Abstract
This study aims to explore the risk factors for carotid plaque (CP) and carotid common artery intima-media thickening (CCAIMT) and clarify the relationship between the risk factors with the number of CPs and the side of CCAIMT in a high-stroke-risk population in Qujing, Yunnan, China. Carotid ultrasonography was performed in 430 participants with high stroke risk, who were divided into different groups according to their ultrasound results. The risk factors and blood biochemical indices were recorded for assessment. The prevalence rates of CP and CCAIMT were 88.1% and 70.5%, respectively. Multivariate logistic regression analysis identified age and lack of physical exercise as risk factors of CP. Compared to participants without CP, participants who performed little physical exercise were prone to have one CP, while participants with risk factors for smoking, older age, and physical inactivity were more likely to have several CPs. Risk factors for CCAIMT were older age, male, and the levels of low density lipoprotein cholesterol. Risk factors for left CCAIMT included a history of hyperlipidemia and low density lipoprotein cholesterol, while male sex was the sole risk factor for right CCAIMT. Finally, male sex and advanced age were identified as risk factors for dual CCAIMT. The research reveals the risk factors for CP and CCAIMT, also clarifies the relationship between the risk factors, CP numbers, and the side of CCAIMT.
Keywords: carotid common artery intima, carotid plaque, high, media thickening, risk factors, risk population, stroke
1. Introduction
Stroke is currently the second leading cause of death worldwide, and the leading cause of death in China.[1] In China, the annual absolute medical cost of stroke in 2013 reaching $7.77 billion.[2] In addition to the high disability and mortality rates associated with stroke, it also exerts a significant and negative influence on society.[3]
Carotid atherosclerotic disease is a cause of ischemic stroke which has been associated with a high risk of recurrent stroke.[4] Atherosclerotic diseases are characterized by plaque formation within the arterial wall. Unstable atherosclerotic plaques in the carotid artery can cause many serious cerebrovascular ischemic events, including ischemic stroke, transient ischemic attack (TIA), and amaurosis fugax. Carotid artery stenosis accounts for about 80% of ischemic stroke.[5] Further, carotid atherosclerosis is a well-established risk factor for ischemic stroke, contributing to up to 10% to 20% of strokes or transient ischemic attacks.[6] Up to 25% of all ischemic stroke events are caused by thromboembolisms arising from the carotid arteries.[7] As such, atherosclerotic plaques in the carotid artery represent an important disease burden.[5] Plaques in the internal carotid artery are most frequently involved in stroke pathogenesis.[8] In brief, carotid atherosclerosis may result in stroke through the rupture of a carotid atherosclerotic plaque, ultimately leading to the embolization of plaque material and thrombi into the distal arteries.[5]
Carotid ultrasonography is the most commonly used rapid, noninvasive, and repeatable imaging method to evaluate carotid atherosclerosis and underlying cardiovascular risk.[9] Two indices have been used to evaluate carotid atherosclerosis: measurement of the carotid intima-media thickness and assessment of carotid arterial plaques.[9] B-mode ultrasound images are used to evaluate plaque echoes.[8] One study found that, regardless of stenosis, patients with echogenic plaques had a stroke risk of up to 13%, which was higher than that in patients with severe stenosis. B-mode carotid ultrasound has also been found to have a high specificity in identifying plaques.[10]
Many previous studies have shown that atherosclerosis is strongly associated with many risk factors, including hypertension, smoking, dyslipidemia, diabetes, obesity, age, and family history.[11] Both primary and secondary prevention of cardiovascular disease (CVD) are based on the treatment of atherosclerosis through risk factor intervention.[12] Monitoring patients at an elevated risk of stroke is critical for developing better prevention strategies. The heavy disease burden associated with carotid plaques needs effective preventive strategies.[13]
2. Methods
2.1. Study design and population
This study was approved by the Clinical Experimentation Committee of Humans of the Second People’s Hospital of Qujing (2022-006-01). All participants signed an informed consent form before enrollment. This study was performed in a hospitalized population at the Department of Neurology of the Second People’s Hospital of Qujing between April and December 2022. After primary screening of the patients’ demographic information, previous disease history, family history, and other cardiovascular and cerebrovascular disease risk factors, 430 patients (age range 37–91, 251 men, 179 women) with at least three risk factors or a previous history of TIA or stroke were enrolled and underwent carotid ultrasonography examination.[14] The risk factors were as follows: hypertension; atrial fibrillation or valvulopathy; tobacco use; hyperlipidemia; diabetes; lack of physical exercise; overweight or obesity; and family history of stroke.
