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Am J Physiol Heart Circ Physiol 292: H1193-H1203, 2007. First published September 29, 2006; doi:10.1152/ajpheart.00645.2006
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INNOVATIVE METHODOLOGY

A simplified two-component model of blood pressure fluctuation

¹Autonomic Dysfunction Center, Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University School of Medicine, and ²Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee

Submitted 15 June 2006 ; accepted in final form 22 September 2006

We propose a simple moving-average (MA) model that uses the low-frequency (LF) component of the peroneal muscle sympathetic nerve spike rate (LF_{spike rate}) and the high-frequency (HF) component of respiration (HF_Resp) to describe the LF neurovascular fluctuations and the HF mechanical oscillations in systolic blood pressure (SBP), respectively. This method was validated by data from eight healthy subjects (23–47 yr old, 6 male, 2 female) during a graded tilt (15° increments every 5 min to a 60° angle). The LF component of SBP (LF_SBP) had a strong baroreflex-mediated feedback correlation with LF_{spike rate} (r = –0.69 ± 0.05) and also a strong feedforward relation to LF_{spike rate} [r = 0.58 ± 0.03 with LF_SBP delay () = 5.625 ± 0.15 s]. The HF components of spike rate (HF_{spike rate}) and SBP (HF_SBP) were not significantly correlated. Conversely, HF_Resp and HF_SBP were highly correlated (r = –0.79 ± 0.04), whereas LF_Resp and LF_SBP were significantly less correlated (r = 0.45 ± 0.08). The mean correlation coefficients between the measured and model-predicted LF_SBP (r = 0.74 ± 0.03) in the supine position did not change significantly during tilt. The mean correlation between the measured and model-predicted HF_SBP was 0.89 ± 0.02 in the supine position. R² values for the regression analysis of the model-predicted and measured LF and HF powers indicate that 78 and 91% of the variability in power can be explained by the linear relation of LF_{spike rate} to LF_SBP and HF_Resp to HF_SBP. We report a simple two-component model using neural sympathetic and mechanical respiratory inputs that can explain the majority of blood pressure fluctuation at rest and during orthostatic stress in healthy subjects.

wavelet transform; blood pressure variability; Mayer waves; respiration; muscle sympathetic nerve activity