Association of impaired arterial wall properties with the presence of coronary artery disease in patients with abdominal aortic aneurysms

Abstract

Pulse wave velocity (PWV) is a valid, clinically feasible marker of arterial stiffening, and a strong predictor of outcomes. The present study aimed to compare aortic elastic properties in patients with abdominal aortic aneurysms (AAA), with or without coronary artery disease (CAD), as well as healthy individuals. A total of 130 patients with AAA, eligible for interventional repair, and 30 healthy individuals, comprising the control group (HC), were enrolled. Presence of CAD was identified by coronary angiography. Aortic PWV (aPWV) was measured using the Arteriograph. aPWV was found considerably higher in AAA patients compared with HC group (11.5 ± 2.9 vs 7.3 ± 1.6 m/s, P < .001). Importantly, among patients with AAA, those with concomitant CAD (n = 41) had greater aPWV than those without CAD (12.5 ± 2.9 vs 11.0 ± 3.0 m/s, P = .03). In receiver operator curve (ROC) analysis, a value of aPWV above 12.8 m/s was identified to correlate with the presence of CAD in the AAA patient population. After adjustment for confounders, including hypertension which is one of the major risk factors for abdominal aneurysms, multivariate logistic regression analysis revealed that this aPWV cutoff remained independently associated with presence of CAD [odds ratio = 1.64, 95% confidence interval =1.19‐4.08, P = .03]. The coexistence of CAD and AAA is characterized by a greater arterial stiffness. This finding should be taken into consideration when selecting endovascular stents with more favorable elastic properties. Moreover, AAA patients with high aPWV (>12.8 m/s) are more likely to also have CAD, and this may be considered by vascular surgeons when evaluating patients' cardiovascular risk.

1. INTRODUCTION

Arterial stiffness plays an important role in the development of cardiovascular (CV) disease and it may be used to determine CV risk in clinical practice.1 It has been associated with age and several CV risk factors, including arterial hypertension, dyslipidemia, diabetes mellitus, smoking, and diet.2, 3, 4, 5, 6 The association between aortic stiffness and atherosclerosis has been previously established.7 It has also been associated not only with the presence, but also with the severity of coronary artery disease (CAD).8 Arterial stiffness may play a significant role in predicting CV events and mortality.9

Several markers of arterial stiffness have been suggested, including augmentation index (AIx), pulse wave velocity (PWV), and central aortic pressures as assessed by non‐invasive methods of pulse wave analysis.10 PWV has been proposed as a valid, applicable, and reproducible index of arterial stiffness. Apart from evaluating the arterial elastic properties and vascular dysfunction on end‐organ damage, PWV may also serve as a predictor of future CV events and all‐cause mortality.9

There are no sufficient data regarding aortic stiffness in patients with abdominal aortic aneurysms (AAA). PWV has been found higher in patients with AAA than healthy controls, possibly indicating decreased arterial compliance.11 Alterations in arterial wall composition and inflammation were proposed as contributors to the increased arterial stiffness in AAA.11, 12 Furthermore, PWV was related, not only to the presence, but also to the severity of CAD in symptomatic CAD patients.8, 13 In asymptomatic CAD patients, higher PWV values were also associated with the progression of coronary atherosclerosis assessed by either coronary artery calcium (CAC) score or luminal stenosis on computed tomography coronary angiography (CCTA).13, 14, 15 Moreover, severe CAD has been associated with presence of abdominal aneurysms.16 However, the association between increased PWV and presence of CAD in patients with abdominal aneurysms has not been investigated.

In the present study, we hypothesized that increased arterial stiffness is associated with presence of CAD in AAA patients. Therefore, we assessed the elastic aortic properties using pulse wave analysis, in patients with AAA, we compared them with those of healthy individuals, and we examined the association of markers of pulse wave analysis with the presence of CAD in the AAA study cohort.

2. PATIENTS AND METHODS

2.1. Study population

The present study is a prospective, single‐center trial that enrolled 130 patients with AAA eligible for interventional repair, according to European Society of Vascular Surgery Guidelines.17 These patients were scheduled to undergo endovascular aneurysm repair (EVAR) in our tertiary care university hospital and agreed to participate in this study. The management and selection of stent‐graft devices were based on the medical history of the patients and the anatomical characteristics of the AAA. Patients with thoracoabdominal, thoracic or juxtarenal aortic aneurysms, aortic para‐anastomotic pseudoaneurysms, and ruptured aneurysms were excluded from the analysis. Further exclusion criteria were also history of recent myocardial infarction (within the past 6 months), chronic symptomatic heart failure (New York Heart Association [NYHA] class III‐IV), collagen‐related disorders, including Marfan or Ehlers‐Danlos syndrome, malignancy, auto‐immune diseases, and other life‐threatening and severe conditions. Patients with chronic kidney disease (defined as serum creatinine levels >1.5 mg/dL or estimated glomerular filtration rate <60 mL/min/1.73 m²) were also excluded as these conditions may have affected baseline arterial stiffness. All AAA patients underwent coronary angiography, and the presence of CAD was defined as at least one stenosis >70% in one or more coronary arteries.

