and left ventricular maximal thickness (LVMT) were similar in NCP and CP patients. No left ventricular outflow tract obstruction (LVOTO) was observed in the NCP group. Left ventricular outflow tract diameter (LVOT), aortic valve diameter (Ao), and LVOT/Ao ratio were significantly higher and anterior mitral leaflet (AML)/LVOT ratio was lower in the NCP compared to the CP group. In conclusion, significant differences in nonstandard CMR parameters were noted between the nonclassic and classic HCM phenotypes that may contribute to future studies on disease stages and risk stratification in HCM.

Anatomical-MRI Correlations in Adults and Children with Hypertrophic Cardiomyopathy.

Hypertrophic Cardiomyopathy (HCM) is the most frequent hereditary cardiovascular disease and the leading cause of sudden cardiac death in young individuals. Advancements in CMR imaging have allowed for earlier identification and more accurate prognosis of HCM. Interventions aimed at slowing or stopping the disease’s natural course may be developed in the future. CMR has been validated as a technique with high sensitivity and specificity, very few contraindications, a low risk of side effects, and is overall a good tool to be employed in the management of HCM patients. The goal of this review is to evaluate the magnetic resonance features of HCM, starting with distinct phenotypic variants of the disease and progressing to differential diagnoses of athlete’s heart, hypertension, and infiltrative cardiomyopathies. HCM in children has its own section in this review, with possible risk factors that are distinct from those in adults; delayed enhancement in children may play a role in risk stratification in HCM. Finally, a number of teaching points for general cardiologists who recommend CMR for patients with HCM will be presented.

Assessing the relationship between systemic immune-inflammation index and mortality in patients with hypertrophic cardiomyopathy.

BackgroundThis study investigates the predictive value of the systemic immune-inflammation index (SII), which was calculated as platelet × neutrophil/lymphocyte ratio, for all-cause mortality in patients with hypertrophic cardiomyopathy (HCM).MethodsA total of 360 HCM patients were enrolled. They were divided into three groups based on the tertiles of baseline SII. The association between SII and all-cause mortality was analyzed.ResultsThere were 53 HCM patients who died during a mean follow-up time of 4.8 years (min: 6 days and max: 10.8 years), and the mortality rate was 3.0 per 100 person years. The cumulative mortality rate was significantly different among the three tertiles of SII (P = 0.004), and the mortality rate in tertile 3 was much higher than that in the first two tertiles. In reference to tertile 1, the fully adjusted hazard ratios of all-cause mortality were 1.02 for the tertile 2 (95% confidence interval [CI]: 0.45–2.31, P = 0.966) and 2.31 for tertile 3 (95% CI: 1.10–4.87, P = 0.027). No significant interactions between SII and other variables were observed during subgroup analysis. The discriminative power was better for mid-term outcome than that for short-term or long-term outcomes. Sensitivity analyses including patients with normal platelet and white blood cell count have revealed similar results.ConclusionSII was a significant risk factor for all-cause mortality in HCM patients. However, the discriminative power was poor to moderate. It could be used in combination with other risk factors in mortality risk stratification in HCM.