Abstract
Introduction: It is not well-known which indicator, central blood pressure (CBP) or arterial stiffness, has a greater impact on carotid atherosclerosis. This study aimed to assess the associations of carotid atherosclerosis with arterial stiffness and CBP in the same individuals. Methods: A total of 142 patients (mean age: 69 years; 43% female) with documented atherosclerotic cardiovascular disease or multiple risk factors were analyzed. Brachial-ankle pulse wave velocity (baPWV) and CBP measurements, along with carotid ultrasound, were performed on the same day. CBP was assessed using radial artery tonometry. Results: In simple linear regression analysis, only baPWV exhibited a significant correlation with carotid intima-media thickness (CIMT) (r = 0.272; p = 0.001), whereas none of the CBP parameters (systolic, diastolic, pulse pressures, and augmentation index) correlated with CIMT (p > 0.05 for each). Multiple linear regression analysis indicated that baPWV had no significant association with CIMT after adjusting for age (p = 0.264). A higher baPWV (≥1,656 cm/s) was significantly associated with carotid plaque presence, even after accounting for potential confounders (odds ratio: 3.66; 95% confidence interval: 1.65–8.12; p = 0.001). Moreover, as the number of carotid plaques increased, there was a linear rise in baPWV (p < 0.001). None of CBP parameters were associated with the presence of carotid plaque (p > 0.05 for each). Conclusions: Among a high-risk Korean population, baPWV demonstrated a stronger association with carotid plaque presence and extent compared to CBP parameters. Thus, baPWV may serve as a valuable marker for identifying carotid plaque.
Introduction
The carotid artery, easily imaged via ultrasound, is crucial for assessing atherosclerosis and predicting cardiovascular disease, including stroke [1‒3]. Carotid intima-media thickness (CIMT) and atherosclerotic plaques are key markers in this assessment. Increased CIMT indicates early atherosclerosis, helping stratify cardiovascular risk [2, 3]. Carotid plaques suggest more advanced disease and a higher risk of ischemic stroke [3, 4]. Together, CIMT and plaques provide a comprehensive view of atherosclerotic burden and guide clinical decisions and preventive care [3].
As we age or are exposed to risk factors like high blood pressure, hyperglycemia, and chronic inflammation, our arterial walls harden, leading to increased arterial stiffness [5]. Understanding arterial stiffness is clinically vital as it can predict future cardiovascular events or mortality, independent of traditional risk factors [6, 7]. In pulse wave velocity (PWV) testing, carotid-femoral PWV (cfPWV) and brachial-ankle PWV (baPWV) are two common measures, with cfPWV regarded as the gold standard for assessing arterial stiffness. cfPWV directly measures the central arterial stiffness by capturing PWV between the carotid and femoral arteries, which is closely associated with cardiovascular risk. However, baPWV is also widely used due to its practicality and ease of measurement as it involves the brachial and ankle arteries. Despite cfPWV being the gold standard, baPWV remains valuable, particularly in clinical settings where it provides a feasible and reliable alternative for assessing arterial stiffness [7, 8].
Central blood pressure (CBP) signifies the pressure within the aorta and other central arteries. It more accurately reflects the hemodynamic stress experienced by essential organs such as the heart, brain, and kidneys, thereby directly relating to the risk of end-organ damage [9]. Consequently, elevated CBP is linked to an increased risk of cardiovascular morbidity and mortality [9]. In contrast to brachial blood pressure, which is commonly measured in clinical settings, CBP offers a more precise prediction of cardiovascular risk and outcomes [10‒15].
Numerous studies have shown the impact of arterial stiffness and CBP on carotid atherosclerosis, often focusing on individual relationships between CBP and CIMT or arterial stiffness and carotid plaques [8, 14‒17]. Understanding how arterial stiffness and CBP together affect CIMT and carotid plaques is essential for proactive risk assessment. This study explored the associations between CBP indicators, baPWV, and the presence of CIMT and carotid plaques, aiming to improve early identification and intervention in cardiovascular disease risk.
Methods
Study Population
This single-center, cross-sectional study included patients from Boramae Medical Center (Seoul, South Korea) between June 2020 and December 2021. Participants were aged between 20 and 90 years and had documented cardiovascular or cerebrovascular disease, or at least two risk factors: age (≥45 for men, ≥ 55 for women), hypertension, diabetes, dyslipidemia, smoking, or obesity. Initially, 159 subjects were screened, with 17 excluded based on the following criteria: uncontrolled blood pressure (>180/110 mm Hg) (n = 2), arrhythmia (n = 3), end-stage renal disease (n = 2), abnormal ankle-brachial index (n = 2), low left ventricular ejection fraction (<50%) (n = 4), significant cardiac valvular disease (n = 2), congenital heart disease (n = 1), and pericardial effusion (n = 1). One subject had their CBP measured, but the value was deemed unreliable and was excluded from the analysis. Ultimately, 142 subjects were included in the final analysis for this study. The study enrollment flow chart is shown in Figure 1. Written informed consent was obtained from all participants prior to the study. The study followed the Declaration of Helsinki and was approved by Boramae Medical Center IRB (IRB number: 20-2019-103).