Thirty healthy individuals were also enrolled into the study as the control group (ie, healthy controls, HC). These patients were age‐ and sex‐matched volunteers without known CV disease or CAD equivalents, including diabetes mellitus (DM) or AAA. They also had a recent negative non‐interventional testing for myocardial ischemia.

The study was approved by the Scientific and Ethics Committee of our hospital in compliance with the principles of the 1975 Declaration of Helsinki. All participants signed written informed consent prior to their enrollment in the trial.

2.2. Data collection and measurements

All data, including demographics, past medical history, drug therapy, and clinical measurements, were documented at a case report form (CRF) by a single operator. Blood pressure (BP) was measured in the morning at sitting position twice (with a 5‐minute interval between measurements), and the average value was included into the analysis. These measurements were obtained after resting for 20 minutes. Body mass index (BMI) was calculated by dividing the body weight in kilograms by the square of the height in meters (kg/m²). Waist‐hip ratio (WHR) was calculated by the ratio between waist circumference, measured at the midway between lower rib margin and iliac crest, and hip girth, assessed at the greater femoral trochanters level. The ankle‐brachial index (ABI) was calculated by dividing the highest blood pressure recorded at the ankle by the highest pressure recorded at the brachial artery.

Hypertension was defined as office systolic blood pressure (SBP) ≥140 mm Hg and/or DBP ≥90 mm Hg, or in the presence of antihypertensive drug therapy, according to current guidelines.18 Dyslipidemia was defined as a disorder of lipoprotein metabolism, assessed by low‐density lipoprotein cholesterol (LDL‐C) levels according to CVD risk, or in the presence of drugs for treatment of dyslipidemias.19 Diabetes mellitus was defined as the presence of fasting hyperglycemia (fasting plasma glucose ≥7.0 mmol/L or 126 mg/dL) or 2‐hour plasma glucose ≥11.1 mmol/L (or 200 mg/dL) or HbA1c ≥6.5% (or 48 mmol/mol) or in the presence of antidiabetic drug therapy.20 Current smokers were those patients who smoked more than five cigarettes per day.21

The Arteriograph (TensioMed TensioClinic Arteriograph TL1, Tensiomed Ltd.) was used to record aortic PWV (aPWV) and central systolic BP (SBP) (cSBP). Arm circumferences were measured to define the correct choice of cuff size (two sizes available: 24‐34 and 32‐42 cm). An upper arm cuff was applied to the patient, and after a first BP measurement, the cuff was over‐inflated with 35‐40 mm Hg beyond SBP. During systole, blood volume having been ejected into the aorta generates a pulse wave (early systolic peak). This pulse wave runs down and reflects from the bifurcation of aorta, creating a second wave (late systolic peak). Both early systolic peak and late systolic peak were obtained and recorded on the computer as pulse waves. The difference in time between the beginning of the first wave and the beginning of the second (reflected) wave was related to the measured distance from the jugulum to the symphysis, resulting in the assessment of PWV in m/s. The software of Arteriograph decomposes the early, late systolic and diastolic waves and also determines the onset and peaks of the waves. For PWV analysis, the onsets of the waves are determined by using first and second derivatives.22, 23 Augmentation index (%) was calculated using the formula AIx = 100 × (Augmentation pressure)/(Pulse pressure). Our laboratory had validated measurements, which were performed by a single observer, with 2.3% intra‐observer variability for PWV.23 The operator performing the vascular studies was blinded to results of coronary angiography in the AAA patients.

