Hypertrophic Cardiomyopathy Risk-SCD Research Articles

Validation of the HCM Risk-SCD model in patients with hypertrophic cardiomyopathy and future perspectives

Abstract Background/Introduction The fact that hypertrophic cardiomyopathy (HCM) is associated with sudden cardiac death (SCD) due to malignant ventricular arrhythmias underlies its clinical importance (1). SCD in patients with HCM is often an unpredictable event, occurring without previous warning signs or symptoms, and is most common in the young middle-aged group (2). The greatest dilemma in the management of HCM patients is to identify the high-risk population for SCD. The HCM risk- SCD model provides a useful convenience in determining the risk of SCD in patients with HCM even though some patients with low-risk scores still remain at risk of SCD (3). These results have increased the interest in additional strategies to improve the existing risk model. Purpose Hence, the aim of our study was to assess the performance of HCM Risk-SCD in a large series of consecutive patients with HCM who had been followed up in a tertiary centre. Methods The study population consisted of 389 consecutive HCM patients who had been followed up between 2004 and 2021. Demographic and clinical characteristics estimated 5-year risk using the HCM Risk-SCD model were compiled and survival data were collected during follow-up. Patients were divided into 2 groups according to their long-term survival and HCM risk-SCD scores of these two groups were compared. Results The long-term mortality was observed in 47 patients out of 389 patients in the mean follow-up of 55.5 ± 12.7 months. The mean HCM Risk-SCD of surviving patients was significantly lower than that of non-survivors (1.8% vs. 3.0%, p<0.001). The HCM Risk-SCD score was above 6% in 9 (2.6%) survivors and 9 (19.1%) non-survivors (p<0.001). Considering the Kaplan-Meier curve based on the 6% HCM Risk-SCD score, patients at ≥6% risk also had a significantly higher long-term risk of death compared to those with <6% (log-rank test value: 33.72, p<0.001) (Figure 1). The ROC curve based on the HCM Risk-SCD score had 61% sensitivity and 61% specificity for risk for 2.0%, 38% sensitivity and 99% specificity for ≥4%, 17% sensitivity and 99% specificity for ≥6% (Figure 2). Conclusion(s) In conclusion, the current study demonstrates that the HCM risk-SCD model, while easily calculable and clinically useful, does not reliably identify a significant subset of patients with HCM who will potentially be at lifetime risk of SCD. Identifying patients with hypertrophic cardiomyopathy at high risk for SCD who deserve ICD therapy is a critical management priority. A new risk algorithm that can detect the SCD risk of HCM patients with higher sensitivity is needed.Figure 1Figure 2

Prognostic role of gene variants in sudden cardiac death risk associated to paediatric hypertrophic cardiomyopathy

Abstract Introduction Genetic testing plays an important role in diagnosis of hypertrophic cardiomyopathy (HCM), being sarcomeric genes commonly involved, particularly MYBPC3. However, arrhythmic risk related to genotype remains unclear in adults and almost unexplored in children. Hence, current sudden cardiac death (SCD) risk calculators do not include genetic information. Purpose To analyse risk of arrhythmic events associated with causal variants in MYBPC3 respecting to other genes in a paediatric cohort with non-syndromic HCM from a cardiomyopathy referral centre. Methods This retrospective study included patients with non-syndromic HCM 0-18 years old between 2009-2022. Demographic, clinical, and genetic data were collected. Genetic variants pathogenicity followed American College of Medical Genetics criteria. A positive genetic test was considered if a likely pathogenic or pathogenic variant in HCM related genes was found. Considered outcomes were SCD or a major arrhythmic cardiac event (MACE) within 5 years follow-up: recovered SCD, appropriate ICD therapy, or sustained ventricular tachycardia. Some SCD-risk estimation models (in 5 years) as HCM Risk-SCD model for patients >=15 y.o and/or 55 kg, ESC Guidelines paediatric algorithm, and HCM Risk-Kids model were applied. Results 77 patients were diagnosed with non-syndromic HCM. A causal variant was found in 45/73 (62%). No significant differences in cardiac phenotype were found related to genes. 10/77 patients (13%) presented a MACE in 5 years follow-up. A positive genetic study was significantly associated with having an event (p=0.011). Most patients with a positive genetic test harboured MYBPC3 variants (21/45, 47%), however only 2 patients who suffered a MACE had a causal variant in MYBPC3. Those with causal variants in genes other than MYBPC3 presented more and earlier events (p=0.022). Risk of having a MACE during follow-up was higher when presenting causal variants in genes other than MYBPC3: Hazard Ratio 18.5 (95% CI 2.31, 148), p=0.006. Applying HCM Risk-SCD calculator, model had better predictive discrimination when variable "causal variant in gene other than MYBPC3" was added in multivariate analysis, with high-risk category >=6% (C-statistic =0.931 vs 0.844) and intermediate-risk category 4-6% (C-statistic =0.845 vs 0.514). Same occurred with ESC Guidelines algorithm, adding that variable to 2 risk factors category (C-statistic =0.881 vs 0.742) or 1 risk factor (C-statistic =0.844 vs 0.635). HCM Risk-Kids also improved its predictive discrimination adding the genetic value to high-risk category >=6% (C-statistic =0.896 vs 0.796) and intermediate-risk (C-statistic =0.821 vs 0.506). Conclusions Genotype may have prognostic value in SCD risk in HCM in children. Our results suggests that causal genetic variants in genes other than MYBPC3 can lead to higher risk of SCD. Genetic information might be considered for future models of arrhythmic risk in children with HCM.