Study enrollment flow chart. baPWV, brachial-ankle pulse wave velocity; CBP, central blood pressure.
Study enrollment flow chart. baPWV, brachial-ankle pulse wave velocity; CBP, central blood pressure.
Clinical Data Collection
Height and weight were measured to calculate body mass index, defined as weight in kilograms divided by height in meters squared, with obesity defined as a body mass index of ≥ 25 kg/m2 [18]. Hypertension was defined by a prior diagnosis, use of anti-hypertensive medications, or high blood pressure (SBP ≥140 mm Hg or DBP ≥90 mm Hg). Diabetes was characterized by a prior diagnosis, use of anti-diabetic medications, high fasting glucose, or high glycated hemoglobin (≥6.5%). Dyslipidemia was identified by a prior diagnosis, use of anti-dyslipidemic medications, or high low-density lipoprotein cholesterol (≥160 mg/dL). Current smokers were those who smoked in the past year. Coronary artery disease included history of myocardial infarction, revascularization, documented ischemia, or significant stenosis in coronary arteries. Ischemic stroke was identified by sudden neurological deficits and brain imaging abnormalities. After 12 h of fasting, venous blood was collected to measure various parameters, including glucose, glycated hemoglobin, cholesterol levels, creatinine, and C-reactive protein. The estimated glomerular filtration rate was calculated using the Modification of Diet in Renal Disease equation. Information on cardiovascular medications was also collected.
baPWV Measurement
baPWV was measured using a volume-plethysmographic device (VP-1000; Colin Co. Ltd, Komaki, Japan) [19]. The test was conducted in a quiet space, with patients abstaining from smoking and caffeine for 12 h prior. Patients rested supine for 5 min before measurement. Oscillometric cuffs were placed on the brachial and ankle regions and inflated to record pulse waveforms. ECG electrodes ensured synchronized pressure adjustments. The baPWV was calculated as the path length (based on the patient’s height) divided by the time difference between brachial and ankle waveforms. The average value of left and right baPWV was used. An experienced technician performed the test, with an inter-observer variability of approximately 5% [20].
CBP Measurement
In the same room, immediately following the baPWV measurement, CBP was assessed using radial artery applanation tonometry (HEM-9000AI; Omron Healthcare, Kyoto, Japan) [21]. Left radial artery pressure waveforms and right brachial blood pressure were measured after the patient had rested for at least 5 min. Peripheral systolic pressure peaks (SBP1 and SBP2) were calibrated with brachial SBP to derive central SBP from SBP2 [22]. Pulse pressure (PP) was calculated as the difference between SBP and DBP. Augmentation pressure and the augmentation index (AI), normalized to a heart rate of 75 bpm (AI@75), were determined [23]. Measurements were repeated if necessary, and all were performed by one skilled examiner for consistency. The examination was conducted by a single skilled technician who was blinded to the details of the study. All test results were reviewed by a single expert, Professor Hack-Lyoung Kim.
Carotid Ultrasonography
The Vivid E95 ultrasound machine (GE Healthcare, Horten, Norway) with a 10-MHz linear transducer was operated by an experienced sonographer for carotid artery assessment. Patients lay with their heads extended and slightly rotated away from the examined artery. CIMT was automatically measured using the machine’s software, focusing on the thickest part of the posterior wall of the common carotid artery, 1 cm below the carotid bulb. Both carotid arteries were measured, and the average value was calculated [24]. A CIMT over 0.9 mm was clinically significant. The presence of plaque was assessed in the distal part of the common carotid artery, carotid bulb, and the proximal part of external and internal carotid arteries as captured in the ultrasound images. Carotid plaque presence was noted if the plaque diameter exceeded 1.5 mm or if localized thickening was over 0.5 mm or 50% thicker than the adjacent IMT [25]. The total number and maximum length of carotid plaques were documented. The examination was conducted by a single skilled technician who was blinded to the details of the study. All test results were reviewed by a single expert, Professor Hack-Lyoung Kim.