2.2. Survey procedure
In the entire hospitalized population, medical history was investigated on the first day, including a detailed risk-factor survey. On subsequent days, patients underwent blood examination and other inspections. Fasting blood samples were collected by nurses in the Department of Neurology, analyzed by the clinical laboratory. Carotid ultrasound examinations were performed by experienced technicians in the Department of Ultrasound.
2.3. Physical examinations
Blood pressure, height, weight, and pulse rate were measured. Body mass index (BMI) was calculated as the weight (kg) divided by the height square (m2). Serum fasting blood glucose, total cholesterol, total triglyceride, high density lipoprotein cholesterol, and low density lipoprotein cholesterol (LDL-C) levels were measured and analyzed at the Clinical Laboratory of the Second People’s Hospital of Qujing. Carotid ultrasonography and 12-lead echocardiography were also performed.
2.4. The survey for risk factors
Surveys to assess risk factors were conducted by trained physicians through consultation. Data need to be collected has been listed in our previous study.[11] The criteria used to assess these risk factors are listed in Table 1.[15,16] The use of antihypertensive, lipid-lowering, and glucose-lowering medications within the two weeks prior to the survey were also self-reported.
Table 1.
The criteria of risk factors
| Risk factors | Criteria |
|---|---|
| Hypertension | Systolic BP (SBP) ≥ 140mm Hg or diastolic BP (DBP) ≥ 90 mm Hg or taking medication for hypertension |
| Hyperlipidemia | TC ≥ 6.22 mmol/L, TG ≥ 2.26 mmol/L, LDL-C ≥ 4.14 mmol/L, or HDL-C＜1.04 mmol/L15 |
| Diabetes | FBG ≥ 7.0 mmol/L or taking medication for diabetes |
| Overweight | BMI of 24.0–27.9 kg/m2[15] |
| Obesity | BMI ≥ 28.0 kg/m2[15] |
| Tobacco use | ≥1 cigarette per day for ≥ 1 year |
| Alcohol use | Drinking alcohol ≥ 1 time per week for 1 year |
| Physical exercise | ≥3 times per week and ＞30mins each time or heavy physical labor |
2.5. Ultrasonography measurements
All ultrasound examinations were performed by practiced technicians. The patients were examined in the supine position using B-mode ultrasonography (PHILIPS EPIQ CVx and Canon Aplio i800). The definitions of plaques and IMT have been listed in our previous research.[11]
2.6. Statistical analysis
Statistical analyses were conducted using SPSS software 29.0. Continuous data are summarized as mean ± standard deviations, while categorical data are showed as counts and percentages. The association between risk factors and ultrasound are showed as odds ratios, 95% confidence intervals (CI). Student t test, analysis of variance were applied to compare non-paired data. The chi-squared test was further used to compare categorical variables. Binary and multinomial logistic regression analyses were performed to analyze the association between positive carotid ultrasound results and risk factors. Patients were divided into different subgroups for the multinomial logistic regression analysis. Risk factors with P < .1 in the univariate analyses and had clinical significance were selected as covariates in the multivariate models. P < .05 in the two-sided tests were considered significant.
3. Results
A total of 430 residents, including 251 men (58.4 %) and 179 women (41.6 %), were enrolled in this study. The mean age of the participants was 68.3 ± 10.7 years, ranging from 37 to 91 years.
In the initial stage of the analysis, all patients were assigned to different groups according to presence of plaque. Carotid plaque (CPs) were found 58.0% and 42.0% of men and women, respectively. The mean age of the CP group was 69.1 ± 10.2, and the mean age of the no (N)-CP group was 62.2 ± 12.1. The percentage of the participants who lacked physical exercise was significantly higher in the CP group than in the N-CP group (P < .05; Table 2). Binary logistic regression analysis identified age and lack of physical exercise as independent risk factors of CP (Table 3).