Novel electric predictors of lethal arrhythmic event in patients with hypertrophic cardiomyopathy

Abstract Background Little is known regarding the association between electrical markers and lethal arrhythmic events (LAE) in patients with hypertrophic cardiomyopathy (HCM). This study aimed to identify the electrical predictors of LAE in adult patients with HCM. Methods This study was a retrospective analysis of patients with HCM at a single center from 1998 to 2021. LAE was defined as a composite outcome of (1) sustained ventricular arrhythmia, (2) aborted sudden cardiac death (SCD), (3) implantable cardioverter defibrillator (ICD) implantation, and (4) appropriate ICD shock. A 12-lead electrocardiography was performed at the time of diagnosis. Results A total of 611 patients with HCM were analyzed, and 48 (7.8%) experienced LAE. Patients who experienced LAE were diagnosed at a younger age and more frequently had history of ventricular arrhythmia, new-onset atrial fibrillation (AF) or non-sustained ventricular tachycardia. New-onset AF, an increase in the QTc interval, and the absence of massive LVH were associated with LAE risk. In addition to conventional markers of HCM Risk-SCD, consideration of the QTc interval and massive LVH on electrocardiography improved the prediction of LAE (area under curve 0.682 to 0.740). Further inclusion of new-onset AF, history of ventricular arrhythmia, HCM type, and left ventricular mass index improved the predictability to 0.867. Conclusion An increase in the QTc interval, the absence of a massive LVH pattern on electrocardiography (ECG), and new-onset AF were independently associated with an increased risk of LAE. Comprehensive stratification using electrical markers improves the prediction of LAE when combined with conventional markers.

Effectiveness of contemporary risk stratification in patients with hypertrophic cardiomyopathy: a pilot study

Abstract Introduction Risk stratification and primary prevention of sudden cardiac death (SCD) in patients with hypertrophic cardiomyopathy (HCM) is a challenging discipline. When using current stratification systems, there is always a compromise between sensitivity and specificity. Objective In our pilot study, we sought to determine the incidence of SCD and the effectiveness of stratification systems, i.e., the ESC HCM Risk-SCD score and the system of individual major risk factors (RF) according to ACC/AHA in patients followed in an expert center. Methods Patients with HCM were risk-stratified and followed for 10 ± 8 years at the referral HCM center. Results Five hundred and five patients were stratified, and 71 (14%) were implanted with a cardioverter-defibrillator (ICD) based on risk stratification. ICD patients were stratified at age 39 ± 17 years, of which 26 (35%) were women, maximal left ventricular wall thickness (MLWT) was 23 ± 7 mm, and left atrial dimension (LA) 46 ± 7 mm. During follow-up, 12 (17%) patients had ≥ 1 appropriate ICD therapy at age 46 ± 19 years. Patients with ≥ 1 appropriate ICD therapy had an average 5-year ESC score of 1.8 ± 0.4% and an average ACC/AHA major RF of 1.4 ± 0.8, MLWT 25 ± 6 mm, LA 47 ± 7 mm. None of the ICD patients died of SCD. Five (7%) patients suffered from ICD complications, including 4 (6%) inappropriate shock, and one patient experienced infective endocarditis requiring system extraction. During follow-up, 118 (23%) patients died, of which 28 (6%) from HCM-related causes, 12 (2%) from stroke, 11 (2%) from advanced heart failure, one perioperatively (myectomy) and 4 (1%) patients died suddenly (SCD). The mean age of SCD patients at the time of stratification was 59 ± 14 years; all were male, MLWT 18 ± 5 mm, LA 49 ± 2 mm, mean ESC score 2.0 ± 0.9%, and three (75%) had no RF present according to ACC/AHA. The ESC HCM Risk-SCD score was markedly less sensitive (sensitivity 56%; 95% CI 21-86) but more specific (specificity 98%; 95% CI 96-99) than the ACC/AHA approach (sensitivity 77%; 95% CI 46-95; and specificity 71%; 95% CI 67-75) (Figure). Conclusion With current risk stratification, albeit imperfect, SCD is rare in HCM patients managed at an expert center.

