Prospects for remodeling the hypertrophic heart with myosin modulators

Family screening for hypertrophic cardiomyopathy: Initial cardiologic assessment, and long-term follow-up of genotype-positive phenotype-negative individuals

AIMS

(i) Investigate the prevalence of hypertrophic cardiomyopathy (HCM) in individuals with pathogenic/likely pathogenic (P/LP) gene variants detected through family cascade testing in relatives, and (ii) evaluate phenotypic progression in genotype-positive phenotype-negative (G+/P-) individuals during follow-up.

RESULTS

From 2000 to 2023, 273 individuals underwent cardiologic evaluation following P/LP variant detection through family screening. Upon initial evaluation, HCM was diagnosed in 128 (47 %) individuals. Comparing with 145 G+/P- individuals, HCM patients were older (48 vs 38 years, p < 0.001) and more likely male (57 % vs 34 %, p < 0.001). During follow-up (median 11 years), 14 (11 %) of the HCM patients died (two from sudden cardiac death), four (3 %) underwent myectomy, 15 (12 %) developed atrial fibrillation and 17 (13 %) required implantable cardioverter-defibrillator implantation (15 primary prevention, 88 %). HCM-related adverse outcomes correlated with younger diagnosis age. During follow-up (median 8 years) of 118 (out of 145) G+/P- subjects with at least one year of follow-up, seven (6 %) individuals (71 % female, diagnosed age 39-77, after median follow-up 6 years) developed HCM (mean maximal wall thickness increasing from 10.2 mm to 13.3 mm). In this G+/P- cohort, significant echocardiographic changes from baseline to last visit were negligible. Over half (56 %) had <1 mm change of maximal wall thickness. No adverse cardiac outcomes occurred.

CONCLUSION

The initial evaluation was high-yield, with HCM being diagnosed in 47 % of G+ individuals, more frequently in older males. Over a median 8-year follow-up, 6 % of G+/P- individuals developed mild HCM, with no adverse cardiac outcomes. These data support initial screening in all first degree relatives, but (very) low-frequency cardiologic evaluations for G+/P- individuals thereafter.

Detection of late gadolinium enhancement in patients with hypertrophic cardiomyopathy using machine learning

BACKGROUND

Late gadolinium enhancement (LGE) on cardiac magnetic resonance (CMR) in hypertrophic cardiomyopathy (HCM) typically represents myocardial fibrosis and may lead to fatal ventricular arrhythmias. However, CMR is resource-intensive and sometimes contraindicated. Thus, in patients with HCM, we aimed to detect LGE on CMR by applying machine learning (ML) algorithm to clinical parameters.

METHODS AND RESULTS

In this trans-Pacific multicenter study of HCM, a ML model was developed to distinguish the presence or absence of LGE on CMR by ridge classification method using 22 clinical parameters including 9 echocardiographic data. Among 742 patients in this cohort, the ML model was constructed in 2 institutions in the United States (training set, n = 554) and tested using data from an institution in Japan (test set, n = 188). LGE was detected in 299 patients (54%) in the training set and 76 patients (40%) in the test set. In the test set, the area under the receiver-operating-characteristic curve (AUC) of the ML model derived from the training set was 0.77 (95% confidence interval [CI] 0.70-0.84). When compared with a reference model constructed with 3 conventional risk factors for LGE on CMR (AUC 0.69 [95% CI 0.61-0.77]), the ML model outperformed the reference model (DeLong's test P = 0.01).

CONCLUSIONS

This trans-Pacific study demonstrates that ML analysis of clinical parameters can distinguish the presence of LGE on CMR in patients with HCM. Our ML model would help physicians identify patients with HCM in whom the pre-test probability of LGE is high, and therefore CMR will have higher utility.

Prediction of cardiac death in patients with hypertrophic cardiomyopathy using plasma adipokine levels

BACKGROUNDS AND AIMS

Hypertrophic cardiomyopathy (HCM) causes cardiac death through both sudden cardiac death (SCD) and death due to heart failure (HF). Although adipokines lead to adverse cardiac remodeling in HCM, the prognostic value of plasma adipokines in HCM remains unknown. We aimed to predict cardiac death in patients with HCM using plasma adipokines.

METHODS AND RESULTS

We performed a multicenter prospective cohort study of patients with HCM. The outcome was cardiac death including heart transplant, death due to HF, and SCD. With data from 1 institution (training set), a prediction model was developed using random forest classification algorithm based on 10 plasma adipokines. The performance of the prediction model adjusted for 8 clinical parameters was examined in samples from another institution (test set). Time-to-event analysis was performed in the test set to compare the rate of outcome events between the low-risk and high-risk groups determined by the prediction model. In total, 389 (267 in the training set; 122 in the test set) patients with HCM were included. During the median follow-up of 2.7 years, 21 patients experienced the outcome event. The area under the covariates-adjusted receiver-operating characteristics curve was 0.89 (95 % confidence interval [CI] 0.71-0.99) in the test set. revealed the high-risk group had a significantly higher risk of cardiac death (hazard ratio 17.8, 95 % CI 2.1-148.3, P = 0.008).

CONCLUSION

The present multicenter prospective study demonstrated that a panel of plasma adipokines predicts cardiac death in patients with HCM.

Design and Analysis of a Polymeric Left Ventricular Simulator via Computational Modelling

Preclinical testing of medical devices is an essential step in the product life cycle, whereas testing of cardiovascular implants requires specialised testbeds or numerical simulations using computer software Ansys 2016. Existing test setups used to evaluate physiological scenarios and test cardiac implants such as mock circulatory systems or isolated beating heart platforms are driven by sophisticated hardware which comes at a high cost or raises ethical concerns. On the other hand, computational methods used to simulate blood flow in the cardiovascular system may be simplified or computationally expensive. Therefore, there is a need for low-cost, relatively simple and efficient test beds that can provide realistic conditions to simulate physiological scenarios and evaluate cardiovascular devices. In this study, the concept design of a novel left ventricular simulator made of latex rubber and actuated by pneumatic artificial muscles is presented. The designed left ventricular simulator is geometrically similar to a native left ventricle, whereas the basal diameter and long axis length are within an anatomical range. Finite element simulations evaluating left ventricular twisting and shortening predicted that the designed left ventricular simulator rotates approximately 17 degrees at the apex and the long axis shortens around 11 mm. Experimental results showed that the twist angle is 18 degrees and the left ventricular simulator shortens 5 mm. Twist angles and long axis shortening as in a native left ventricle show it is capable of functioning like a native left ventricle and simulating a variety of scenarios, and therefore has the potential to be used as a test platform.