Table 2.
Demographic characteristics of the participants, based on the presence of CP
| CP | N-CP | |
|---|---|---|
| Total, n (%) | 379 (88.1) | 51 (11.9) |
| Men (%) | 220 (58.0) | 31 (60.8) |
| Women (%) | 159 (42.0) | 20 (39.2) |
| Age | 69.1 ± 10.2 | 62.2 ± 12.1 |
| HT (%) | 277 (73.1) | 34 (66.7) |
| DM (%) | 121 (31.9) | 13 (25.5) |
| AF (%) | 14 (3.7) | 2 (3.9) |
| HLP (%) | 190 (50.1) | 31 (60.8) |
| Smoke (%) | 119 (31.4) | 14 (27.5) |
| Stroke F (%) | 19 (5.0) | 3 (5.9) |
| Obesity (%) | 188 (49.6) | 27 (52.9) |
| PE (%) | 349 (92.1)* | 39 (76.5) |
| TIA (%) | 206 (54.4) | 22 (43.1) |
| BMI (kg/m2) | 24.3 ± 3.5 | 24.5 ± 3.1 |
| FBG (mmol/L) | 6.8 ± 3.3 | 6.1 ± 2.2 |
| TC (mmol/L) | 5.0 ± 1.2 | 5.2 ± 1.2 |
| TG (mmol/L) | 2.0 ± 1.7 | 2.0 ± 1.6 |
| HDL (mmol/L) | 1.1 ± 0.3 | 1.1 ± 0.3 |
| LDL (mmol/L) | 2.7 ± 0.8 | 2.9 ± 0.8 |
The P value was determined by the chi-square test, and the Student t test.
AF = atrial fibrillation, BMI = body mass index, DM = diabetes mellitus, FBG = fasting blood glucose, HDL = high density lipoprotein cholesterol, HLP = hyperlipidemia, HT = hypertension, LDL = low density lipoprotein cholesterol, PE = physical exercise, Stroke F = family history of stroke, TC = total cholesterol, TG = total triglyceride, TIA = transient ischemic attack.
P<0.05 vs N-CP group.
Table 3.
The risk factors of CP
| OR | OR (95% CI) | P | |
|---|---|---|---|
| Age | 1.058 | 1.023–1.093 | .001 |
| PE | 3.085 | 1.301–7.600 | .011 |
The P value was determined by the binary logistic regression analysis.
PE = physical exercise.
Subsequently, the subjects were divided by the number of CPs, the characteristics of participants were shown in Table 4. Age, percentage of participants who lacked physical exercise, presence of TIA, and BMI were all found to show significant differences among the three subgroups (all P < .05). Further analysis found risk factors for single CP was lack of physical exercise. Moreover, age, smoking, and lack of physical exercise were identified as risk factors for multiple CPs (Table 5).
Table 4.
Demographic characteristics of the participants, based on the number of CP
| None | Single | Multiple | P | |
|---|---|---|---|---|
| Total, n (%) | 48 (11.2) | 75 (17.4) | 307 (71.4) | – |
| Men (%) | 28 (58.3) | 41 (54.7) | 182 (59.3) | .768 |
| Women (%) | 20 (41.7) | 34 (45.3) | 125 (40.7) | .768 |
| Age | 61.3 ± 11.7 | 64.0 ± 10.0 | 70.5 ± 9.9 | .000 |
| HT (%) | 31 (64.6) | 54 (72.0) | 226 (73.6) | .428 |
| DM (%) | 12 (25.0) | 25 (33.3) | 97 (31.6) | .594 |
| AF (%) | 2 (4.2) | 2 (2.7) | 12 (3.9) | .865 |
| HLP (%) | 30 (62.5) | 38 (50.7) | 153 (49.8) | .204 |
| Smoke (%) | 12 (25.0) | 23 (30.7) | 98 (31.9) | .658 |
| Stroke F (%) | 2 (4.2) | 4 (5.3) | 16 (5.2) | .950 |
| Obesity (%) | 25 (52.1) | 44 (58.7) | 146 (47.6) | .194 |
| PE (%) | 36 (75.0) | 68 (90.7) | 284 (92.5) | .001 |
| TIA (%) | 22 (45.8) | 27 (36.0) | 179 (58.3) | .001 |
| BMI (kg/m2) | 24.5 ± 3.2 | 25.3 ± 3.4 | 24.0 ± 3.5 | .013 |
| FBG (mmol/L) | 6.3 ± 2.3 | 6.1 ± 2.9 | 7.0 ± 3.4 | .059 |
| TC (mmol/L) | 5.3 ± 1.2 | 5.0 ± 1.2 | 5.0 ± 1.3 | .320 |
| TG (mmol/L) | 2.1 ± 1.6 | 1.7 ± 0.9 | 2.1 ± 1.9 | .178 |
| HDL (mmol/L) | 1.1 ± 0.3 | 1.2 ± 0.3 | 1.1 ± 0.3 | .769 |
| LDL (mmol/L) | 3.0 ± 0.8 | 2.8 ± 0.8 | 2.7 ± 0.8 | .169 |
The P value was determined by the chi-square test and the analysis of variance (ANOVA).
