Cardiomyopathy, Hypertrophic ; diagnosis ; therapy ; Humans

Cardiomyopathy, Hypertrophic ; diagnosis ; therapy ; Humans

Cardiomyopathy, Hypertrophic ; diagnosis ; therapy ; Consensus ; Humans

Cardiomyopathies ; classification ; diagnosis ; etiology ; Cardiomyopathy, Dilated ; diagnosis ; etiology ; Cardiomyopathy, Hypertrophic ; diagnosis ; etiology ; Child ; Humans ; Pediatrics ; Suggestion

An unusual form of hypertrophic cardiomyopathy localized to the left ventricular apex is called apical hypertrophic cardiomyopathy. In the classic form is characterized by giant T wave inversion in electrocardiogram and an angiographic silhouette showing enddiastolic deformation of the left ventricular cavity resembling a "spade". Apical hypertrophic cardiomyopathy appears functionally similar to other forms of nonobstructive hypertrophic cardiomyopathy. The diagnosis of apical hypertrophic cardiomypathy is made chiefly from the 12 lead electrocardiogram, two-dimensional echocardiography, left ventriculogram and magnetic resonance imaging. The prognosis appears relatively favorable course. We report a case of regressed apical hypertrophic cardiomyopathy which was diagnosed by two-dimensional echocardiography and 12 lead electrocardiogram, with related literatures.
Cardiomyopathy, Hypertrophic ; Diagnosis ; Echocardiography ; Electrocardiography ; Magnetic Resonance Imaging ; Prognosis

BACKGROUND: Although idiopathic cardiomyopathies(i-CMP) are very important in all age groups, the epidemiology of i-CMP in children has not been well defined. A retrospective study in Korean children was performed in 1998 to obtain basic data on i-CMP. MATERIAL AND METHOD: The medical records of all patients aged birth to 15 years from the hospitals where pediatric cardiologists worked were reviewed to obtain information on i-CMP. Pediatric cardiologists from a total of 22 hospitals were participated in reviewing the medical records of their patients and filling up the protocol. The data were pooled to the study committee and reviewed. RESULTS: Of the 278 cases with i-CMP, there were dilated cardiomyopathy (d-CMP) in 182 (65.4%): hypertrophic cardiomyopathy (h-CMP) in 74 (26.6%): restrictive cardiomyopathy (r-CMP) and unclassified in 17 (6.1%) and 5 (1.9%) each. The average annual occurrence of new cases as a whole was 2.65 per 100,000 (95% CI: 1.5-3.7): d-CMP, 1.73/100,000/year (95% CI: 0.73-2.73): h-CMP, 0.71/100,000/year (95% CI: 0.35-1.07): r-CMP, 0.16/100,000/year (95% CI: 0.02-0.3). The median age at the time of diagnosis was 11 months in d-CMP: 3.0 years in h-CMP: 6.9 years in r-CMP. The survival rate in d-CMP was 76% at 1 year, 72.5% at 2 year, 70% at 5 year. There was no difference in survival rate according to age (in d-CMP, between children less than 2 years of age and over 2 years of age (74% vs. 79% at 1 year: 67% vs. 76% at 5 year, p=NS): in h-CMP, between children less than 1 year of age and over 1 year of age (84% vs. 96% at 1 year: 63% vs. 81% at 5 year, p=NS)). R-CMP showed the worst survival rate (72% at 1 year, 30.2% at 5 year). CONCLUSION: In spite of the inherent defects of retrospective analysis, this study provides the useful epidemiological data in children with i-CMP. However, more systemic approach is needed to define the nature of the i-CMP in children.
Cardiomyopathies* ; Cardiomyopathy, Dilated ; Cardiomyopathy, Hypertrophic ; Cardiomyopathy, Restrictive ; Child* ; Diagnosis ; Epidemiology ; Humans ; Medical Records ; Parturition ; Retrospective Studies ; Survival Rate

About half of all cases of hypertrophic cardiomyopathy(HCMP) have a positive family history. All first-degree relatives of patients with HCMP should be screened with echocardiography. The prenatal diagnosis of abnormal septal hypertrophy in fetuses of mothers with HCMP has not yet been documented. We report a prenatal diagnosis in a case of familial HCMP by ultrasonography which was confirmed by autopsy. Fetal echocardiography provides a valuable aid in diagnosis of familial HCMP.
Autopsy ; Cardiomyopathy, Hypertrophic, Familial* ; Diagnosis ; Echocardiography ; Fetus ; Humans ; Hypertrophy ; Mothers ; Prenatal Diagnosis* ; Ultrasonography ; Ultrasonography, Prenatal*

Aged ; Cardiomyopathy, Hypertrophic ; diagnosis ; Diagnostic Errors ; Female ; Humans ; Hypertrophy, Left Ventricular ; complications ; diagnosis

The case is a 54-year-old man with hypertrophic cardiomyopathy, mid-ventricular obstruction, apical aneurysm, and recurrence sustained monomorphic ventricular tachycardia (VT). A coronary angiogram revealed myocardial bridging located in the middle of the left anterior descending coronary artery (LAD), and the left ventriculogram showed an hour-glass appearance of the left ventricular cavity. There was a significant pressure gradient of 60 mmHg across the mid-ventricular obliteration at rest. A successful myectomy of the inappropriate hypertrophy myocardium and excision of the apical aneurysm were performed. Pathologic analysis demonstrated fibrosis in the apical aneurysm and thickened and narrowed vessels in the adjacent area. During the follow-up of eighteen months, the patient remained clinically stable and free from arrhythmic recurrence.
Cardiomyopathy, Hypertrophic ; diagnosis ; physiopathology ; Female ; Heart Aneurysm ; physiopathology ; Humans ; Male ; Middle Aged ; Tachycardia, Ventricular ; physiopathology

The diagnosis of hypertrophic cardiomyopathy (HCM) is of great significance for the early risk classification of sudden cardiac death and the screening of family genetic diseases. This research proposed a HCM automatic detection method based on convolution neural network (CNN) model, using single-lead electrocardiogram (ECG) signal as the research object. Firstly, the R-wave peak locations of single-lead ECG signal were determined, followed by the ECG signal segmentation and resample in units of heart beats, then a CNN model was built to automatically extract the deep features in the ECG signal and perform automatic classification and HCM detection. The experimental data is derived from 108 ECG records extracted from three public databases provided by PhysioNet, the database established in this research consists of 14,459 heartbeats, and each heartbeat contains 128 sampling points. The results revealed that the optimized CNN model could effectively detect HCM, the accuracy, sensitivity and specificity were 95.98%, 98.03% and 95.79% respectively. In this research, the deep learning method was introduced for the analysis of single-lead ECG of HCM patients, which could not only overcome the technical limitations of conventional detection methods based on multi-lead ECG, but also has important application value for assisting doctor in fast and convenient large-scale HCM preliminary screening.
Algorithms ; Cardiomyopathy, Hypertrophic/diagnosis* ; Databases, Factual ; Electrocardiography ; Heart Rate ; Humans ; Neural Networks, Computer