Statistical Analysis
Data are presented as mean ± standard deviation or n (%). Pearson’s correlation analysis evaluated relationships between CIMT, carotid plaques, baPWV, and CBP parameters. Multiple linear regression explored the independent relationship between baPWV and CIMT, adjusting for age. The Student’s t test and chi-square test compared clinical characteristics and CBP parameters. ROC curve analysis determined the baPWV cut-off for predicting carotid plaque presence, followed by multiple binary logistic regression. Significant variables in univariate comparisons were adjusted in multivariable analysis. ANOVA assessed the relationship between baPWV and the number of carotid plaques. Statistical significance was set at p < 0.05. Analyses were performed using SPSS version 25.0 (IBM Corp., Armonk, NY, USA).
Results
Clinical Characteristics of Study Patients
Clinical characteristics of the study patients (n = 142) are shown in Table 1. The mean age was 69.1 ± 10.6 years, and 43% were female. The proportions of patients with hypertension, diabetes mellitus, dyslipidemia, obesity, and current cigarette smoking were 66.9%, 35.2%, 52.8%, 64.1%, and 19.0%, respectively. Approximately half of the patients (45.8%) had a history of coronary heart disease, and 3.5% had a history of ischemic stroke. The major blood test results were within the normal range. Anti-platelets, calcium channel blockers, β-blockers, renin-angiotensin system blockers, and statins were taken by 59.2%, 43.7%, 40.1%, 53.5%, and 77.5% of patients, respectively.
Clinical characteristics of study patients
Characteristics . | Value (n = 142) . |
---|---|
Age, years | 69.1±10.6 |
Female sex | 61 (43.0) |
Height, cm | 159±9 |
Weight, kg | 66.5±11.4 |
Body mass index, kg/m2 | 26.2±3.4 |
Systolic blood pressure, mm Hg | 132±14 |
Diastolic blood pressure, mm Hg | 77±10 |
Cardiovascular risk factors | |
Hypertension | 95 (66.9) |
Diabetes mellitus | 50 (35.2) |
Dyslipidemia | 75 (52.8) |
Obesity, body mass index ≥25 kg/m2 | 91 (64.1) |
Current cigarette smoking | 27 (19.0) |
Coronary artery disease | 65 (45.8) |
Ischemic stroke | 5 (3.5) |
Major laboratory findings | |
White blood cell count, per microliter | 6,637±956 |
Hemoglobin, g/dL | 13.6±1.5 |
Fasting glucose, mg/dL | 114±33 |
Glycated hemoglobin, % | 6.28±0.95 |
Total cholesterol, mg/dL | 156±38 |
Low-density lipoprotein cholesterol, mg/dL | 84±31 |
High-density lipoprotein cholesterol, mg/dL | 51.0±13.8 |
Triglyceride, mg/dL | 141±76 |
Estimated glomerular filtration rate, mL/min/1.73 m2 | 78.5±20.3 |
C-reactive protein, mg/dL | 0.30±1.14 |
Concomitant medications | |
Anti-platelets | 84 (59.2) |
Calcium channel blockers | 62 (43.7) |
Beta-blockers | 57 (40.1) |
Renin-angiotensin system blockers | 76 (53.5) |
Statins | 110 (77.5) |
Characteristics . | Value (n = 142) . |
---|---|
Age, years | 69.1±10.6 |
Female sex | 61 (43.0) |
Height, cm | 159±9 |
Weight, kg | 66.5±11.4 |
Body mass index, kg/m2 | 26.2±3.4 |
Systolic blood pressure, mm Hg | 132±14 |
Diastolic blood pressure, mm Hg | 77±10 |
Cardiovascular risk factors | |
Hypertension | 95 (66.9) |
Diabetes mellitus | 50 (35.2) |
Dyslipidemia | 75 (52.8) |
Obesity, body mass index ≥25 kg/m2 | 91 (64.1) |
Current cigarette smoking | 27 (19.0) |
Coronary artery disease | 65 (45.8) |
Ischemic stroke | 5 (3.5) |
Major laboratory findings | |
White blood cell count, per microliter | 6,637±956 |
Hemoglobin, g/dL | 13.6±1.5 |
Fasting glucose, mg/dL | 114±33 |
Glycated hemoglobin, % | 6.28±0.95 |
Total cholesterol, mg/dL | 156±38 |
Low-density lipoprotein cholesterol, mg/dL | 84±31 |
High-density lipoprotein cholesterol, mg/dL | 51.0±13.8 |
Triglyceride, mg/dL | 141±76 |
Estimated glomerular filtration rate, mL/min/1.73 m2 | 78.5±20.3 |
C-reactive protein, mg/dL | 0.30±1.14 |
Concomitant medications | |
Anti-platelets | 84 (59.2) |
Calcium channel blockers | 62 (43.7) |
Beta-blockers | 57 (40.1) |
Renin-angiotensin system blockers | 76 (53.5) |
Statins | 110 (77.5) |
Numbers are expressed as mean ± standard deviation or n (%).
