Beat to beat variability in cardiovascular variables: noise or music?

Cardiovascular variables such as heart rate, arterial blood pressure, stroke volume and the shape of electrocardiographic complexes all fluctuate on a beat to beat basis. These fluctuations have traditionally been ignored or, at best, treated as noise to be averaged out. The variability in cardiovascular signals reflects the homeodynamic interplay between perturbations to cardiovascular function and the dynamic response of the cardiovascular regulatory systems. Modern signal processing techniques provide a means of analyzing beat to beat fluctuations in cardiovascular signals, so as to permit a quantitative, noninvasive or minimally invasive method of assessing closed loop hemodynamic regulation and cardiac electrical stability. This method promises to provide a new approach to the clinical diagnosis and management of alterations in cardiovascular regulation and stability.

System identification of closed-loop cardiovascular control: effects of posture and autonomic blockade.

We applied system identification to the analysis of fluctuations in heart rate (HR), arterial blood pressure (ABP), and instantaneous lung volume (ILV) to characterize quantitatively the physiological mechanisms responsible for the couplings between these variables. We characterized two autonomically mediated coupling mechanisms [the heart rate baroreflex (HR baroreflex) and respiratory sinus arrhythmia (ILV-HR)] and two mechanically mediated coupling mechanisms [the blood pressure wavelet generated with each cardiac contraction (circulatory mechanics) and the direct mechanical effects of respiration on blood pressure (ILV-->ABP)]. We evaluated the method in humans studied in the supine and standing postures under control conditions and under conditions of beta-sympathetic and parasympathetic pharmacological blockades. Combined beta-sympathetic and parasympathetic blockade abolished the autonomically mediated couplings while preserving the mechanically mediated coupling. Selective autonomic blockade and postural changes also altered the couplings in a manner consistent with known physiological mechanisms. System identification is an "inverse-modeling" technique that provides a means for creating a closed-loop model of cardiovascular regulation for an individual subject without altering the underlying physiological control mechanisms.

Power spectrum analysis of heart rate variability in human cardiac transplant recipients.

Beat-to-beat heart rate variability was studied by power spectral analysis in 17 orthotopic cardiac transplant patients. Heart rate power spectra were calculated from eighty-four 256-second recordings and compared with those taken from six normal subjects. The power spectra from the control subjects resolved into discrete peaks at 0.04-0.12 Hz and 0.2-0.3 Hz, whereas those of heart transplant recipients resembled broad-band noise without peaks. Log total power in the 0.02-1.0 Hz range was greater in the control subjects (0.982 +/- 0.084 [0.206], mean +/- SEM [SD]) than in the transplanted subjects (-0.766 +/- 0.059 [0.541]), (p less than 0.0001). Fifty-five electrocardiographic recordings from transplant patients were done within 48 hours of an endomyocardial biopsy. When the power spectra of those patients whose endomyocardial biopsies showed evidence of myocardial rejection were compared with those from patients who were found to be free of rejection, a significant difference was found in log total power (-0.602 +/- 0.090 [0.525] vs. -0.909 +/- 0.136 [0.577], p less than 0.02). We conclude that denervation of the heart significantly reduces heart rate variability and abolishes the discrete spectral peaks seen in untransplanted control subjects and that the development of allograft rejection may significantly increase heart rate variability.