Machine Learning in Hypertrophic Cardiomyopathy: Nonlinear Model From Clinical and CMR Features Predicting Cardiovascular Events

BackgroundThe cumulative burden of hypertrophic cardiomyopathy (HCM) is significant, with a noteworthy percentage (10%-15%) of patients with HCM per year experiencing major adverse cardiovascular events (MACEs). A current risk stratification scheme for HCM had only limited accuracy in predicting sudden cardiac death (SCD) and failed to account for a broader spectrum of adverse cardiovascular events and cardiac magnetic resonance (CMR) parameters. ObjectivesThis study sought to develop and evaluate a machine learning (ML) framework that integrates CMR imaging and clinical characteristics to predict MACEs in patients with HCM. MethodsA total of 758 patients with HCM (67% male; age 49 ± 14 years) who were admitted between 2010 and 2017 from 4 medical centers were included. The ML model was built on the internal discovery cohort (533 patients with HCM, admitted to Fuwai Hospital, Beijing, China) by using the light gradient-boosting machine and internally evaluated using cross-validation. The external test cohort consisted of 225 patients with HCM from 3 medical centers. A total of 14 CMR imaging features (strain and late gadolinium enhancement [LGE]) and 23 clinical variables were evaluated and used to inform the ML model. MACEs included a composite of arrhythmic events, SCD, heart failure, and atrial fibrillation–related stroke. ResultsMACEs occurred in 191 (25%) patients over a median follow-up period of 109.0 months (Q1-Q3: 73.0-118.8 months). Our ML model achieved areas under the curve (AUCs) of 0.830 and 0.812 (internally and externally, respectively). The model outperformed the classic HCM Risk-SCD model, with significant improvement (P < 0.001) of 22.7% in the AUC. Using the cubic spline analysis, the study showed that the extent of LGE and the impairment of global radial strain (GRS) and global circumferential strain (GCS) were nonlinearly correlated with MACEs: an elevated risk of adverse cardiovascular events was observed when these parameters reached the high enough second tertiles (11.6% for LGE, 25.8% for GRS, −17.3% for GCS). ConclusionsML-empowered risk stratification using CMR and clinical features enabled accurate MACE prediction beyond the classic HCM Risk-SCD model. In addition, the nonlinear correlation between CMR features (LGE and left ventricular pressure gradient) and MACEs uncovered in this study provides valuable insights for the clinical assessment and management of HCM.

