Sick sinus syndrome and atrial fibrillation in older persons - A view from the sinoatrial nodal myocyte

Sick sinus syndrome remains a highly relevant clinical entity, being responsible for the implantation of the majority of electronic pacemakers worldwide. It is an infinitely more complex disease than it was believed when first described in the mid part of the 20th century. It not only involves the innate leading pacemaker region of the heart, the sinoatrial node, but also the atrial myocardium, predisposing to atrial tachydysrhythmias. It remains controversial as to whether the dysfunction of the sinoatrial node directly causes the dysfunction of the atrial myocardium, or vice versa, or indeed whether these two aspects of the condition arise through some related underlying pathological mechanism, such as extracellular matrix remodeling, i.e., fibrosis. This review aims to shed new light on the myriad possible contributing factors in the development of sick sinus syndrome, with a particular focus on the sinoatrial nodal myocyte. This article is part of a Special Issue entitled CV Aging.

Macitentan treatment retards the progression of established pulmonary arterial hypertension in an animal model

BACKGROUND

Macitentan is a new endothelin receptor antagonist that is used to treat pulmonary arterial hypertension in humans. Treatment of established pulmonary hypertension with macitentan was studied using the monocrotaline model of pulmonary hypertension.

METHODS

Three groups of rats were created (n=12): control (CON: macitentan only), monocrotaline (MCT: monocrotaline only) and macitentan (MACI: macitentan and monocrotaline). Monocrotaline (60 mg/kg) was injected in the MCT and MACI groups on day 0; volume matched saline was injected in the CON groups. Macitentan therapy (30 mg/kg/day) was commenced on day 11 in the CON and MACI groups. Serial echocardiography and ECGs were performed. The rats were sacrificed if they showed clinical deterioration.

RESULTS

The MCT and MACI rats showed signs of pulmonary hypertension by day 7 (maximum pulmonary velocity, CON 1.15 ± 0.15m/s vs MCT 1.04 ± 0.10 m/s vs MACI 0.99 ± 0.18 m/s; p<0.05). Both the MCT and MACI groups developed pulmonary hypertension, but this was less severe in the MACI group (day 21 pulmonary artery acceleration time, MCT 17.55 ± 1.56 ms vs MACI 22.55 ± 1.00 ms; pulmonary artery deceleration, MCT 34.72 ± 3.72 m/s(2) vs MACI 17.30 ± 1.89 m/s(2); p<0.05). Right ventricular hypertrophy and QT interval increases were more pronounced in MCT than MACI (right ventricle wall thickness, MCT 0.13 ± 0.1cm vs MACI 0.10 ± 0.1cm; QT interval, MCT 85 ± 13 ms vs MACI 71 ± 14 ms; p<0.05). Survival benefit was not seen in the MACI group (p=0.50).

CONCLUSIONS

Macitentan treatment improves haemodynamic parameters in established pulmonary hypertension. Further research is required to see if earlier introduction of macitentan has greater effects.

Stochastic vagal modulation of cardiac pacemaking may lead to erroneous identification of cardiac "chaos"

Fluctuations in the time interval between two consecutive R-waves of electrocardiogram during normal sinus rhythm may result from irregularities in the autonomic drive of the pacemaking sinoatrial node (SAN). We use a biophysically detailed mathematical model of the action potentials of rabbit SAN to quantify the effects of fluctuations in acetylcholine (ACh) on the pacemaker activity of the SAN and its variability. Fluctuations in ACh concentration model the effect of stochastic activity in the vagal parasympathetic fibers that innervate the SAN and produce varying rates of depolarization during the pacemaker potential, leading to fluctuations in cycle length (CL). Both the estimated maximal Lyapunov exponent and the noise limit of the resultant sequence of fluctuating CLs suggest chaotic dynamics. Apparently chaotic heart rate variability (HRV) seen in sinus rhythm can be produced by stochastic modulation of the SAN. The identification of HRV data as chaotic by use of time series measures such as a positive maximal Lyapunov exponent or positive noise limit requires both caution and a quantitative, predictive mechanistic model that is fully deterministic.