• B Silke and J G Riddell.
• University Department of Therapeutics and Pharmacology, Queen's University of Belfast, UK. b.silke@qub.ac.uk
• Clin. Auton. Res. 1998 Jun 1;8(3):145-53.

AbstractThere 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 autonomic control during therapeutic intervention.

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