Artery Research (Feb 2024)

Ambulatory Arterial Stiffness Index is Associated with the Presence and Severity of Coronary Artery Disease

  • Xintong Qin,
  • Qiuguo Yin,
  • Yidan Zhang,
  • Peng Jiang,
  • Xingtai Jia,
  • Liguo Jian

DOI
https://doi.org/10.1007/s44200-023-00043-3
Journal volume & issue
Vol. 30, no. S1
pp. 11 – 23

Abstract

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Abstract Objective To evaluate the relationship between the ambulatory arterial stiffness index (AASI) and the degree of coronary stenosis, and assess its predictive value for the presence and severity of coronary artery disease (CAD). Materials and methods In total, 619 consecutive patients who presented with exertional anginal symptoms and/or acute coronary syndrome between January 2021 and December 2022 underwent elective non-urgent CAG with no emergency conditions and performed 24-h ambulatory blood pressure monitoring (ABPM) were included in this study and were divided into the control group (n = 68) and CAD group (n = 551) according to the angiography results. Ambulatory Arterial Stiffness Index (AASI) is obtained from the 24-h ABPM recordings, defined as 1 minus the regression slope of diastolic blood pressure on systolic blood pressure values. CAD complexity was determined by the Gensini score (GS). The patients with CAD were stratified according to the tertiles of the Gensini score (GS 48), and GS > 48 is considered severe coronary artery disease. To explore the relationship between AASI and the severity of CAD, Spearman correlation analysis was conducted. Logistic regression analysis was then performed to determine the influence of AASI on CAD as well as severe CAD. Moreover, a Receiver Operating Characteristic (ROC) curve was constructed to assess the predictive value of AASI for CAD and severe CAD. Results The CAD group had a substantially higher median AASI than the control group [0.47 (0.4, 0.58) vs.0.32 (0.24, 0.41), P < 0.001]. There was a positive correlation between AASI and Gensini score. Compared to controls, patients in low-, medium-, and high-GS had significantly higher levels of AASI in a rising trend (P < 0.001). Logistic regression demonstrated that AASI was an independent contributor to CAD and severe CAD. The area under the curve (AUC) for AASI in predicting CAD was 0.806 (P < 0.001), and for predicting high-GS CAD was 0.663 (P < 0.001). Conclusion AASI was associated with CAD and the severity of coronary stenosis and demonstrated predictive potential for both CAD and severe CAD.

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