Heart rate variability effects of an agonist or antagonists of the β-adrenoceptor assessed with scatterplot and sequence analysis

Abstract

There is evidence that the processes regulating heart rate variations reflect non-linear complexity and show 'chaotic' determinism. Data analyses using non-linear methods may therefore reveal patterns not apparent with conventional statistical approaches. We have consequently investigated two non-linear methods, the Poincaré plot (scatterplot) and cardiac sequence (quadrant) analysis, and compared these with standard time-domain summary statistics, during a normal volunteer investigation of an agonist and antagonists of the cardiac beta-adrenoceptor. Under double-blind and randomized conditions (Latin square design), 12 normal volunteers received placebo, celiprolol (beta 1- and beta 2-adrenoceptor partial agonist), propranolol (beta 1- and beta 2-adrenoceptor antagonist), atenolol (beta 1-adrenoceptor antagonist) and combinations of these agents. Single oral doses of medication (at weekly intervals) were administered at 22:30 hours with sleeping heart rates recorded overnight. The long (SDNN, SDANN) and short-term (rmsSD) time-domain summary statistics were reduced by celiprolol--effects different from the unchanged or small increases after atenolol and propranolol alone. The Poincaré plot was constructed by plotting each RR interval against the preceding RR interval, but unlike previous descriptions of the method, an automated computer method, with a high level of reproducibility, was employed. Scatterplot length and area were reduced following celiprolol and different from the small increases after propranolol and atenolol. The geometric analysis of the scatterplots allowed width assessment (i.e. dispersion) at fixed RR intervals. Differences between the drugs were confined to the higher percentiles (i.e. 75% and 90% of scatterplot length: low heart rate). The long-term time-domain statistics (SDNN, SDANN) correlated best with scatterplot length and area whereas the short-term heart rate variability (HRV) indices (rmsSD), pNN50) correlated strongly with scatterplot width. Cardiac sequence analysis (differences between three adjacent beats; delta RR vs delta RRn+1) assessed the short-term patterns of cardiac acceleration and deceleration, four patterns are identified: +/+ (a lengthening sequencing), +/- or -/+ (balanced sequences), and finally -/- (a shortening sequence). A running count of events by quadrant, together with the average magnitude of the differences was computed. The beta-adrenoceptor partial agonist celiprolol increased acceleration sequences. The duration of beat-to-beat difference shortened after celiprolol; this contrasted with increased duration of beat-to-beat difference after propranolol and atenolol. These results demonstrated a shift towards sympathetic dominance after the beta-adrenoceptor partial agonist celiprolol contrasting in parasympathetic dominance after the beta-adrenoceptor antagonists propranolol and atenolol. These non-linear methods appear to be valuable tools to investigate HRV in health and in cardiovascular disease and to study the implications of alterations in autonomi...

Autoantibodies to theβ1-Adrenoceptor from Patients with Periodontitis as a Risk Factor for Cardiac Dysfunction

“…The 20 patients with periodontitis and 20 normal subjects were studied according to a previous report [25]. Heart rate was recorded using an Oxford Medilog 2–24 miniature analog tape recorder (Oxford Instruments Medical Systems, Abingdon, UK).…”

“…The summary time-domain statistical measures of HRV calculated included the HRV long-term standard deviation of all NN (SDNN) indices. These indices represent variability over heart cycles and estimate high-frequency variation in the heart rate [25]. …”

“…The partial agonistic activity of autoantibodies observed in vitro mimics the action on HRV of the partial β 1 -adrenergic agonist celiprolol described in vivo . However, the combination of celiprolol with atenolol did not prevent the fall in HRV triggered by the partial agonist [25]. Hence, the antibody-mediated partial β 1 agonistic activity could be responsible for the decrease in HRV in patients with periodontitis.…”

The Concept of Nonlinearity in Complex Systems

“…Although the initial focus was on cardiovascular dynamics [9,[12][13][14][15][16][17][18][19][20][21][22], it soon became clear that the mathematical models they were adapting had more general applications [1, 3, 4, 6, 8-10, 12, 18, 19, 23-31]. Nevertheless, up to now the potential importance of nonlinear dynamics for the understanding of reactions in trauma and shock has not been described.…”

Poincare plots and symbolic dynamics patterns of left ventricular function parameters extracted from echocardiographic acoustic quantification

“…Differently from the previous application for long-term analysis of RR series [9,10], we propose also to quantify these clouds of points by the distance of their center of mass (Bx) from the origin, which represent the amount of variation of the predominant pattern (figure 3). Regarding the VV variability series, similar values of HVE § in SV were observed in both populations, while significant differences were found in peak filling (PF) and peak ejection (PE), with a reduction in NO: In peak atrial (PA) an increasing trend, hence not significant, was observed in NO.…”