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Ultrasound Assessment of Endothelial-Dependent Flow-Mediated Vasodilation of the Brachial Artery in Clinical Research
Published on: October 22, 2014
A multicenter study on the diagnostic value of ankle brachial index combined with pulse volume wave parameters for
Xiaowei Pan1, Na Wang2, Yue Huang1
1Electrocardiography Department, The First Hospital of Jiaxing Affiliated Hospital of Jiaxing University, Jiaxing, China.
Insights
Adding pulse wave parameters to the ankle-brachial index (ABI) significantly improves peripheral arterial disease (PAD) detection. This integrated approach offers a more accurate, objective assessment for enhanced clinical utility.
Area of Science:
- Vascular Medicine
- Diagnostic Imaging
- Biomedical Engineering
Background:
- Peripheral arterial disease (PAD) diagnosis relies on traditional methods with limitations.
- Pulse wave analysis offers quantitative insights into arterial health.
- Integrating pulse wave parameters may enhance PAD detection accuracy.
Purpose of the Study:
- To assess the diagnostic significance of incorporating pulse volume wave parameters with the ankle-brachial index (ABI) for PAD detection.
- To evaluate the combined efficacy of ABI, inter-arm systolic blood pressure disparity (IASBPD), inter-leg systolic blood pressure difference (ILSBPD), proportion of mean arterial pressure (%MAP), and upstroke time.
Main Methods:
- A multicenter, cross-sectional study involving 1,156 participants.
- Hemodynamic parameters were assessed using an arterial stiffness analyzer.
- PAD diagnosis was based on predefined criteria including ABI, IASBPD, and ILSBPD.
Main Results:
- An integrated diagnostic model showed superior performance (AUC=0.924) compared to individual parameters like ABI (AUC=0.892).
- ILSBPD and %MAP demonstrated significant independent association with PAD diagnosis.
- The composite model achieved 88.6% sensitivity and 85.4% specificity.
Conclusions:
- Integrating ABI with pulse volume wave parameters substantially improves PAD diagnostic accuracy.
- Quantitative pulse wave analysis offers objective assessment, overcoming limitations of conventional methods.
- This multi-parameter strategy enhances PAD detection precision in various clinical settings.
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.
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