2.3. Statistical analysis

The statistical software package used was the SPSS 21.0 (IBM Corporation). Data are reported as numbers and percent of nonmissing values for categorical variables or mean and standard deviation (SD) for quantitative variables. Normal distribution of continuous variables was defined using the Kolmogorov‐Smirnov test. Categorical variables were compared between patients with AAA, CAD, and HC using chi‐square tests. Quantitative variables were compared between groups using Student's t test, one‐way ANOVA, and post hoc Turkey's test as appropriate. The Pearson and Spearman coefficient analysis was used to identify correlations between PWV and other variables, including SBP and diastolic BP (DBP). Univariate logistic regression analysis was performed to examine relationships between common non‐invasive markers, including PWV, and the odds of disease presence (AAA or CAD). Receiver operating characteristic (ROC) curve analysis was used to predict CAD presence according to PWV levels. Multivariate logistic regression analysis was also performed to identify predicting factors for the coexistence of CAD in the AAA study group. For all tests, which were two‐sided, a P value of .05 or less was considered as indicating statistically significant differences.

3. RESULTS

Study groups did not differ in anthropometrical characteristics and CV risk factors (ie, hypertension, DM, dyslipidemia, obesity, and smoking), as shown in Table 1. aPWV was significantly higher in the AAA group than in the control group (11.5 ± 2.9 m/s vs 7.3 ± 1.6 m/s, P < .001), after adjustment for age, sex, and mean arterial pressure (MAP). AAA patients also demonstrated increased central SBP (cSBP), central pulse pressure (cPP), and augmentation index (Aix) compared with the control group (P < .001; Table 2). A slightly higher SBP was observed in AAA group. Furthermore, in a univariate analysis within the AAA group, aPWV was positively correlated with SBP (r = .430, P = .01), DBP (r = .401, P = .02), cPP (r = .312, P = .001), and cSBP (r = .301, P = .002). The presence of AAA was significantly associated with PWV levels (r = .550, P = .001).

Table 1.

Clinical characteristics of the study population

Variable	AAA group (n = 130)	Control group (n = 30)	P
Age (y)	73.9 ± 6.1	71.2 ± 8.4	.1
Risk factors
Hypertension n (%)	102 (78)	19 (63)	.5
Diabetes mellitus n (%)	21 (16)	7 (23)	.4
Dyslipidemia n (%)	54 (42)	11 (38)	.9
Current smoking n (%)	81 (62)	13 (45)	.8
ΒΜΙ (kg/m2)	31 ± 6	29 ± 5	.6
WHR	0.91 ± 0.1	0.87 ± 0.09	.3
Medication (%)
β‐blockers	65 (50)	10 (33)	.1
ACE inhibitors/ARBs	64 (49)	11 (37)	.2
CCBs	47 (36)	8 (27)	.4
Diuretics	46 (35)	10 (33)	.9
Statins	72 (55)	12 (40)	.1

Smoking refers to current smokers defined as smoking >5 cigarettes daily.

Abbreviations: AAA, abdominal aortic aneurysm; BMI, body mass index; ACE, angiotensin‐converting enzyme; ARBs, angiotensin receptor blockers; CCBs, calcium channel blockers. WHR, waist‐hip ratio.

Table 2.

Comparison of hemodynamic parameters and markers of arterial stiffness between study groups

Variable	AAA group (n = 130)	Control group (n = 30)	P
aPWV (m/s)	11.5 ± 2.9	7.3 ± 1.6	<.001
SBP (mm Hg)	135 ± 18	131 ± 12	.02
DBP (mm Hg)	83 ± 10	81 ± 8	.1
MAP (mm Hg)	100 ± 13	98 ± 10	.1
cSBP (mm Hg)	137 ± 23	123 ± 11	<.001
cPP (mm Hg)	51 ± 15	35 ± 5	<.001
Aix (%)	37.0 ± 16	25.0 ± 6	<.001

Abbreviations: Aix, augmentation index; aPWV, aortic pulse wave velocity; cPP, central pulse pressure; cSBP, central systolic blood pressure; DBP, diastolic blood pressure; MAP, mean arterial pressure; SBP, systolic blood pressure.

Among AAA patients, 41 had also coronary artery disease. After adjustment for age, sex, and MAP, aPWV was significantly higher in patients with concomitant CAD than those without CAD (n = 89) (12.5 ± 2.9 vs 11.0 ± 3.0 m/s, P = .03). They also had higher cSBP (145 ± 26 vs 135 ± 21 mm Hg, P = .04) and cPP (58 ± 15 vs 49 ± 14 mm Hg, P = .01). Other hemodynamic indexes and markers of arterial stiffness did not demonstrate significant differences among the two groups, as shown in Table 3. History of hypertension (86% vs 75%, P = .2), DM (15% vs 17%, P = .8), dyslipidemia (44% vs 40%, P = .7), smoking (73% vs 57%, P = .1), and markers of obesity (BMI and WHR) did not differ significantly between AAA patients with or without CAD. No statistically significant differences regarding drug therapy were observed between the aforementioned groups.