Results of baPWV, CBP Measurements, and Carotid Ultrasound
The results of the baPWV, CBP measurements, and carotid ultrasound are presented in Table 2. The mean baPWV was 1,732 ± 308 cm/s. The mean values of central SBP, PP, and augmentation AI@75 were 131 ± 17 mm Hg, 72.4 ± 12.8 mm Hg, and 77.6 ± 13.4%, respectively. The mean CIMT was 0.78 ± 0.16 mm, and 19% of patients had a CIMT greater than 0.9 mm. More than half of the patients (54.9%) had at least one carotid plaque. Twenty patients (14.1%) had three or more carotid plaques. The mean maximal thickness of the carotid plaque was 2.16 ± 0.86 mm.
Results of baPWV, CBP measurements, and carotid ultrasound
Variable . | Value (n = 142) . |
---|---|
baPWV, cm/s | 1,732±308 |
SBP2, mm Hg | 116±16 |
Central SBP, mm Hg | 131±17 |
Central DBP, mm Hg | 71.5±11.4 |
Central PP, mm Hg | 72.4±12.8 |
Central AI@75, % | 77.6±13.4 |
Carotid IMT, mm | 0.78±0.16 |
Carotid IMT >0.9 mm | 27 (19.0) |
Presence of carotid plaque, yes | 78 (54.9) |
Carotid plaque, n (%) | 1.02±1.16 |
0 | 64 (45.1) |
1 | 36 (25.4) |
2 | 22 (15.5) |
3 | 15 (10.6) |
4 | 5 (3.5) |
Maximal thickness of carotid plaque, mm | 2.16±0.86 |
Variable . | Value (n = 142) . |
---|---|
baPWV, cm/s | 1,732±308 |
SBP2, mm Hg | 116±16 |
Central SBP, mm Hg | 131±17 |
Central DBP, mm Hg | 71.5±11.4 |
Central PP, mm Hg | 72.4±12.8 |
Central AI@75, % | 77.6±13.4 |
Carotid IMT, mm | 0.78±0.16 |
Carotid IMT >0.9 mm | 27 (19.0) |
Presence of carotid plaque, yes | 78 (54.9) |
Carotid plaque, n (%) | 1.02±1.16 |
0 | 64 (45.1) |
1 | 36 (25.4) |
2 | 22 (15.5) |
3 | 15 (10.6) |
4 | 5 (3.5) |
Maximal thickness of carotid plaque, mm | 2.16±0.86 |
Numbers are expressed as mean ± standard deviation or n (%). baPWV, brachial-ankle pulse wave velocity; CBP, central blood pressure; SBP, systolic blood pressure; DBP, diastolic blood pressure; PP, pulse pressure; AI, augmentation index; AI@75, augmentation index adjusted for 75 beats/minute; IMT, intima-media thickness.
Associations of Measurements with CIMT
Simple linear correlations of baPWV and CBP measurements with CIMT are presented in Table 3. Among the various measurements, only baPWV showed a significant correlation with CIMT (r = 0.272; p = 0.001). None of the CBP parameters were correlated with CIMT (p > 0.05 for each). In multiple linear regression analysis, baPWV was found to have no significant association with CIMT after controlling for the confounding effect of age (p = 0.264) (Table 4).
Simple linear correlations between measurements and CIMT
Measurement . | r . | p value . |
---|---|---|
baPWV | 0.272 | 0.001 |
SBP2 | 0.161 | 0.056 |
Central SBP | 0.161 | 0.055 |
Central DBP | −0.141 | 0.095 |
Central PP | −0.128 | 0.128 |
Central AI@75 | 0.120 | 0.154 |
Measurement . | r . | p value . |
---|---|---|
baPWV | 0.272 | 0.001 |
SBP2 | 0.161 | 0.056 |
Central SBP | 0.161 | 0.055 |
Central DBP | −0.141 | 0.095 |
Central PP | −0.128 | 0.128 |
Central AI@75 | 0.120 | 0.154 |
baPWV, brachial-ankle pulse wave velocity; CBP, central blood pressure; SBP, systolic blood pressure; DBP, diastolic blood pressure; PP, pulse pressure; AI, augmentation index; AI@75, augmentation index adjusted for 75 beats/minute; CIMT, carotid intima-media thickness.
Multiple linear regression analysis demonstrating an association between baPWV and CIMT, controlling for the confounding effect of age
Variable . | β . | t . | p value . |
---|---|---|---|
Age | 0.418 | 5.026 | < 0.001 |
baPWV | 0.093 | 1.121 | 0.264 |
Variable . | β . | t . | p value . |
---|---|---|---|
Age | 0.418 | 5.026 | < 0.001 |
baPWV | 0.093 | 1.121 | 0.264 |
baPWV, brachial-ankle pulse wave velocity; CIMT, carotid intima-media thickness.