Additional factors associated with sudden cardiac death in HCM patients

Abstract Background Hypertrophic cardiomyopathy (HCM) is a primary myocardial disease characterized by an increase in the thickness of the left ventricular (LV) wall, which is not explained only by abnormal loading conditions. Sudden cardiac death (SCD) is the most devastating complication of HCM occurring in asymptomatic or younger patients without warning. Purpose To evaluate additional SCD risk factors in Ukrainian population of HCM patients. Materials and methods We retrospectively evaluated 350 consecutive HCM patients that were followed from 2006 to 2021 in our Cardiological Department. General clinical examination, standard 12-lead ECG, transthoracic echocardiography and 24 hours Holter ECG monitoring data were estimated. The 5-year SCD risk was calculated according to the HCM Risk-SCD score. The endpoint of the study was SCD and its surrogates, including adequate performance of the implantable cardioverter-defibrillator and successful resuscitation. Results Follow-up time was 5.0 (1.5-9.5) years. During this time, 16 patients (4.6%) reached the end point, which was 0.9%/year. According to the HCM Risk-SCD score, 5 (31.3%) of this group had a high risk of SCD (≥ 6%) and 3 (18.8%) had an intermediate risk (≥ 4% and &amp;lt; 6%). In multivariable Cox regression analysis adjusted for conventional SCD risk factors it was found that independent predictors of SCD were unexplained syncope (HR 3.81, 95% CI 1.11-13.12, p=0.034), systolic blood pressure (SBP) (HR 0.97 , 95% CI 0.94- 0.99, p=0.026), "infarct-like" ST elevation on ECG (HR 6.81, 95% CI 2.09-22.16, p=0.001) and PQ interval duration (HR 1.03, 95% CI 1.01-1.05, p=0.002), Harrell's C-index 0.84, 95% CI 0.73-0.95, p &amp;lt; 0.0001). Conclusions In our study HCM Risk-SCD score predicted SCD or surrogates only in 50% of cases. In order to improve the risk stratification some additional independent predictors of SCD can be proposed. ECG parameters ("infarct-like" ST elevation and PQ interval duration) and level of SBP were found to have SCD predictive value.

The Feasibility of Left Ventricular Strain and Strain Rate for Evaluating Hypertrophic Cardiomyopathy with Risk Factors of Sudden Cardiac Death by Feature-Tracking CMR

Sudden cardiac death (SCD) represents the most severe complication of hypertrophic cardiomyopathy (HCM). However, the relation between strain, strain rate (SR), and risk factors in SCD risk stratification remains elusive. The study aimed to assess the attenuation of strain and SR in HCM by feature tracking cardiac magnetic resonance. All strain and SRs were obtained automatically by feature tracking, with manual adjustment of endocardial and epicardial borders. Strain indicators included left ventricular global longitudinal, circumferential, global radial strain (GRS), peak diastolic-longitudinal, circumferential, and radial SR. Patients were categorized into high-risk and low-risk groups for SCD based on the 2020 American Heart Association/American College HCM risk-SCD model. The correlation between strain/SR and SCD risk factors was assessed through Spearman correlation analysis. Furthermore, a multivariate logistic regression analysis was conducted to explore the factors that influence SCD risk in HCM patients. A total of 105 HCM patients were analyzed in this study, including 38 patients in the high-risk group, and 67 patients in the low-risk group. Compared with the low-risk group, the high-risk group exhibited significantly worse strain and SR (p <0.001). Furthermore, both circumferential and GRS and SR exhibited meaningful associations with risk factors for SCD. Additionally, GRS emerged as an independent risk factor for predicting heightened SCD risk in HCM patients (p <0.001). In conclusion, left ventricular strain and SR based on feature tracking-cardiac magnetic resonance can be evaluated for SCD risk and are strongly associated with SCD risk factors.

ECG changes and their prognostic value for the development of sudden cardiac death in HCM patients

Background. Hypertrophic cardiomyopathy (HCM) is a primary myocardial disease characterized by an increase in the left ventricular (LV) wall thickness, which is not explained only by abnormal loading conditions. The development of sudden cardiac death (SCD) is one of the most dangerous complications of HCM. The aim of our study was to evaluate the prognostic value of electrocardiography (ECG) changes for the development of SCD in the Ukrainian population of patients with HCM. Materials and methods. We evaluated 350 patients with HCM who were examined in the City Clinical Hospital 8 (Kharkiv, Ukraine) from 2006 to 2021. The diagnosis of HCM was made in accordance with the current guidelines of the European Society of Cardiology. Clinical and instrumental data of patients with HCM were analyzed retrospectively, including general clinical data, 12-lead ECG, echocardiography, Holter monitoring, calculation of the 5-year risk of SCD according to the HCM Risk-SCD tool. The endpoint of the study was SCD and its surrogates, including adequate performance of the implantable cardioverter-defibrillator and the state after a successful resuscitation. Results. Follow-up was 5.0 (1.5–9.5) years. During this time, 16 patients (4.6 %) reached the endpoint, which was 0.9 %/year. According to the HCM Risk-SCD, 5 (31.3 %) patients in this group were at a high (≥ 6 %) and 3 (18.8 %) were at an intermediate risk of SCD (≥ 4 and &lt; 6 %). A multivariable Cox regression analysis has shown that independent predictors of SCD are syncope (hazard ratio (HR) 3.81, 95% confidence interval (CI) 1.11–13.12, p = 0.034), systolic blood pressure (HR 0.97, 95% CI 0.94–0.99, p = 0.026), ECG with “infarction-like” ST elevation (HR 6.81, 95% CI 2.09–22.16, p = 0.001) and PQ interval value (HR 1.03, 95% CI 1.01–1.05, p = 0.002), Harrell’s C-index (HR 0.84, 95% CI 0.73–0.95, p &lt; 0.0001). Conclusions. The proposed HCM Risk-SCD tool was not effective enough in predicting SCD in our study. In order to improve the risk stratification, ECG changes (“infarction-like” ST elevation and PQ interval prolongation) and systolic blood pressure lowering can be used, which were found to be independent predictors of SCD risk.