Table 3.

Clinical and hemodynamic parameters, and markers of arterial stiffness among AAA patients with or without CAD

Variable	AAA with CAD (n = 41)	AAA without CAD (n = 89)	P
Hypertension (%)	35 (86)	67 (75)	.2
Diabetes mellitus (%)	6 (15)	15 (17)	.8
Dyslipidemia (%)	18 (44)	36 (40)	.7
Smoking (%)	30 (73)	51 (57)	.1
ΒΜΙ (kg/m2)	32 ± 5	30 ± 6	.7
WHR	0.93 ± 0.09	0.90 ± 0.11	.5
SBP (mm Hg)	139 ± 22	134 ± 18	.1
DBP (mm Hg)	84 ± 12	83 ± 10	.3
MAP (mm Hg)	102 ± 12	100 ± 13	.2
aPWV (m/s)	12.5 ± 2.9	11.0 ± 3.0	.03
cSBP (mm Hg)	145 ± 26	135 ± 21	.04
cPP (mm Hg)	58 ± 15	49 ± 14	.01
Aix (%)	39.5 ± 16.2	35.0 ± 16.4	.25
ABI	1.06 ± 0.16	1.13 ± 0.17	.1
Medication (%)
β‐blockers	26 (63)	39 (44)	.1
ACE inhibitors/ARBs	23 (56)	41 (46)	.4
CCBs	16 (39)	31 (35)	.6
Diuretics	15 (37)	31 (35)	.8
Statins	27 (66)	45 (51)	.1

Abbreviations: AAA, abdominal aortic aneurysm; ABI, ankle branchial index; ACE, angiotensin‐converting enzyme; Aix, augmentation index; aPWV, aortic pulse wave velocity; ARBs, angiotensin receptor blockers; BMI, body mass index; CAD, coronary artery disease; CCBs, calcium channel blockers; cPP, central pulse pressure; cSBP, central systolic blood pressure; DBP, diastolic blood pressure; MAP, mean arterial pressure; SBP, systolic blood pressure; WHR, waist‐hip ratio.

Interestingly, the area under the curve (AUC) of aPWV for the prediction of CAD presence in the AAA study group was 0.72 (95% confidence interval [CI]: 0.55‐0.84, P = .03). The AUC for the prediction of CAD for cPP was slightly lower (0.57, 95% CI: 0.53‐0.79, P = .05). According to the aforementioned ROC curve, the best cutoff value for predicting the coexistence of CAD in AAA patients was a value of aPWV above 12.8 m/s (78% sensitivity and 73% specificity). This cutoff was identified as a significant predictor of CAD presence in the AAA study population according to univariate logistic regression analysis (OR = 2.51, 95% CI: 1.79‐5.19, P = .02). After adjustment for age, sex, dyslipidemia, smoking, and MAP in multivariate logistic regression analysis, the cutoff aPWV level remained independently associated with the presence of CAD (OR = 1.64, 95% CI: 1.19‐4.08, P = .03). The cutoff of cPP for the detection of CAD was 52.5 mm Hg with 74% sensitivity and 63% specificity. However, this cutoff was not independently associated with the presence of CAD after adjustment for age, sex, dyslipidemia, smoking, and MAP (OR = 1.22, 95% CI: 0.95‐2.68, P = .14).

4. DISCUSSION

In the present study, patients with AAA had significantly higher aPWV levels compared with the control group. This finding may be useful in selecting the most appropriate type of endovascular stent based on the elastic properties of the aorta. Furthermore, aPWV was even higher in patients with both AAA and CAD compared with those without CAD. A possible clinical implication of this finding is that the presence of an increased arterial stiffness (assessed by aPWV) above a certain cutoff point in AAA patients could raise concern about the coexistence of CAD, thus leading to further evaluation of these very high‐risk patients. Nevertheless, more data are needed to establish such a cutoff point in AAA patients.

These findings are in accordance with previous studies showing that AAA patients have increased cfPWV levels compared with healthy individuals,12, 24 as do CAD patients.13 To the best of our knowledge, this is the first study comparing aPWV levels within AAA patient population according to the coexistence of CAD, showing that the combination of AAA with CAD is associated with an even greater aPWV than the presence of AAA alone. As increased arterial stiffness can exert harmful effects on the myocardial function,25 this finding highlight the need for a closer monitoring of these patients for adverse CV events and a more intensive medical treatment to prevent their occurrence.