Associations of Measurements with Carotid Plaque
Among study patients, 78 (54.9%) had at least one carotid plaque. Differences of clinical characteristics, baPWV and CBP measurements according to the presence of carotid plaque are presented in Table 5. Patients with carotid plaques were older (71.8 ± 9.3 vs. 65.8 ± 11.2 years; p = 0.001) and more of them had a history of CAD (55.1% vs. 34.4%; p = 0.014) compared to those without carotid plaques. Anti-platelet (67.9% vs. 48.4%; p = 0.019) and RAS blocker (62.8% vs. 42.2%; p = 0.014) were more frequently prescribed to patients with carotid plaque than to those without. baPWV was significantly higher in patients with carotid plaques compared to those without (1,808 ± 285 vs. 1,639 ± 312 cm/s; p = 0.001). All CBP measurements including SBP2, SBP, DBP, PP, and AI@75 were not different between the two groups (p > 0.05 for each). ROC curve analysis showed that cut-off value of baPWV predicting the presence of carotid plaque was 1,656 cm/s with a sensitivity of 70.5% and specificity of 64.1% (area under curve, 0.676; p < 0.001) (Fig. 2). Using this cut-off value, multivariable binary logistic regression analysis was performed, and the result showed that higher baPWV (≥1,656 cm/s) was significantly associated with the presence of carotid plaque, even after controlling for potential confounders (odds ratio, 3.66; 95% confidence interval, 1.65–8.12; p = 0.001) (Table 6). As the number of carotid plaques increased, there was a linear increase in baPWV (p < 0.001) (Fig. 3).
Differences of clinical characteristics and measurements according to the presence of carotid plaque
Measurement . | Plaque (+) (n = 78) . | Plaque (−) (n = 64) . | p value . |
---|---|---|---|
Age, years | 71.8±9.3 | 65.8±11.2 | 0.001 |
Female sex | 34 (43.6) | 27 (42.2) | 0.867 |
Height, cm | 158±9 | 160±9 | 0.197 |
Weight, kg | 65.2±11.9 | 68.0±10.7 | 0.154 |
BMI, kg/m2 | 26.0±3.5 | 26.5±3.3 | 0.415 |
Brachial SBP, mm Hg | 134±15 | 130±12 | 0.104 |
Brachial DBP, mm Hg | 76.6±9.4 | 77.7±11.4 | 0.540 |
Cardiovascular risk factors | |||
Hypertension | 55 (70.5) | 40 (62.5) | 0.313 |
Diabetes mellitus | 30 (38.5) | 20 (31.2) | 0.371 |
Dyslipidemia | 42 (53.8) | 33 (51.6) | 0.786 |
Obesity, BMI ≥25 kg/m2 | 48 (61.5) | 43 (67.2) | 0.485 |
Cigarette smoking | 14 (17.9) | 13 (20.3) | 0.721 |
Coronary heart disease | 43 (55.1) | 22 (34.4) | 0.014 |
Ischemic stroke | 5 (6.4) | 0 | 0.064 |
Major laboratory findings | |||
WBC, per microliter | 6,811±2,094 | 6,418±1,615 | 0.229 |
Hemoglobin, g/dL | 13.6±1.5 | 13.5±1.4 | 0.785 |
Fasting glucose, mg/dL | 116±35 | 112±30 | 0.539 |
Glycated hemoglobin, % | 6.27±1.01 | 6.29±0.87 | 0.921 |
Total cholesterol, mg/dL | 152±37 | 160±39 | 0.215 |
LDL cholesterol, mg/dL | 81.4±29.0 | 88.4±33.7 | 0.207 |
HDL cholesterol, mg/dL | 51.0±15.0 | 50.8±12.3 | 0.930 |
Triglyceride, mg/dL | 141±87 | 140±61 | 0.911 |
eGFR, mL/min/1.73 m2 | 76.5±19.0 | 81.0±21.6 | 0.196 |
C-reactive protein, mg/dL | 0.37±1.37 | 0.22±0.78 | 0.451 |
Concomitant medications | |||
Antiplatelets | 53 (67.9) | 31 (48.4) | 0.019 |
Calcium channel blockers | 37 (47.4) | 25 (39.1) | 0.317 |