Prolonged mHealth-Based Arrhythmia Monitoring in Patients With Hypertrophic Cardiomyopathy (HCM-PATCH): Protocol for a Single-Center Cohort Study.

Patients with hypertrophic cardiomyopathy (HCM) are at increased risk of sudden cardiac death (SCD) due to ventricular arrhythmias and other arrhythmias. Screening for arrhythmias is mandatory to assess the individual SCD risk, but long-term electrocardiography (ECG) is rarely performed in routine clinical practice. Intensified monitoring may increase the detection rate of ventricular arrhythmias and identify more patients with an increased SCD risk who are potential candidates for the primary prophylactic implantation of an implantable cardioverter-defibrillator. To date, reliable data on the clinical benefit of prolonged arrhythmia monitoring in patients with HCM are rare. This prospective study aims to measure the prevalence of ventricular arrhythmias in patients with HCM observed by mobile health (mHealth)-based continuous rhythm monitoring over 14 days compared to standard practice (a 24- and 48-h long-term ECG). The frequency of ventricular arrhythmias in this 14-day period is compared with the frequency in the first 24 or 48 hours for the same patient (intraindividual comparison). Following the sample size calculation, 34 patients with a low or intermediate risk for SCD, assessed by the HCM Risk-SCD calculator, will need to be recruited in this single-center cohort study between June 2023 and February 2024. All patients will receive an ECG patch that records their heart activity over 14 days. In addition, cardiac magnetic resonance imaging and genetic testing data will be integrated into risk stratification. All patients will be asked to complete questionnaires about their symptoms; previous therapy; family history; and, at the end of the study, their experience with the ECG patch-based monitoring. The Hypertrophic Cardiomyopathy: Clinical Impact of a Prolonged mHealth-Based Arrhythmia Monitoring by Single-Channel ECG (HCM-PATCH) study investigates the prevalence of nonsustained ventricular tachycardia (ie, ≥3 consecutive ventricular beats at a rate of 120 beats per minute, lasting for <30 seconds) in low- to intermediate-risk patients with HCM (according to the HCM Risk-SCD calculator) with additional mHealth-based prolonged rhythm monitoring. The study was funded by third-party funding from the Department of Cardiology and Intensive Care Medicine, University Hospital Ostwestfalen-Lippe of Bielefeld University in June 2023 and approved by the institutional review board in May 2023. Data collection began in June 2023, and we plan to end the study in February 2024. Of the 34 patients, 26 have been recruited. Data analysis has not yet taken place. Publication of the results is planned for the fall of 2024. Prolonged mHealth-based rhythm monitoring could lead to differences in the prevalence of arrhythmias compared to 24- and 48-hour long-term ECGs. This may lead to improved identification of patients at high risk and trigger therapeutic interventions that may provide better protection from SCD or atrial fibrillation-related complications such as embolic stroke. Deutsches Register Klinischer Studien DRKS00032144; https://tinyurl.com/498bkrx8. DERR1-10.2196/52035.

Validation of the HCM Risk-SCD model in patients with hypertrophic cardiomyopathy and future perspectives.

