Subclinical cardiac involvement present as electrocardiographic abnormalities in various neuromuscular diseases

Management of Cardiac Involvement in Becker Muscular Dystrophy: A Case Report

Becker muscular dystrophy (BMD) is an X-linked recessive neuromuscular disorder caused by a mutation in the dystrophin gene. Cardiac involvement is a frequent finding in BMD, and manifestations may vary from asymptomatic cardiac involvement to developing symptoms of heart failure and severe cardiomyopathy. We presented the case of a 32-year-old wheelchair-dependent BMD patient who came to our cardiology clinic with a two-month history of heart palpitations, rest and nocturnal dyspnea, fatigue, and generalized muscular weakness. Upon evaluation, a 24-hour Holter rhythm showed complex ventricular arrhythmia and 300 polymorphic ventricular extrasystoles with episodes of ventricular bigeminy, while echocardiography revealed a dilated left ventricle with severe systolic dysfunction (left ventricular ejection fraction (LVEF) 23%) and impaired global contractility. An implantable cardioverter defibrillator (ICD) was implanted, and guideline direct medical therapy (GDMT), sacubitril/valsartan, bisoprolol, furosemide, spironolactone, and dapagliflozin were initiated. The patient was discharged five days later, in an improved clinical condition, without dyspnea. A follow-up appointment two weeks after discharge was recommended in order to evaluate the patient's symptoms and the effectiveness of GDMT and a follow-up echocardiography at least three months after discharge to evaluate the heart's systolic and diastolic function.

Robust QRS detection based on simulated degenerate optical parametric oscillator-assisted neural network

Accurately detecting the depolarization QRS complex in the ventricles is a fundamental requirement for cardiovascular disease detection using electrocardiography (ECG). In contrast to traditional signal enhancement algorithms, emerging neural network approaches have shown promise for QRS detection because of their generalizability on complex data. However, the inevitable noise present during ECG recording leads to a decrease in the performance of neural networks. To enhance the robustness and performance of neural network-based QRS detectors, we propose a simulated degeneration unit (SDU)-assisted convolutional neural network (CNN). An SDU simulates the physical degeneration process of interfering optical pulses, which can effectively suppress in-band noise. Through comprehensive performance evaluations on three open-source databases, the SDU-enhanced CNN-based approach demonstrated better performance in detecting QRS complexes than other recently reported QRS detectors. Furthermore, real-world noise injection tests indicate that the optimal noise robustness boundary for the CNN equipped with SDU is 167-300% higher than that for the CNN without SDU.

A reliable evaluation approach for multichannel signal denoising algorithms based on a novel arterial pulse acquisition system

Background

Tactile sensors are utilized to measure multichannel pulse signals in pulse wave analysis (PWA). Owing to noise interferences, researchers have applied various denoising algorithms on multichannel pulse signals. To comprehensively assess these algorithms, numerous evaluation metrics have been proposed. However, these studies did not investigate the noise mechanisms in depth and lacked reference pulse signals, thus making the evaluations insufficiently objective.

Materials and methods

An applicable denoising evaluation approach for multichannel pulse signal algorithms based on an arterial pulse acquisition system is established by superimposing real-world multichannel noise to the reference signals. The system, comprising a SphygmoCor and a uniaxial noise acquisition device, allows us to acquire single-reference pulse signals as well as real-world multichannel noise.

Results

We assess eight popular denoising algorithms with three evaluation metrics, including amplitude relative error (ARE), mean square error (MSE) and increased percentage signal-noise ratio (SNR%). Our proposed approach provides accurate and objective evaluations of multichannel pulse signal denoising. Notably, classic algorithms for single-channel denoising are not recommended for multichannel denoising. Comparatively, RPCA-based algorithms can denoise pulse signals independently for each channel.

Conclusion

This study sets the stage for the establishment of accurate and objective pulse signal denoising evaluations and provides insights for data-driven clinical diagnoses in cardiovascular medicine.

Electrocardiographic Changes in Jordanian Patients With Becker Muscular Dystrophy

Background and aim Becker muscular dystrophy (BMD) is an X-linked disease caused by an in-frame mutation in the dystrophin gene, which is considered an allelic disorder to the most severe form of dystrophinopahies, Duchenne muscular dystrophy, which leads to skeletal and cardiac muscle involvement and results in dilated cardiomyopathy (DCM). The aim of this study is to present our ECG data and the significance of this data in the early detection of DCM in these patients. Methods This is a retrospective study. All patients known to the clinical Genetic Clinic and Queen Alia Heart Center in Jordan with a diagnosis of Becker muscular dystrophy from the year 2011-2022 are offered cardiac evaluation according to the guidelines, which included clinical assessment, electrocardiograph, and 2-D echocardiograph (echo) at the time of diagnosis and every five years thereafter once the initial assessment was normal. All the records were retrieved and analyzed. Results Fifty-three patients of all ages with genetically confirmed BMD were identified. Twelve had no record as they didn't attend any cardiac evaluation. Forty-one were under regular clinical follow-up. Two were excluded as they died, and another four had no recorded data in our center. Ultimately, 35 patients were included and studied. The mean age was 30.5 years ± 22.1, ranging from two to seventy-seven years of age. Twenty-seven (77%) had abnormal ECG. High voltage R wave in V2 and V1 was the most common finding, followed by repolarisation abnormalities and Q wave (43%, 17%, 13%, and 11% respectively). Incomplete right bundle branch block in 4% as well as R/S ratio >1.2. U wave abnormalities in 3% and sinus tachycardia were found in only one patient. Conclusion Cardiac surveillance for patients with Becker muscular dystrophy is mandatory after the age of 16. Q wave and repolarisation changes should be taken seriously as early signs of dilated cardiomyopathy, even if the echo is normal.