Beta-blockers | 33 (42.3) | 24 (37.5) | 0.561 |
RAS blockers | 49 (62.8) | 27 (42.2) | 0.014 |
Statins | 64 (82.1) | 46 (71.9) | 0.149 |
Measurements | |||
baPWV, cm/s | 1,808±285 | 1,639±312 | 0.001 |
SBP2, mm Hg | 118±17 | 114±15 | 0.147 |
Central SBP, mm Hg | 133±18 | 129±16 | 0.143 |
Central DBP, mm Hg | 70.1±10.1 | 73.1±12.6 | 0.119 |
Central PP, mm Hg | 71.1±12.7 | 74.1±13.0 | 0.169 |
Central AI@75, % | 78.7±12.7 | 74.1±13.0 | 0.269 |
Measurement . | Plaque (+) (n = 78) . | Plaque (−) (n = 64) . | p value . |
---|---|---|---|
Age, years | 71.8±9.3 | 65.8±11.2 | 0.001 |
Female sex | 34 (43.6) | 27 (42.2) | 0.867 |
Height, cm | 158±9 | 160±9 | 0.197 |
Weight, kg | 65.2±11.9 | 68.0±10.7 | 0.154 |
BMI, kg/m2 | 26.0±3.5 | 26.5±3.3 | 0.415 |
Brachial SBP, mm Hg | 134±15 | 130±12 | 0.104 |
Brachial DBP, mm Hg | 76.6±9.4 | 77.7±11.4 | 0.540 |
Cardiovascular risk factors | |||
Hypertension | 55 (70.5) | 40 (62.5) | 0.313 |
Diabetes mellitus | 30 (38.5) | 20 (31.2) | 0.371 |
Dyslipidemia | 42 (53.8) | 33 (51.6) | 0.786 |
Obesity, BMI ≥25 kg/m2 | 48 (61.5) | 43 (67.2) | 0.485 |
Cigarette smoking | 14 (17.9) | 13 (20.3) | 0.721 |
Coronary heart disease | 43 (55.1) | 22 (34.4) | 0.014 |
Ischemic stroke | 5 (6.4) | 0 | 0.064 |
Major laboratory findings | |||
WBC, per microliter | 6,811±2,094 | 6,418±1,615 | 0.229 |
Hemoglobin, g/dL | 13.6±1.5 | 13.5±1.4 | 0.785 |
Fasting glucose, mg/dL | 116±35 | 112±30 | 0.539 |
Glycated hemoglobin, % | 6.27±1.01 | 6.29±0.87 | 0.921 |
Total cholesterol, mg/dL | 152±37 | 160±39 | 0.215 |
LDL cholesterol, mg/dL | 81.4±29.0 | 88.4±33.7 | 0.207 |
HDL cholesterol, mg/dL | 51.0±15.0 | 50.8±12.3 | 0.930 |
Triglyceride, mg/dL | 141±87 | 140±61 | 0.911 |
eGFR, mL/min/1.73 m2 | 76.5±19.0 | 81.0±21.6 | 0.196 |
C-reactive protein, mg/dL | 0.37±1.37 | 0.22±0.78 | 0.451 |
Concomitant medications | |||
Antiplatelets | 53 (67.9) | 31 (48.4) | 0.019 |
Calcium channel blockers | 37 (47.4) | 25 (39.1) | 0.317 |
Beta-blockers | 33 (42.3) | 24 (37.5) | 0.561 |
RAS blockers | 49 (62.8) | 27 (42.2) | 0.014 |
Statins | 64 (82.1) | 46 (71.9) | 0.149 |
Measurements | |||
baPWV, cm/s | 1,808±285 | 1,639±312 | 0.001 |
SBP2, mm Hg | 118±17 | 114±15 | 0.147 |
Central SBP, mm Hg | 133±18 | 129±16 | 0.143 |
Central DBP, mm Hg | 70.1±10.1 | 73.1±12.6 | 0.119 |
Central PP, mm Hg | 71.1±12.7 | 74.1±13.0 | 0.169 |
Central AI@75, % | 78.7±12.7 | 74.1±13.0 | 0.269 |
baPWV, brachial-ankle pulse wave velocity; BMI, body mass index; SBP, systolic blood pressure; DBP, diastolic blood pressure; WBC, white blood cell; LDL, low-density lipoprotein; HDL, high-density lipoprotein; eGFR, estimated glomerular filtration rate; RAS, renin-angiotensin system blocker; PP, pulse pressure; AI@75, augmentation index adjusted for 75 beats/minute.
Receiver operating characteristic curve analysis demonstrated the cut-off value of baPWV for predicting the presence of carotid plaque. baPWV, brachial-ankle pulse wave velocity.
Receiver operating characteristic curve analysis demonstrated the cut-off value of baPWV for predicting the presence of carotid plaque. baPWV, brachial-ankle pulse wave velocity.
