Modelling of the dynamic relationship between arterial pressure, renal sympathetic nerve activity and renal blood
1Department of Electrical Engineering and Computer Systems, Monash University, Clayton, Baker Medical Research Institute, Prahran, Victoria, Australia.
Abstract:
A linear autoregressive/moving-average model was developed to describe the dynamic relationship between mean arterial pressure (MAP), renal sympathetic nerve activity (SNA) and renal blood flow (RBF) in conscious rabbits. The RBF and SNA to the same kidney were measured under resting conditions in a group of eight rabbits. Spectral analysis of the data sampled at 0.4 Hz showed that the low-pass bandwidth of the signal power for RBF was approximately 0. 05 Hz. An autoregressive/moving-average model with an exogenous input (ARMAX) was then derived (using the iterative Gauss-Newton algorithm provided by the MATLAB identification Toolbox), with MAP and SNA as inputs and RBF as output, to model the low-frequency fluctuations. The model step responses of RBF to changes in SNA and arterial pressure indicated an overdamped response with a settling time that was usually less than 2 s. Calculated residuals from the model indicated that 79 5 % (mean s.d., averaged over eight independent experiments) of the variation in RBF could be accounted for by the variations in arterial pressure and SNA. Two additional single-input models for each of the inputs were similarly obtained and showed conclusively that changes in RBF, in the conscious resting rabbit, are a function of both SNA and MAP and that the SNA signal has the predominant effect. These results indicate a strong reliance on SNA for the dynamic regulation of RBF. Such information is likely to be important in understanding the diminished renal function that occurs in a variety of disease conditions in which overactivity of the sympathetic nervous system occurs.