The pathophysiology of AAA includes an increased production of collagen and a reduction in elastin.12 Arteriosclerosis, the arterial remodeling process that usually occurs at elastic arteries, gradually worsens with age.26 The main pathophysiological mechanisms involve reduction of elastic fibers and increased fibrosis of the arterial wall due to the increased shear stress and luminal pressure.12 These changes in the composition of the extracellular matrix of the arterial wall may result in augmentation of arterial stiffness. Increased arterial stiffness and PP can lead to rises in SBP, vascular remodeling, and atherosclerotic plaque formation. Furthermore, increased PWV and atherosclerosis share common traditional risk factors, including hypertension, dyslipidemia, and DM.27, 28 Several biomarkers indicative of arterial changes related to atherosclerosis have been correlated to PWV.29 In this context, the presence of AAA was independently related to osteoprotegerin (OPG) levels.12 Therefore, alterations in composition of extracellular matrix of the arterial wall and atherosclerosis seem to be the main pathophysiological pathways that lead to impaired aortic compliance in AAA patients.

Atherosclerosis may also represent the main mechanism linking aortic stiffness and CAD.7 Furthermore, reduced DBP, as a consequence of impaired aortic elastic properties, may result in decreased coronary perfusion, which could further deteriorate the symptoms and prognosis of CAD patients.30, 31 In this context, increased aortic stiffness has been linked to increases in cardiac workload and decreased coronary artery perfusion.32 The predictive role of PWV for the diagnosis of CAD has been demonstrated in several studies.8 Proportional increases in PWV values with the severity of CAC score have also been reported.33 Furthermore, PWV was correlated with the presence and progression of stenosis or plaque development in the coronary arteries according to findings from CCTA in asymptomatic DM patients.14, 34 Similarly, in asymptomatic individuals, PWV was identified as an independent prognostic factor for the presence of CAD diagnosed by CCTA.15, 35, 36 In symptomatic patients, PWV levels were positively related to the presence and severity of CAD as assessed by invasive coronary angiography.13, 37, 38, 39 Furthermore, osteoprotegerin and osteopontin levels have been associated with CAD progression through arterial wall stiffening and inflammation. It appears that elevated levels of these biomarkers represent a common biochemical link between arterial stiffness and coronary artery disease in patients with abdominal aortic aneurysms.40

In the present study, a value of aPWV above 12.8 m/s was found to predict the coexistence of CAD in AAA patients. In a previous meta‐analysis (n = 18 000 patients), the hazard ratios change in log_e aPWV per 1 SD were 1.35 (95% CI, 1.22‐1.50; P < .001) for CAD incidence and 1.30 (95% CI, 1.18‐1.43; P < .001) for CV events.41 Increased PWV independently predicted a future PCI in CAD patients, highlighting that arterial stiffness is also involved in the progression of new culprit lesions in coronary arteries after PCI.42

It is worth noting that arterial stiffness has also been related to microvascular damage in hypertensive patients, CV risk prediction and the presence of peripheral artery disease, indicating its significant role in polyvascular disease.8 The Framingham Heart Study reported that elevated PWV values were correlated with an increase in an almost 50% relative risk of CV events.43 Another large‐scale meta‐analysis of 17 cohort studies (n = 15 877) showed that, after adjustment for age, sex, and risk factors, for every increase in aortic PWV by 1 m/s, a rise of 14% in CV events, 15% in CV mortality and 15% in all‐cause death was observed.1 These studies included not only general population, but also high‐risk groups (CAD, renal disease, hypertension, and diabetes). A more recent meta‐analysis of 19 studies (n = 19 908) demonstrated a rise of 12% in future CV events for every increase in carotid‐femoral PWV by 1 m/s. These cohorts were mixed; eight of them included patients with various diseases, such as hypertension, renal failure, and renal transplant recipients, whereas the rest of them included healthy individuals.44

Endovascular repair of AAA has been correlated with a negative effect on aortic compliance and an increase in PWV.1, 8, 45, 46 In this context, even a small rise in this aortic stiffness marker may result in subsequent increases in left ventricular afterload, myocardial energy requirements, and adverse prognostic outcomes.9 Therefore, in AAA patients with increased baseline PWV levels, including those with coexisting CAD, a careful selection of endovascular stents with more favorable biomechanical properties may result in better long‐term outcomes.