The hypertrophic cardiomyopathy (HCM) risk- sudden cardiac death (SCD) model provides a convenient tool for determining the risk of SCD in patients with HCM even though some patients with low-risk scores still remain at risk of SCD. Hence, the aim of our study was to assess the performance of HCM Risk-SCD in a large series of consecutive patients with HCM who had been followed up in a tertiary center. The study population consisted of 389 consecutive HCM patients who had been followed up between 2004 and 2021. Demographic and clinical characteristics, estimated 5-year risk using the HCM Risk-SCD model, were compiled, and survival data were collected during follow-up. Patients were divided into 2 groups according to their long-term survival, and HCM risk-SCD scores of these two groups were compared. The long-term mortality was observed in 47 patients out of 389 patients in the during a mean follow-up of 55.5 ± 12.7 months. The mean HCM Risk-SCD score of surviving patients was significantly lower than that of non-survivors (1.8% vs. 3.0%, p < .001). The HCM Risk-SCD score was above 6% in nine (2.6%) survivors and nine (19.1%) non-survivors (p < .001). The ROC curve based on the HCM Risk-SCD score had 61% sensitivity and 61% specificity for risk threshold of for 2.0%, 38% sensitivity and 99% specificity a threshold of ≥4%, 17% sensitivity, and 99% specificity for a threshold of ≥6%. A new risk algorithm with higher sensitivity is needed, although the HCM risk-SCD model is still quite useful in identifying patients at a high risk for SCD.

Long-term follow-up in patients with hypertrophic cardiomyopathy after defibrillator implantation: analysis of appropriate and inappropriate therapy

Abstract Background Treatment with implantable cardioverter-defibrillators (ICD) is effective for prevention of sudden cardiac death (SCD) in patients with hypertrophic cardiomyopathy (HCM). Assessment of SCD risk and identification of patients most likely to benefit from primary prevention ICD is challenging. Purpose To investigate the long-term incidence of appropriate and inappropriate ICD therapy in patients with HCM. Methods This was a retrospective cohort study including all patients with HCM and ICDs implanted between 1995 to 2022 in our region (population 2.6 million). Both patients treated with primary and secondary prevention ICD were included. Data was retrieved from medical records. Patients with an ICD implanted for primary prevention were stratified into risk groups according to European Society of Cardiology HCM Risk-SCD score. Results We included 187 patients (65% male) with HCM and ICDs implanted for primary (80%) or secondary (20%) prevention. The median age at ICD implantation was 50 years (IQR: 40 to 61 years). During a mean follow-up of 9 years (IQR: 4 to 12 years), 53 patients (28%) experienced appropriate ICD therapy (antitachycardia pacing and/or shock), while 17 (9%) patients received inappropriate therapy. Patients with an ICD as secondary prevention were almost twice as likely to receive appropriate ICD therapy compared to patients with a primary prevention ICD (42% vs. 25%, p=0.04). The proportion of patients receiving appropriate shocks was 7 times higher in patients with an HCM Risk-SCD score ≥6% compared to patients with a risk score &amp;lt;4% (29% vs. 4%, p&amp;lt;0.001). There was no significant difference in the proportion of appropriate shocks between patients with a HCM Risk-SCD score ≥6% and patients with a risk score of 4%-6% (29% vs. 21%, p=0.49). (Figure 1). Conclusion One in four patients with HCM treated with an ICD experienced appropriate device intervention during 9 years of follow up. Patients with an HCM Risk-SCD score ≥6% had a 7-fold higher risk of appropriate ICD therapy compared to patients with an HCM Risk-SCD score &amp;lt;4%. There was no significant difference in the risk of appropriate shock therapy between patients with a risk score ≥6% and patients with a risk score of 4%-6%. The findings indicate the need for improved selection of patient with HCM for implantation of ICD’s.

Abstract 19218: Prognosis of Apical Hypertrophic Cardiomyopathy in Patients With Implantable Cardioverter Defibrillators

