Aug 2026· Journal of Clinical Medicine· Vol 15, pp. 6230· 0 citations· 27 references
Medicine
TL;DR
Substantial phenotypic heterogeneity across age and sex, coupled with the identification of key factors associated with LVOTO, highlights the need for sex- and age-specific diagnostic strategies and therapeutic planning in clinical practice.
Abstract
Background: Contemporary data on the clinical detection rate and profile of phenotypical hypertrophic cardiomyopathy (HCM) in major Chinese healthcare settings are limited. This multicenter study aimed to determine the detection rate and echocardiographic features of the HCM phenotype in a large Chinese cohort. Methods: This cross-sectional study analyzed echocardiography databases from nine medical centers across China, including adult patients examined during 2023. HCM phenotype was defined as end-diastolic wall thickness ≥15 mm in the left ventricle. Patients with moderate to severe aortic stenosis were excluded. Subcategories included phenotypes of obstructive HCM and apical hypertrophy. Results: Among 655,383 examinations, 2610 patients met the criteria of the HCM phenotype, yielding a detection rate of 0.40% (≈1 in 250). The mean age was 60.2 years with male predominance (70.3%). Asymmetric septal hypertrophy was present in 53.3% of patients. The most commonly involved site with maximal wall thickness was the interventricular septum (57.6%), followed by the apex (20.9%) and the basal septum (17.7%). The overall intra-left ventricular obstruction rate was 16.2%; left ventricular outflow tract obstruction (LVOTO) accounted for 12.1%. LVOTO patients had greater septal thickness, smaller left ventricular diastolic dimensions, and more mitral regurgitation. Female sex was associated with a significantly higher LVOTO rate than males (18.2% vs. 9.6%, p < 0.001). Pure apical hypertrophy was identified in 4.5% of patients, with an increasing detection rate in older age groups. Conclusions: This large-scale, multicenter study confirms a high clinical detection rate for the HCM phenotype (≈1 in 250) in major Chinese centers. Substantial phenotypic heterogeneity across age and sex, coupled with the identification of key factors associated with LVOTO, highlights the need for sex- and age-specific diagnostic strategies and therapeutic planning in clinical practice.
BACKGROUND
Indices reflecting the discordance between QRS complex voltages on ECG and left ventricular (LV) wall thickness or LV mass index on echocardiogram (echo) have enabled identification of cardiac amyloidosis (CA) among patients with hypertrophic hearts. However, this evidence comes from studies that have exclud...
Valentina Allegro, L. Pagura, A. Porcari et al.· Journal of the American Hear...· 0 citations
BACKGROUND
The impact of coexisting type 2 diabetes mellitus (T2DM) on the phenotype and prognosis of hypertrophic cardiomyopathy (HCM) remains insufficiently studied. We aimed to evaluate the structural, functional, and prognostic effects of T2DM in HCM using cardiac magnetic resonance (CMR).
METHODS
This retrospect...
Yu-Kun Cao, Yu-Min Li, Zhenglin Ming et al.· International Journal of Car...· 0 citations
Introduction. Hypertrophic cardiomyopathy (HCM) is characterized by clinical and genetic heterogeneity. Age of manifestation, clinical and anatomical phenotypes of HCM vary significantly. This study discusses genetic causes and reconstructive surgery results for patients with particular intracardiac phenotype - diffuse...
S. Dzemeshkevich, M. Balashova, M. Polyak et al.· medRxiv· 0 citations
Compared with TTNtv and genotype-negative DCM, HRAv is characterized by a distinct CMR tissue phenotype marked by more extensive myocardial injury and fibrosis, despite similar ventricular remodeling and systolic impairment, suggesting that CMR tissue characterization may help identify genotype-associated phenotypic di...
Zhi-Gang Zhang, Yang-Jie Li, Yuan-Wei Xu et al.· International Journal of Car...· 0 citations
Abstract Aims Hypertrophic cardiomyopathy (HCM) remains underdiagnosed due to limited access to expert imaging. We developed and validated a deep-learning (DL)-based echocardiographic model adaptable to point-of-care ultrasound (POCUS) for scalable HCM screening. Methods and results We retrospectively analysed 134 956...
N. Karra, Y. Klempfner, V. Copeland et al.· European Heart Journal - Dig...· 0 citations