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THE EFFECTS OF REGIONAL BRACHIAL PULSE WAVE VELOCITY ON ARTERIAL OCCLUSION PRESSURE

Abstract

BACKGROUND: Blood flow restriction, the application of external compression to the proximal segment of a limb, has been combined with low-load resistance exercise or low-intensity aerobic exercise to increase muscle function and size. Applying pressure to the limb is a crucial aspect to this mode of training, as full occlusion should be avoided. It is recommended that the restriction pressure be set to a percentage of an individual’s arterial occlusion pressure (AOP). Previous studies have examined several variables that contribute to the determination of AOP, predominantly blood pressure and arm circumference. The purpose of this study was to examine the effects of pulse wave velocity, an indirect marker of arterial stiffness, on AOP, while also accounting for previously-determined predictors of AOP. METHODS: 28 (men=9) participants visited the laboratory on one occasion. Following anthropometric measurements, blood pressure was recorded following 10 minutes of supine rest. A pulse tonometer combined with electrocardiogram (ECG) was used to record 20 consecutive pulse waves at the radial artery. The distance between the suprasternal notch and the measurement location was recorded. The average time between peak R-Wave and the foot of the pressure wave was determined, and from this, pulse wave velocity (PWV) was calculated. Three models of hierarchical linear regression were used to determine the greatest predictor of AOP: Block 1 (blood pressure, both systolic (SBP) and diastolic (DBP)); Block 2 (arm circumference (CIRC)); Block 3 (PWV). RESULTS: Collinearity was not violated in any of the three models. Block 1 predicted 51.0% of the variance in AOP (SBP: β = .698, part = .690, P < .0005; DBP: β = .079, part = .078, P = .582). Block 2 predicted 64.2% of the variance in AOP (SBP: β = .475, part = .402, P = .003; DBP: β = .041, part = .040, P = .745; CIRC: β = .431, part = .364, P = .007). Block 3 predicted 70.2% of the variance in AOP (SBP: β = .336, part = .256, P = .034; DBP: β = -.014, part = -.013, P = .909; CIRC: β = .346, part = .280, P = .022; PWV: β = .326, part = .245, P = .042). CONCLUSIONS: SBP, CIRC, and PWV all explained a statistically significant amount of the variance in the AOP measurement. This study was conducted in a young, healthy population, so additional research should be performed to confirm these results in populations with a wider variation in PWVs.

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