Evolution of P-wave indices during long-term follow-up as markers of atrial substrate progression in arrhythmogenic right ventricular cardiomyopathy

Predictor of A4 amplitude using preprocedural electrocardiography in patients with leadless pacemakers

BACKGROUND

Based on historical studies of leadless pacemakers (LPs), high atrioventricular synchrony (AVS) with mechanical sensing-based VDD pacing is largely influenced by A4 amplitude. A limited study investigated the predictors of A4 amplitude using clinical and echocardiographic parameters.

OBJECTIVE

The purpose of this study was to investigate the predictors of A4 amplitude preoperatively to select patients who could benefit the most from AVS among patients with VDD LPs (Micra-AV, Medtronic).

METHODS

Data from patients who received Micra-AV implantations from November 2021 to August 2023 at Tottori University Hospital were analyzed. Twelve-lead electrocardiography and transthoracic echocardiography were performed before the Micra-AV implantations. To assess the electrical indices associated with the A4 signal, electrocardiographic morphologic P-wave parameters were analyzed, including P-wave duration, P-wave amplitude, maximum deflection index (MDI), and P-wave dispersion.

RESULTS

A total of 50 patients who underwent Micra-AV implantations (median age 84 years; 64% male) were included and divided into 2 groups based on the median value of A4 amplitude, the high-A4 group (A4 amplitude >2.5 m/s2; n = 26), and low-A4 group (A4 amplitude ≤2.5 m/s2; n = 24). There was a significant difference between the high-A4 and low-A4 groups with regard to left ventricular ejection fraction (P = .01), P-wave dispersion (P = .01), and MDI (P <.001). Multivariate logistic analysis revealed that lower MDI was an independent predictor of high A4-amplitude (odds ratio 0.78; 95% confidence interval 0.67-0.92; P = 0.003).

CONCLUSION

Preoperative electrocardiographic evaluations of P-wave morphology may be useful for predicting A4 amplitude. MDI was the only independent A4 amplitude predictor that seemed promising for selecting Micra-AV patients.

Reduced plakoglobin increases the risk of sodium current defects and atrial conduction abnormalities in response to androgenic anabolic steroid abuse

Androgenic anabolic steroids (AAS) are commonly abused by young men. Male sex and increased AAS levels are associated with earlier and more severe manifestation of common cardiac conditions, such as atrial fibrillation, and rare ones, such as arrhythmogenic right ventricular cardiomyopathy (ARVC). Clinical observations suggest a potential atrial involvement in ARVC. Arrhythmogenic right ventricular cardiomyopathy is caused by desmosomal gene defects, including reduced plakoglobin expression. Here, we analysed clinical records from 146 ARVC patients to identify that ARVC is more common in males than females. Patients with ARVC also had an increased incidence of atrial arrhythmias and P wave changes. To study desmosomal vulnerability and the effects of AAS on the atria, young adult male mice, heterozygously deficient for plakoglobin (Plako+/- ), and wild type (WT) littermates were chronically exposed to 5α-dihydrotestosterone (DHT) or placebo. The DHT increased atrial expression of pro-hypertrophic, fibrotic and inflammatory transcripts. In mice with reduced plakoglobin, DHT exaggerated P wave abnormalities, atrial conduction slowing, sodium current depletion, action potential amplitude reduction and the fall in action potential depolarization rate. Super-resolution microscopy revealed a decrease in NaV 1.5 membrane clustering in Plako+/- atrial cardiomyocytes after DHT exposure. In summary, AAS combined with plakoglobin deficiency cause pathological atrial electrical remodelling in young male hearts. Male sex is likely to increase the risk of atrial arrhythmia, particularly in those with desmosomal gene variants. This risk is likely to be exaggerated further by AAS use. KEY POINTS: Androgenic male sex hormones, such as testosterone, might increase the risk of atrial fibrillation in patients with arrhythmogenic right ventricular cardiomyopathy (ARVC), which is often caused by desmosomal gene defects (e.g. reduced plakoglobin expression). In this study, we observed a significantly higher proportion of males who had ARVC compared with females, and atrial arrhythmias and P wave changes represented a common observation in advanced ARVC stages. In mice with reduced plakoglobin expression, chronic administration of 5α-dihydrotestosterone led to P wave abnormalities, atrial conduction slowing, sodium current depletion and a decrease in membrane-localized NaV 1.5 clusters. 5α-Dihydrotestosterone, therefore, represents a stimulus aggravating the pro-arrhythmic phenotype in carriers of desmosomal mutations and can affect atrial electrical function.

Analysis of digitalized ECG signals based on artificial intelligence and spectral analysis methods specialized in ARVC

Arrhythmogenic right ventricular cardiomyopathy (ARVC) is an inherited heart muscle disease that appears between the second and forth decade of a patient's life, being responsible for 20% of sudden cardiac deaths before the age of 35. The effective and punctual diagnosis of this disease based on electrocardiograms (ECGs) could have a vital role in reducing premature cardiovascular mortality. In our analysis, we first outline the digitalization process of paper-based ECG signals enhanced by a spatial filter aiming to eliminate dark regions in the dataset's images that do not correspond to ECG waveform, producing undesirable noise. Next, we propose the utilization of a low-complexity convolutional neural network for the detection of an arrhythmogenic heart disease, that has not been studied through the usage of deep learning methodology to date, achieving high classification accuracy, namely 99.98% training and 98.6% testing accuracy, on a disease the major identification criterion of which are infinitesimal millivolt variations in the ECG's morphology, in contrast with other arrhythmogenic abnormalities. Finally, by performing spectral analysis we investigate significant differentiations in the field of frequencies between normal ECGs and ECGs corresponding to patients suffering from ARVC. In 16 out of the 18 frequencies where we encounter statistically significant differentiations, the normal ECGs are characterized by greater normalized amplitudes compared to the abnormal ones. The overall research carried out in this article highlights the importance of integrating mathematical methods into the examination and effective diagnosis of various diseases, aiming to a substantial contribution to their successful treatment.