Multivariable binary logistic regression analysis showing an independent risk factor for the presence of carotid plaque
Variable . | OR (95% CI) . | p value . |
---|---|---|
Age ≥65 years | 1.65 (0.72–3.79) | 0.236 |
Coronary artery disease, yes | 1.29 (0.53–3.14) | 0.563 |
Antiplatelets, yes | 1.60 (0.67–3.83) | 0.285 |
Renin angiotensin system blockers, yes | 2.43 (1.14–5.22) | 0.022 |
baPWV ≥1,656 cm/s | 3.66 (1.65–8.12) | 0.001 |
Variable . | OR (95% CI) . | p value . |
---|---|---|
Age ≥65 years | 1.65 (0.72–3.79) | 0.236 |
Coronary artery disease, yes | 1.29 (0.53–3.14) | 0.563 |
Antiplatelets, yes | 1.60 (0.67–3.83) | 0.285 |
Renin angiotensin system blockers, yes | 2.43 (1.14–5.22) | 0.022 |
baPWV ≥1,656 cm/s | 3.66 (1.65–8.12) | 0.001 |
OR, odds ratio; CI, confidence interval; baPWV, brachial-ankle pulse wave velocity.
Associations between the number of carotid plaques and baPWV. baPWV, brachial-ankle pulse wave velocity.
Associations between the number of carotid plaques and baPWV. baPWV, brachial-ankle pulse wave velocity.
Discussion
This cross-sectional study investigated the associations of baPWV and CBP parameters with CIMT and carotid plaque in patients at high coronary risk. It found that baPWV was associated with the presence and number of carotid plaques but not with CIMT. Various CBP measurements, including SBP2, SBP, DBP, PP, and AI@75, were not associated with CIMT or carotid plaques. While several previous studies have shown associations between carotid arteriosclerosis and arterial stiffness or CBP indices, most have focused on the relationship between two specific indices. The most noteworthy strength of our study is that it systematically examined the associations of both baPWV and CBP indicators with CIMT, and carotid plaque in the same individuals.
Numerous studies have consistently demonstrated a significant correlation between arterial stiffness measurements and CIMT or carotid plaque presence. These studies, conducted in diverse populations, have employed various metrics of arterial stiffness, such as baPWV and cfPWV, to establish this association [8]. One notable study, involving 1,583 Japanese individuals attending health checkups, highlighted the predictive value of baPWV in identifying increased CIMT. This study found that a baPWV value equal to or greater than 1,400 cm/s was a significant predictor of an increased CIMT (CIMT ≥1.0 mm), showcasing an odds ratio (OR) of 2.22, which was statistically significant (p < 0.01) [26]. Similarly, a study conducted in Turkey with 312 hypertensive patients revealed a substantial relationship between CIMT and cfPWV. The research indicated that for each 1 mm increase in CIMT, there was a corresponding 50% increase in cfPWV [27]. As a result of similar studies, the association between cfPWV and CIMT was also identified in diabetic patients [28]. In a Korean study involving 773 participants undergoing health checkups, a significant association was observed between higher baPWV values (particularly those in the highest quartile) and the presence of carotid plaque. The odds ratio for this association was 1.59, although the statistical significance was marginal (p = 0.08) [29]. Furthermore, a prospective study by Yang et al. [30] involving 738 Chinese individuals from the general population yielded insightful results. This study reported that individuals with a baseline baPWV of 1,400 cm/s or more had approximately double the risk of developing new carotid plaques when compared to those with lower baPWV values (below 1,400 cm/s). These studies collectively reinforce the idea that arterial stiffness, as measured by baPWV and cfPWV, is a significant predictor of changes in the carotid artery, such as increased CIMT and the presence of carotid plaque. However, in our study, baPWV was significantly correlated with the presence and extent of carotid plaque, but not with CIMT. The individuals in our study were at higher cardiovascular risk compared to those in other studies, which may account for some of these differences. Additionally, variations in race, arterial stiffness, or CBP measurement methods may have contributed to the discrepancies observed between our findings and previous research. These results suggest that the relationship between baPWV, CIMT, and carotid plaque might vary across populations and risk profiles, underscoring the need for further research to clarify these associations, particularly in high-risk groups.
There are several studies showing the association between indices of CBP and carotid atherosclerosis. In a focused study comprising 228 patients with type 2 diabetes, a significant association was observed between central AI, estimated through radial artery applanation tonometry, and CIMT [31]. Parallel findings were reported in a cohort of 67 patients suffering from chronic kidney disease. Here, both central PP and central SBP demonstrated significant correlations with CIMT. Notably, in the same study, central PP was also associated with the presence of carotid plaques [32]. Cheng et al. [33] conducted a study within a community population in China, further elaborating on these associations. Their research highlighted that central SBP exhibited a more pronounced association with CIMT. In contrast, central PP demonstrated a stronger link to the presence of carotid plaques. Contrary to the findings of other studies, none of the CBP measurements in our study demonstrated a significant correlation with the presence of carotid plaques. It is important to consider that the characteristics of the patients analyzed in each study differ, as do the research methodologies employed. These variations could account for the discrepancies in results. However, this suggests a need for further research to explore the relationship between CBP measurements and indicators of carotid atherosclerosis more thoroughly.
