Several methods for estimating stroke volume (SV) were tested in conscious, freely moving rats in which ascending aortic pressure and cardiac flow were simultaneously (beat-to-beat) recorded. We compared two pulse-contour models to two new statistical models including eight parameters extracted from the pressure waveform in a multiple linear regression. Global as well as individual statistical models gave higher correlation coefficients between estimated and measured SV ( model 1, r = 0.97; model 2, r= 0.96) than pulse-contour models ( model 1, r = 0.83; model 2, r = 0.91). The latter models as well as statistical model 1 used the pulsatile systolic area and thus could be applied to only 47 ± 17% of the cardiac beats. In contrast, statistical model 2 used the pressure-increase characteristics and was therefore established for all of the cardiac beats. The global statistical model 2 applied to data sets independent of those used to establish the model gave reliable SV estimates: r= 0.54 ± 0.07, a small bias between −8% to +10%, and a mean precision of 7%. This work demonstrated the limits of pulse-contour models to estimate SV in conscious, unrestrained rats. A multivariate statistical model using eight parameters easily extracted from the aortic waveform could be applied to all cardiac beats with good precision.
Uncalibrated Real-Time Stroke Volume Estimation in MRI Using the Magnetohydrodynamic Effect ?
