A Diagnostic Comparison Study between Maximal Systolic Acceleration and Acceleration Time to Detect Peripheral Arterial Disease

Siem A Willems; Obrecht O van Bennekom; Abbey Schepers; Jan van Schaik; Joost R van der Vorst; Jaap F Hamming; Jeroen J W M Brouwers

doi:10.1016/j.avsg.2024.10.021

A Diagnostic Comparison Study between Maximal Systolic Acceleration and Acceleration Time to Detect Peripheral Arterial Disease

Ann Vasc Surg. 2024 Nov 23:111:203-211. doi: 10.1016/j.avsg.2024.10.021. Online ahead of print.

Authors

Siem A Willems¹, Obrecht O van Bennekom², Abbey Schepers², Jan van Schaik², Joost R van der Vorst², Jaap F Hamming², Jeroen J W M Brouwers²

Affiliations

¹ Department of Vascular Surgery, Leiden University Medical Center, Leiden, The Netherlands. Electronic address: [email protected].
² Department of Vascular Surgery, Leiden University Medical Center, Leiden, The Netherlands.

PMID: 39586527
DOI: 10.1016/j.avsg.2024.10.021

Abstract

Background: Detecting peripheral arterial disease (PAD) can be particularly challenging in patients with diabetes mellitus (DM) or chronic kidney disease (CKD) due to medial arterial calcification (MAC). Current bedside tests, such as the ankle-brachial index, are less accurate in these patient groups. The primary aim of this study is to evaluate the diagnostic accuracy of point-of-care duplex ultrasound parameters maximal systolic acceleration (ACC_max) and acceleration time (AT) to detect PAD, including a comparison of both metrics.

Methods: Patients suspected of having PAD, who underwent point-of-care duplex ultrasound measurements (ACC_max and AT) of the posterior tibial artery (PTA) and/or anterior tibial artery (ATA) at ankle level along with computed tomography angiography were eligible for inclusion. PAD was defined as a stenosis >50% on computed tomography angiography. Diagnostic accuracy of AT was evaluated at calculated (Youden index) and prespecified cut-off values (121 ms), using the sensitivity, specificity, positive likelihood ratio, negative likelihood ratios, and area under the curve. The McNemar test compared ACC_max with AT at prespecified and calculated cut-off values. Subgroup analyses of patients prone to MAC (i.e., those with DM and/or CKD) were also performed.

Results: This study included 184 patients (267 legs) with a high prevalence of DM (53%) and CKD (36%). The diagnostic accuracy of AT to identify PAD for PTA showed a sensitivity of 84%, specificity of 98%, positive likelihood ratio of 42.00, negative likelihood ratio of 0.16 and area under the curve of 0.96. Regarding the ATA, the results were 81%, 93%, 11.57, 0.20, and 0.92, respectively. Statistical comparisons favored ACC_max over AT in detecting PAD at prespecified and calculated cut-off values for both the PTA and ATA (P < 0.001). Additionally, in patients prone to MAC, ACC_max also outperformed AT in detecting PAD (P values ranging from <0.001 to 0.039). For patients without PAD, no significant differences were observed in the ability to rule out the disease.

Conclusions: ACC_max proved to be more accurate than AT in detecting PAD, also in patients prone to MAC. While no significant difference was found between ACC_max and AT in their diagnostic accuracy to exclude PAD, ACC_max should be favored in the diagnostic work-up in patients suspected of PAD due to its superior ability to detect an arterial stenosis.