Several CV risk factors, including hypertension, obesity, dyslipidemia, DM, and smoking, have been associated with increased arterial stiffness.2, 3, 4, 5, 6 Specifically, cigarette smoke has compounds that participate in oxidant and inflammatory pathways and may directly induce endothelial damage and enhance inflammation response leading to increased arterial stiffness, CAD and generation of abdominal aortic aneurysms.47 However, in our study, the association of PWV with CAD remained significant after adjustment for current smoking. It should be noted that, in the present study, there were no significant differences in the aforementioned CV risk factors between the AAA group and the control group, as well as among AAA patients with and without CAD. Furthermore, antihypertensive, hypolipidemic, and antidiabetic drugs may affect arterial stiffness.48, 49, 50, 51, 52 In our study, no significant differences in the drug therapy were observed among AAA patients with and without CAD.

Atherosclerotic vascular lesions may also be affected by the antioxidant effects of diet53, 54; however, data on dietary habits were not available in our study cohort. Another limitation of the present study was the non‐randomized, case‐control, single‐center design of the study. However, the control group included age‐ and sex‐matched volunteers without known CV disease or CAD equivalents and similar traditional atherosclerotic risk factors with the AAA patients. The sample size of the AAA (n = 130) was sufficient to investigate the association of PWV with the presence of CAD, and also to the best of our knowledge, until now, there is no large‐scale, randomized trial to examine differences in aortic stiffness markers between AAA patients with or without CAD. Another strength of our analysis was that CAD was identified by invasive coronary angiography, which is considered a gold standard examination. Furthermore, the operator performing the vascular studies was blinded to results of coronary angiography in the AAA patients. All potential parameters that could affect arterial stiffness, including history of hypertension, obesity, dyslipidemia, diabetes mellitus, and smoking, as well as, medical treatment for these CV risk factors were included in the multivariate analysis assessing the association of PWV with the presence of coexisting CAD.

It should also be noted that though PWV is considered as the gold standard non‐invasive marker of aortic stiffness assessment, its measurement suffers from some technical limitations. PWV measurement should be performed by experienced personnel and it may be technically difficult to obtain, especially in obese patients. Standardization regarding distance measurements, is also needed, as small differences in distance measurement may impact greatly the calculated value of PWV. As PWV can be measured by various commercially available devices using different methodology for its calculation (eg, oscillometry or tonometry) and these devices are not considered interchangeable for the PWV measurement,23, 55 our results should be considered applicable for devices using the oscillometric method. Despite these issues, PWV is considered a clinical surrogate end point by the European Society of Cardiology (ESC) Working Group on peripheral circulation,56 whereas current ESC/European Atherosclerosis Society (EAS) guidelines recommend that patients at moderate CV risk with carotid‐femoral PWV >10 m/s should be re‐classified as high‐risk.19

In conclusion, the present study reported increased aPWV levels in AAA patients compared with controls; the presence of CAD further raised aPWV. Furthermore, a value of aPWV above 12.8 m/s predicted the coexistence of CAD in AAA patients. These findings support a role of measuring arterial stiffness markers when evaluating AAA patients. Further studies are needed to explore whether aPWV values could be used to as a screening tool to detect CAD or to guide treatment in AAA patients.

CONFLICT OF INTEREST

II has given invited talks and attended conferences sponsored by Bayer, Boehringer Ingelheim, and Janssen. NK has given talks, attended conferences and participated in trials sponsored by Astra Zeneca, Bausch Health, Boehringer Ingelheim, Elpen, Mylan, Novo Nordisk, Sanofi, and Servier. The other authors declare no conflict of interest.

AUTHORS CONTRIBUTION

Conceptualization: PRS, II, NPEK; Data accuracy: PRS, II, NPEK, SV, JT; Formal analysis: PRS, II, NPEK, NK, KGM, JDK; Investigation: NPEK, SV, JT; Methodology: PRS, II, NPEK, NK, JP, KGM, JDK; Project administration: PRS, II; Resources: II, KGM, JDK; Supervision: II, JP, KGM, JDK; Validation: PRS, II, KGM, JDK; Visualization: PRS, II, NK, KGM, JDK; Writing – original draft: PRS, II, NK and Writing – review & editing: PRS, II, NPEK, NK, JP, KGM, JDK.

Rafouli‐Stergiou P, Ikonomidis I, Katsiki N, et al. Association of impaired arterial wall properties with the presence of coronary artery disease in patients with abdominal aortic aneurysms. J Clin Hypertens. 2020;22:187–193. 10.1111/jch.13825