4.8 Article

Sympathetic neural burst amplitude distribution -: A more specific indicator of sympathoexcitation in human heart failure

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CIRCULATION
卷 102, 期 17, 页码 2076-2081

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LIPPINCOTT WILLIAMS & WILKINS
DOI: 10.1161/01.CIR.102.17.2076

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nervous system, autonomic; heart failure; hormones; aging

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Background-Human muscle sympathetic nerve activity (MSNA) is usually measured as the number of pulse-synchronous bursts in multiunit mean voltage recordings. We recently suggested burst amplitude distribution as a more sensitive indicator of altered MSNA in congestive heart failure (CHF). Here, we test whether this distribution can discriminate between different conditions with increased MSNA burst frequency and whether it reflects single vasoconstrictor fiber firing intensity. Methods and Results-We analyzed resting multiunit MSNA in 36 CHF patients (24 with mild to moderate CHF, 12 with severe CHF investigated before and after heart transplantation), 14 patients with pituitary deficiency, 25 matched healthy control subjects, and an additional 56 healthy men with a wider age range (21 to 71 years). Pituitary deficiency was associated with increased MSNA burst frequency (60 versus 37 bursts/min in control subjects), equivalent to that in mild to moderate CHF (61 bursts/min). However, burst amplitude distribution in hypopituitary patients (median burst amplitude, 37%) did not deviate from matched control subjects (36%), whereas amplitudes increased with disease severity in CHF (43% in mild to moderate, 52% in severe) and normalized after transplantation (36%). In the larger healthy group, MSNA burst frequency increased with age, and burst amplitude distribution remained unaffected. In 8 CHF patients, single-unit firing frequency showed a close positive relationship to multiunit burst amplitude distribution (r=0.82, P<0.01) but none to burst frequency (r=0.39, P=0.3). Conclusions-Muscle vasoconstrictor fiber activity is better reflected by multiunit MSNA burst amplitude distribution than by burst frequency, at least in CHF. This distribution can discriminate between conditions with increased burst frequency.

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