Our study provided significant evidence that baPWV is closely associated with both the presence and extent of carotid plaques. This finding suggests a mechanistic link between increased arterial stiffness and the promotion of plaque formation in the carotid artery. As arterial stiffness escalates, both systolic pressure and PP tend to rise, exerting additional stress on the carotid artery wall [34]. This stress may contribute to the development and progression of atherosclerotic plaques. Additionally, the risk factors associated with increased arterial stiffness are notably similar to those implicated in the formation of carotid artery plaque. These include hypertension, hyperlipidemia, diabetes, chronic inflammation, oxidative stress, and endothelial dysfunction [8]. The convergence of these risk factors highlights a shared pathophysiological pathway that may underlie both arterial stiffening and plaque development. In terms of diagnostic implications, our study indicates that CBP may reflect the vascular state over a relatively short period and can be subject to fluctuations due to various factors. Consequently, CBP might be more variable and potentially reversible compared to arterial stiffness. On the other hand, arterial stiffness, as indicated by measurements like baPWV, appears to be a more stable marker, reflecting the long-term condition of blood vessels. This long-term perspective provided by arterial stiffness measurements may explain their stronger correlation with the presence and extent of carotid artery plaque.
The clinical relevance of carotid plaques, rather than CIMT, has gained increased emphasis in recent times due to its stronger association with cardiovascular disease [4]. In light of this, the significance of baPWV as a diagnostic tool should be reasserted, especially given its notable correlation with both the presence and extent of carotid plaques. Our research highlights the pivotal role of arterial stiffness, as measured by baPWV, in evaluating cardiovascular risk. This is particularly pertinent in the realm of carotid atherosclerosis, where the early detection and management of arterial changes can profoundly influence the course of the disease. By focusing on baPWV, clinicians can gain valuable insights into the state of arterial health, allowing for timely interventions that could significantly mitigate the risk of cardiovascular events. Thus, our findings advocate for the integration of baPWV measurements into standard cardiovascular risk assessments, emphasizing its utility in identifying and managing individuals at risk of carotid atherosclerosis and related complications.
Of note, baPWV is simpler to measure than cfPWV, which enhances its practicality for mass screening purposes, especially when applied to large populations [35]. Our study results showed that, along with a higher baPWV, the use of RAS blockers was associated with the presence of carotid plaque. However, this finding likely reflects that high-risk patients with pre-existing plaque were more frequently prescribed RAS blockers, rather than suggesting that RAS blockers contributed to plaque formation.
Our study has several limitations. First, it is a cross-sectional study, which means that a causal relationship between baPWV and carotid plaque cannot be definitively established. Second, due to the relatively small sample size, statistical significance may not have been achieved for some variables. Third, although cfPWV is considered the gold standard non-invasive measure of arterial stiffness [36], our study utilized baPWV. While baPWV is simpler to measure than cfPWV, its usefulness has been validated in numerous clinical studies [8, 35, 37]. Lastly, our study population was limited to high-risk Korean patients; therefore, caution should be exercised when applying our results to other populations or ethnic groups.
Conclusions
In Korean patients at high coronary risk, baPWV was positively associated with both the presence and extent of carotid plaques. This finding suggests that baPWV may serve as a useful marker for identifying carotid plaque, providing additional evidence of its utility in risk stratification.
Statement of Ethics
Written informed consent was obtained from all participants prior to the study. The study followed the Declaration of Helsinki and was approved by Boramae Medical Center IRB (IRB number: 20-2019-103).
Conflict of Interest Statement
The authors declare that there are no conflicts of interest associated with this manuscript.
Funding Sources
The authors declare that this study received no financial support.
Author Contributions
H.-L.K. contributed to conceptualization, resources, investigation, formal analysis, and drafting and editing of the manuscript and, as the corresponding author, had full access to all the data in the study and was responsible for the decision to submit this manuscript for publication. S.K., H.S.J. and W.-H.L. contributed to methodology, resources, and investigation. J.-B.S., S.-H.K., J.-H.Z., and M.-A.K. contributed to resources and data curation. All the authors discussed the results, commented on the manuscript, and read and approved the final manuscript.
Data Availability Statement
The data that support the findings of this study are not publicly available due to the concern of compromising the privacy of research participants but are available from Hack-Lyoung Kim (Boramae Medical Center, [email protected]) upon reasonable request.