Aims: This Short Communication aims to identify the difference between the prognoses of apical and other types of hypertrophic cardiomyopathy (HCM) in patients with implantable cardioverter defibrillators (ICDs). Methods: We retrospectively analysed the database of our ICD clinic. All patients were implanted with ICDs from October 2006 to August 2017. We classified patients with HCM based on left ventricular (LV) outflow tract obstruction (LVOTO) and midventricular obstruction (MVO), in addition to apical HCM and other non-obstructive HCM types. Patient backgrounds, incidences of appropriate ICD therapies, hospitalizations for heart failure, electrical storms, and total deaths were examined. Results: A total of 64 consecutive Japanese patients with HCM and ICDs were enrolled in this study. The mean follow-up period was 86 ± 24 months, the mean age was 65 ± 14 years, and 83% of the patients were male. The LV ejection fraction was 56 ± 14%, the LV max wall-thickness was 19 ± 7 mm, 9.0% had LV apical aneurysms, and the HCM Risk-SCD was 4.4 ± 2.1. We classified the patients into two groups: 14 patients with apical HCM and 50 patients with other types of HCM. During the follow-up periods, there was no significant difference in the incidence of electrical storm, hospitalization for heart failure, and death between the 2 groups (p=0.11, p=0.60, p=0.39, respectively). Appropriate therapies occurred in 6 of 14 (43%) patients with apical HCM patients and 5 of 50 (10%) patients with other types of HCM (p=0.010). Conclusions: Compared with patients with other types of HCM, patients with apical HCM have a comparative prognosis, and treatment of ventricular arrhythmias should be strongly considered.

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

Sudden Death Risk Assessment in Hypertrophic Cardiomyopathy Across the Lifespan: Reconciling the American and European Approaches.

Hypertrophic cardiomyopathy (HCM) is the most prevalent inherited cardiac disease. Since the modern description of HCM more than seven decades ago, great focus has been placed on preventing its most catastrophic complication: sudden cardiac death (SCD). Implantable cardioverter-defibrillators (ICD) have been recognized to provide effective prophylactic therapy. Over the years, two leading societies, the European Society of Cardiology (ESC) and the American Heart Association/American College of Cardiology (AHA/ACC), have proposed risk stratification models to assess SCD in adults. European guidelines rely on a risk calculator, the HCM Risk-SCD, while American guidelines propose a stand-alone risk factor approach. Recently, risk prediction models were also developed in the pediatric population. This article reviews the latest recommendations on the risk stratification of SCD in HCM and summarises current indications for ICD use.

Deep learning-derived 12-lead electrocardiogram-based genotype prediction for hypertrophic cardiomyopathy: a pilot study

Objective: Given the psychosocial and ethical burden, patients with hypertrophic cardiomyopathy (HCMs) could benefit from the establishment of genetic probability prior to the test. This study aimed to develop a simple tool to provide genotype prediction for HCMs. Methods: A convolutional neural network (CNN) was built with the 12-lead electrocardiogram (ECG) of 124 HCMs who underwent genetic testing (GT), externally tested by predicting the genotype on another HCMs cohort (n = 54), and compared with the conventional methods (the Mayo and Toronto score). Using a third cohort of HCMs (n = 76), the role of the network in risk stratification was explored by calculating the sudden cardiac death (SCD) risk scorers (HCM risk-SCD) across the predicted genotypes. Score-CAM was employed to provide a visual explanation of the network. Results: Overall, 80 of 178 HCMs (45%) were genotype-positive. Using the 12-lead ECG as input, the network showed an area under the curve (AUC) of 0.89 (95% CI, 0.83–0.96) on the test set, outperforming the Mayo score (0.69 [95% CI, 0.65–0.78], p < 0.001) and the Toronto score (0.69 [95% CI, 0.64–0.75], p < 0.001). The network classified the third cohort into two groups (predicted genotype-negative vs. predicted genotype-positive). Compared with the former, patients predicted genotype-positive had a significantly higher HCM risk-SCD (0.04 ± 0.03 vs. 0.03 ± 0.02, p <0.01). Visualization indicated that the prediction was heavily influenced by the limb lead. Conclusions: The network demonstrated a promising ability in genotype prediction and risk assessment in HCM.

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. The purpose of this study was 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 ≤2.42 L/min/m2. During median follow-up of 4.3 years, 51 patients reached the endpoint. Reduced cardiac index independently increased the risk of cardiovascular death (adjusted hazard ratio [aHR] 2.976; P = .007), SCD (aHR 6.385; P = .001), and all-cause death (aHR 2.428; P = .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 = .018) and a net reclassification improvement of 0.560 (P = .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.

