Brachial Pulse Wave Velocity Contributes To Upper Body Arterial Occlusion Pressure In Blood Flow Restriction

Measuring arterial occlusion pressure (AOP) is vital when applying blood flow restriction (BFR). Limb pulse wave velocity has never been included in previous studies. PURPOSE: To determine whether brachial pulse wave velocity (bPWV) accounts for any variance in upper body AOP after accounting for previous predictors. METHODS: 64 (men = 19) participants had left arm circumference (CIRC) measured at half the distance between the acromion process and antecubital fossa, and then rested supine with that arm extended laterally. After 10 minutes, blood pressure was measured using an automated blood pressure cuff. An electrocardiogram and pulse tonometer were used to record 20 consecutive cardiac cycles and pulse waves at the left radial artery. The distance between the suprasternal notch and this location was recorded. The second derivative of the pressure wave was calculated via software to locate the foot of the pressure wave. Average time between peak R-Wave and the foot of the pressure wave was recorded, and bPWV was calculated. AOP was measured using a 5 cm inelastic cuff placed at the proximal left arm and a Doppler probe placed over the radial artery at the wrist. Hierarchical linear regression was used to examine predictors of AOP in the upper body: Block 1 comprised systolic and diastolic blood pressure (SBP and DBP, respectively); Block 2 added CIRC; Block 3 added bPWV. Standard error of the estimate (SEE), standardized betas (β), and part correlation coefficients (part) were used to examine each block. Statistical significance was set at α = .05. RESULTS: Block 1 (SEE = 14.608) significantly explained 58.1% of the variance in AOP (P < .001), with SBP (β = .698, part = .674, P < .001) and DBP (β = .173, part = .167, P = .049) contributing. Block 2 (SEE = 12.590) significantly explained 69.4% of the variance in AOP, with SBP (β = .491, part = .406, P < .001) and CIRC (β = .404, part = .336, P < .001) contributing. Block 3 (SEE = 11.950) significantly explained 72.9% of the variance in AOP, with SBP (β = .410, part = .320, P < .001), CIRC (β = .387, part = .321, P < .001), and bPWV (β = .221, part = .187, P = .008) contributing. CONCLUSION: Our findings indicate that bPWV predicts some of the variance in AOP. This may have implications when applying BFR to those with arteriosclerosis. This study should be repeated in a population more likely to have higher PWV.