Pathology of the pacemaker network

Ectopic cycle length estimation from the quantified distribution patterns of ventricular bigeminy and trigeminy

Background

Ectopic cycle length (ECL) and the distribution patterns of ventricular bigeminy and trigeminy, expressed as their postextrasystolic intervals (PEIs) and interectopic intervals (IEIs), have been poorly pursued.

Objective

Based on modulation theory, we hypothesized that the PEIs of bigeminy and trigeminy determine their IEIs and ECL.

Methods

Ambulatory electrocardiograms of 1290 patients with ventricular premature complexes (≥3000/day) were studied. To quantify their distribution pattern on the PEI vs IEI curve (PIC), we introduced the following 2 ratios: PEI of trigeminy to PEI of bigeminy ratio (T/B-PEI) and IEI of trigeminy to IEI of bigeminy ratio (T/B-IEI). Distribution patterns were divided into 3 types by T/B-PEI: standard type (<0.90), intermediate type (between 0.90 and 1.20), and reverse type (>1.20). ECL was defined as the average of the bigeminy and trigeminy intervals in the standard type, and bigeminy intervals in the other 2 types.

Results

T/B-IEI disclosed significant linear relationship with T/B-PEI (P < .0001). ECLs were longest in the standard type (1905 ± 347 ms; n = 426), followed by the intermediate type (1520 ± 239 ms; n = 607) and reverse type (1317 ± 227 ms; n = 227) (P < .0001). Trigeminy PEI/ECL in the standard type (0.450 ± 0.074) was significantly shorter than that of the other 2 types (P < .0001).

Conclusion

We confirmed that T/B-PEI determines T/B-IEI and ECL by discriminating the 3 distribution patterns. Among them, trigeminy PEI/ECL decided the 2 types of modulation by the first sinus QRS, starting at the early delay phase or the later acceleration phase.

Analysis of heterogeneous cardiac pacemaker tissue models and traveling wave dynamics

The sinoatrial-node (SAN) is a complex heterogeneous tissue that generates a stable rhythm in healthy hearts, yet a general mechanistic explanation for when and how this tissue remains stable is lacking. Although computational and theoretical analyses could elucidate these phenomena, such methods have rarely been used in realistic (large-dimensional) gap-junction coupled heterogeneous pacemaker tissue models. In this study, we adapt a recent model of pacemaker cells (Severi et al., 2012), incorporating biophysical representations of ion channel and intracellular calcium dynamics, to capture physiological features of a heterogeneous population of pacemaker cells, in particular "center" and "peripheral" cells with distinct intrinsic frequencies and action potential morphology. Large-scale simulations of the SAN tissue, represented by a heterogeneous tissue structure of pacemaker cells, exhibit a rich repertoire of behaviors, including complete synchrony, traveling waves of activity originating from periphery to center, and transient traveling waves originating from the center. We use phase reduction methods that do not require fully simulating the large-scale model to capture these observations. Moreover, the phase reduced models accurately predict key properties of the tissue electrical dynamics, including wave frequencies when synchronization occurs, and wave propagation direction in a variety of tissue models. With the reduced phase models, we analyze the relationship between cell distributions and coupling strengths and the resulting transient dynamics. Further, the reduced phase model predicts parameter regimes of irregular electrical dynamics. Thus, we demonstrate that phase reduced oscillator models applied to realistic pacemaker tissue is a useful tool for investigating the spatial-temporal dynamics of cardiac pacemaker activity.

Strong modulation of ectopic focus as a mechanism of repetitive interpolated ventricular bigeminy with heart rate doubling

BACKGROUND

Repetitive interpolated ventricular bigeminy (RIVB) can introduce a doubling of the ventricular rate.

OBJECTIVE

To clarify the mechanism of RIVB, we hypothesized that it was introduced by a strong modulation of the ventricular automatic focus.

METHODS

RIVB, defined as more than 7 bigeminy events, was detected by instantaneous heart rate and bigeminy interval (BI) tachograms in 1450 successive patients with frequent ventricular premature contractions (≥3000 per day). Postextrasystolic interval bigeminy interval curves were plotted to determine the degree of modulation. Mean sinus cycle length bigeminy interval curves were plotted for selection. RIVB was simulated by using a computer-based parasystole model.

RESULTS

RIVB was observed in 7 patients (age 60 ± 16 years; 2 men and 5 women) with a heart rate of 58.2 ± 6.5 beats/min during a rest period both during the day and at night. The tachograms disclosed the onset of the RIVB with a doubled ventricular rate to 112.3 ± 8.5 beats/min. On the postextrasystolic interval bigeminy interval curves, compensatory bigeminy and interpolated bigeminy constituted overlapping regression lines with slopes close to 1.00 and RIVB was located in the lower left portion. RIVB lasting for up to 3 hours was quickly detected by mean sinus cycle length bigeminy interval curve. The PQ interval immediately after RIVB was prolonged in comparison with baseline (0.18 ± 0.02 to 0.21 ± 0.02 seconds; P < .001). The simulation was able to reproduce RIVB faithfully at a slow heart rate.

CONCLUSIONS

Our findings support the hypothesis that RIVB was introduced by strongly modulated ventricular pacemaker accelerated by an intervening normal QRS.