Prevalence, characteristics, and natural history of apical phenotype in a large cohort of patients with hypertrophic cardiomyopathy

BackgroundApical hypertrophic cardiomyopathy (ApHCM) is a variant of hypertrophic cardiomyopathy (HCM) with distinct imaging and clinical characteristics. Data on the prognosis of this HCM subgroup appear conflicting. Our study aims to clarify the natural history of ApHCM and identify predictors of outcomes. Materials and methodsA total of 856 patients with HCM were retrospectively examined. ApHCM was defined as asymmetric left ventricular hypertrophy confined predominantly at the apex, either isolated (pure ApHCM type) or with co-existent hypertrophy of the interventricular septum (mixed ApHCM). Echocardiographic, clinical, and survival data were compared between individuals with ApHCM and non-ApHCM. ResultsA total of 143 (16.7%) patients were diagnosed with ApHCM. Compared with non-ApHCM, subjects with apical HCM were diagnosed at an older age and had better echocardiographic indices and more comorbidities at baseline. Apical aneurysms were more prevalent among the ApHCM phenotype (6.3% vs. 1.7%, p = 0.003). During a mean follow-up of 6 ± 3 years, ApHCM was characterized by lower all-cause, cardiovascular, heart failure-related mortality, and ventricular arrhythmic events compared with non-ApHCM. Multivariate analysis identified atrial fibrillation and HCM risk-sudden cardiac death (SCD) as independent predictors of the composite outcome of overall mortality and hospitalizations for cardiovascular reasons (hazard ratio [HR] 4.3, 95% confidence interval [CI] 1.9-9.5 for atrial fibrillation and HR 1.2, 95% CI 1.02-1.3 for HCM risk-SCD) in ApHCM. ConclusionsApHCM exhibited a lower rate of all-cause mortality and arrhythmic events in the middle-aged population of patients with HCM. Atrial fibrillation and HCM risk-sudden cardiac death were independent predictors of a composite of overall mortality and cardiovascular hospitalizations among those with ApHCM.

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.

Prognosis of patients with hypertrophic cardiomyopathy and low-normal left ventricular ejection fraction

ObjectiveTo investigate whether low-normal left ventricular ejection fraction (LVEF) is associated with adverse outcomes in hypertrophic cardiomyopathy (HCM) and evaluate the incremental value of predictive power of LVEF in the...

104 EFFECTIVENESS OF 2014 ESC HCM RISK-SCD SCORE IN PREDICTION OF APPROPRIATE ICD SHOCK

Abstract Background Since 2014, European Guidelines have recommended using a novel clinical risk prediction model, called the HCM Risk-SCD, to identify which patients with hypertrophic cardiomyopathy (HCM) who are at higher risk for sudden cardiac death (SCD) and would benefit most from having a prophylactic cardioverter defibrillator (ICD) implantable. In recent years, evidence has called into question the effectiveness of this model in patient selection. Material and Methods Data from consecutive patients with HCM and ICD who were followed at our Cardiology Department from January 2000 to January 2022 were retrospectively collected. Results Among 702 HCM patients, 52 (7%) received an ICD (female, 31%; mean age at implantation, 49 ± 20; S-ICD, 13%; single-chamber ICD, 50%). Of them, 7 (13%) patients were implanted for secondary prevention while 45 (87%) for primary prevention. Out of the 45 primary prevention patients, 7 (16%) experienced 8 appropriate shocks (AS) while 10 (22%) had 15 inappropriate shocks (IS), during a mean follow up of 8 ± 5 years. Overall, mean HCM Risk-SCD score was 6.8 ± 4.7. Patients with AS showed a non-significant higher risk score when compared to non-AS subjects (7.1 ± 5.4 vs 4.8 ± 5.1, p=0.27). By stratifying study population according to pre-established and clinically adopted HCM Risk-SCD score cut-off (such as &amp;lt; 4 vs. &amp;gt; or = 4), we failed to highlight any significant difference in term of AS between groups. Indeed, out of 10 (22%) patients with HCM Risk-SCD score &amp;lt; 4, 3 (7%) experienced AS, while among 35 (78%) patients with HCM Risk-SCD score &amp;gt; or = 4, 4 (9%) had AS (30% vs. 11%, p=0.17). Conclusions The HCM Risk-SCD score does not seem to be able to predict the occurrence of life-threatening ventricular arrhythmias and AS in HCM patients. Our data highlight the need to elaborate a new score in order to improve SCD risk stratification and better select patients for ICD implantation.