(759.1) Development of Field-Based Prediction Equations For Determining Leg Limb Occlusion Pressure

Poster Board Number: E493

Sylvia Neph (Alma College), Audrey Plouffe (Alma College), Joseph Vondrasek (Alma College, Alma College), Benjamin Cox (Cox Sports Medicine and Orthopedic Surgery), Jennifer Vranish (Alma College), Alexander Montoye (Alma College)

Blood flow restriction and ischemic preconditioning are occlusion techniques used in clinical and athletic populations as rehabilitation techniques and ergogenic aids. Both require determination of limb occlusion pressure (LOP) to know how much pressure to put in a limb-worn cuff. Measurement of LOP takes sophisticated equipment and designing a low-cost way of predicting LOP may allow for these occlusion techniques to be more readily used in field-based settings.

Purpose: To determine demographic and other variables that can be used to predict LOP.

Methods: Participants (n=23, 57% female) aged 18 to 53 years reported to the laboratory for a single session. Participant age, height, weight, body mass index (BMI), body fat percentage, thigh circumference of both legs, systolic, diastolic blood pressure of both arms and mean arterial pressure (MAP), resting heart rate, and single-leg wall sit times for both legs were assessed. Additionally, participants lay in a supine position and were fitted with an automated system (Delfi) on the proximal thigh, one leg at a time, for determining LOP. LOP was confirmed for each leg using a Doppler ultrasound (GE logique) on the popliteal artery. Then, correlation and stepwise regression analyses were used to determine which variables were significant predictors of LOP.

Results: Right arm MAP (r=0.648) and BMI (r=0.539) had the highest correlations with LOP. Stepwise regression yielded two potential predictive equations to predict LOP. Equation 1: LOP = 2.117*MAP - 6.678 (r2=0.42; standard error of estimate (SEE)=17.6 mmHg); Equation 2: LOP = 1.892*MAP + 2.441*BMI - 52.059 (r2=0.62; SEE=14.6 mmHg).

Conclusion: Arm blood pressure was most closely associated with leg LOP, and MAP along with BMI might serve as useful measures for predicting LOP in field settings. Cross-validation is needed to confirm these preliminary findings, and further analysis should explore other variables that may allow for more accurate prediction of LOP in field settings.

This study was supported by the Alma College CORE Research Program.