Congenital and childhood atrioventricular blocks: pathophysiology and contemporary management

Atrioventricular block is classified as congeni- tal if diagnosed in utero, at birth, or within the first month of life. The pathophysiological process is believed to be due to immune-mediated injury of the conduction system, which occurs as a result of transplacental pas- sage of maternal anti-SSA/Ro-SSB/La antibodies. Childhood atrioventricular block is therefore diagnosed between the first month and the 18th year of life. Genetic variants in multiple genes have been described to date in the pathogenesis of inherited progressive car- diac conduction disorders. Indications and techniques of cardiac pacing have also evolved to allow safe perma- nent cardiac pacing in almost all patients, including those with structural heart abnormalities

Unexpected Course of Nonlinear Cardiac Interbeat Interval Dynamics during Childhood and Adolescence

The fluctuations of the cardiac interbeat series contain rich information because they reflect variations of other functions on different time scales (e.g., respiration or blood pressure control). Nonlinear measures such as complexity and fractal scaling properties derived from 24 h heart rate dynamics of healthy subjects vary from childhood to old age. In this study, the age-related variations during childhood and adolescence were addressed. In particular, the cardiac interbeat interval series was quantified with respect to complexity and fractal scaling properties. The R-R interval series of 409 healthy children and adolescents (age range: 1 to 22 years, 220 females) was analyzed with respect to complexity (Approximate Entropy, ApEn) and fractal scaling properties on three time scales: long-term (slope β of the power spectrum, log power vs. log frequency, in the frequency range 10−4 to 10−2 Hz) intermediate-term (DFA, detrended fluctuation analysis, α2) and short-term (DFA α1). Unexpectedly, during age 7 to 13 years β and ApEn were higher compared to the age <7 years and age >13 years (β: −1.06 vs. −1.21; ApEn: 0.88 vs. 0.74). Hence, the heart rate dynamics were closer to a 1/f power law and most complex between 7 and 13 years. However, DFA α1 and α2 increased with progressing age similar to measures reflecting linear properties. In conclusion, the course of long-term fractal scaling properties and complexity of heart rate dynamics during childhood and adolescence indicates that these measures reflect complex changes possibly linked to hormonal changes during pre-puberty and puberty

Failure of epicardial pacing leads in congenital heart disease: not uncommon and difficult to predict

AIMS: We evaluate the incidence of epicardial lead failure and try to identify risk factors in patients with congenital heart disease. METHODS: All patients with a congenital heart defect and an epicardial pacing system, implanted within a timeframe of 25 years, were included in this study. Patients' medical records and lead data were reviewed. Lead failure was defined as the primary endpoint. RESULTS: In total 198 active epicardial leads (atrial 40, ventricular 158) were implanted in 93 patients (median age at implantation 4.4 years (range 0-58.6)). During a total follow-up of 1235 lead-years, 29 lead failures (14.6%, 4 atrial, 25 ventricular) were documented in 22 patients (23.7%). Lead failure occurred at a median time period of 4.8 years (range 1.2-24.1) after implantation. Five-year freedom of lead failure was 88%. The only independent predictor for lead failure was the age at implantation (HR 0.44; 95%CI 0.20-0.97, p = 0.04), other characteristics failed to predict lead failure. Sudden cardiac death occurred in four patients (4.3%), in one a lead failure was documented. CONCLUSION: A high incidence of epicardial lead failures is found in patients with congenital heart disease. Unfortunately, it is difficult to predict this potentially life-threatening complication.status: publishe

Atrial threshold variability: implications for automatic atrial stimulation algorithms.

Automatic management of atrial stimulation by verification of atrial threshold (ACM) has recently been made feasible. We investigated circadian atrial threshold variability over the long term and the predictors of successful automatic atrial threshold measurement, in order to provide practical clues for programming ACM features, in such a way as to achieve daily threshold verification and > 99% effective atrial stimulation