A multicenter study on the diagnostic value of ankle brachial index combined with pulse volume wave parameters for peripheral arterial disease

Objective To evaluate the significance of incorporating all pulse volume wave parameters, such as the inter-arm systolic blood pressure disparity, inter-leg systolic blood pressure difference, proportion of mean arterial pressure, and upstroke time, into the ankle-brachial index for the detection of peripheral arterial disease. Methods This multicenter cross-sectional investigation, conducted across five tertiary medical institutions, enrolled 1,156 participants. Hemodynamic parameters including blood pressure and pulse volume were systematically assessed utilizing an OMRON BP-203RPEIII arterial stiffness analyzer. All four extremities were evaluated in a simultaneous manner under strictly standardized conditions. PAD diagnosis was established by fulfilling one of the predefined criteria: ankle-brachial index (ABI) ≤ 0.9, inter-arm systolic blood pressure disparity (IASBPD) ≥ 10 mmHg, or inter-leg systolic blood pressure divergence (ILSBPD) ≥ 15 mmHg. Diagnostic efficacy was evaluated via receiver operating characteristic curve analysis. Multivariate logistic regression was employed to determine the independent predictive utility of individual or composite parameters. Results Integrated diagnostic model demonstrated superior discrimination performance in differentiating PAD patients from non-PAD individuals (AUC = 0.924, 95% CI: 0.908–0.940) compared with individual parameters analysis: ABI (AUC = 0.892, 95% CI: 0.872–0.912), ILSBPD (AUC = 0.846, 95% CI: 0.824–0.868), and %MAP (AUC = 0.834, 95% CI: 0.812–0.856). Multivariate logistic regression analysis of all parameters revealed significant independent association with PAD diagnosis. Specifically, ILSBPD exhibited the strongest positive correlation (OR = 1.82, 95% CI: 1.56–2.12, p < 0.001), followed by %MAP (OR = 1.76, 95% CI: 1.48–2.08, p < 0.001). Subgroup analyses identified augmented diagnostic value in patients over 75 years and with diffuse arterial disease. Composite model achieved optimal diagnostic metrics of 88.6% sensitivity and 85.4% specificity. Conclusions Integration of ABI with pulse volume wave parameter improved PAD diagnostic accuracy significantly. Quantitative PVR metrics provides objective assessment of peripheral arteries, effectively mitigating limitations of conventional modalities. Automated measurements with predefined thresholds ensure clinical applicability. This approach enhances the clinical utility of a multi-parameter diagnostic strategy applicable across both specialized vascular laboratories and primary care settings, thereby enhancing the precision of PAD detection.