Affiliation:
1. From the Laboratory for Cardiovascular Research, Hebrew Rehabilitation Center for Aged Research and Training Institute; and Division on Aging, Harvard Medical School, Boston, Mass.
Abstract
Abstract
—Traditionally, arterial baroreflex control of vagal neural outflow is quantified by heart period responses to falling and/or rising arterial pressures (ms/mm Hg). However, it is arterial pressure–dependent stretch of barosensory vessels that determines afferent baroreceptor responses, which, in turn, generate appropriate efferent cardiac vagal outflow. Thus, mechanical transduction of pressure into barosensory vessel stretch and neural transduction of stretch into vagal outflow are key steps in baroreflex regulation that determine the conventional integrated input-output relation. We developed a novel technique for direct estimation of gain in both mechanical and neural components of integrated cardiac vagal baroreflex control. Concurrent, beat-by-beat measures of arterial pressures (Finapres), carotid diameters (B-mode ultrasonography), and R-R intervals (ECG lead II) were made during bolus vasoactive drug infusions (modified Oxford technique) in 16 healthy humans. The systolic carotid diameter/pressure relationship (
r
2
=0.79±0.008, mean±SEM) provided a gain estimate of dynamic mechanical transduction of pressure into a baroreflex stimulus. The R-R interval/systolic diameter relationship (
r
2
=0.77±0.009) provided a gain estimate of afferent-efferent neural transduction of baroreflex stimulus into a vagal response. Variance between repeated measures for both estimates was no different than that for standard gain (
P
>0.40). Moreover, in these subjects, the simple product of the 2 estimates almost equaled standard baroreflex gain (ms/mm Hg=0.98x+2.27;
r
2
=0.93,
P
=0.001). This technique provides reliable information on key baroreflex components not distinguished by standard assessments and gives insight to dynamic mechanical and neural events during acute changes in arterial pressure.
Publisher
Ovid Technologies (Wolters Kluwer Health)
Cited by
78 articles.
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