AF = atrial fibrillation, BMI = body mass index, DM = diabetes mellitus, FBG = fasting blood glucose, HDL = high density lipoprotein cholesterol, HLP = hyperlipidemia, HT = hypertension, LDL = low density lipoprotein cholesterol, PE = physical exercise, Stroke F = family history of stroke, TC = total cholesterol, TG = total triglyceride, TIA = transient ischemic attack.
Table 5.
Analysis of the association between CP number and risk factors
| OR | OR (95% CI) | P | |
|---|---|---|---|
| Single* | |||
| PE | 4.237 | 1.242–14.451 | .021 |
| Multiple* | |||
| Age | 1.094 | 1.054–1.136 | .000 |
| Smoke | 2.662 | 1.052–6.738 | .039 |
| PE | 3.096 | 1.194–8.031 | .020 |
The P value was determined by the multinomial logistic regression analysis.
PE = physical exercise.
Compared with the N-CP subgroup.
Then, patients were divided into the carotid common artery intima-media thickening (CCAIMT) or No (N)-CCAIMT groups. The incidence of CCAIMT was higher in men (63.4%) than in women (36.6%) (P < .05). The age of the CCAIMT group was higher than that of the N-CCAIMT group (P < .05; Table 6). Binary logistic regression analysis identified male sex, age, and level of LDL cholesterol as risk factors for CCAIMT, with total cholesterol being associated with a lower risk (Table 7).
Table 6.
Demographic characteristics of the participants, based on the presence of CCAIMT
| CCAIMT | N-CCAIMT | |
|---|---|---|
| Total, n (%) | 303 (70.5) | 127 (29.5) |
| Men (%) | 192 (63.4)* | 59 (46.5) |
| Women (%) | 111 (36.6)* | 68 (53.5) |
| Age | 69.1 ± 10.8* | 66.6 ± 10.4 |
| HT (%) | 224 (73.9) | 87 (68.5) |
| DM (%) | 93 (30.7) | 41 (32.3) |
| AF (%) | 11 (3.6) | 5 (3.9) |
| HLP (%) | 157 (51.8) | 64 (50.4) |
| Smoke (%) | 96 (31.7) | 37 (29.1) |
| Stroke F (%) | 15 (5.0) | 7 (5.5) |
| Obesity (%) | 147 (48.5) | 68 (53.5) |
| PE (%) | 275 (90.8) | 113 (89.0) |
| TIA (%) | 166 (54.8) | 62 (48.8) |
| BMI (kg/m2) | 24.1 ± 3.4 | 24.6 ± 3.6 |
| FBG (mmol/L) | 6.7 ± 3.2 | 6.7 ± 3.1 |
| TC (mmol/L) | 4.9 ± 1.2 | 5.1 ± 1.3 |
| TG (mmol/L) | 2.0 ± 1.6 | 2.0 ± 1.9 |
| HDL (mmol/L) | 1.1 ± 0.3 | 1.2 ± 0.3 |
| LDL (mmol/L) | 2.7 ± 0.8 | 2.8 ± 0.8 |
The P value was determined by the chi-square test, and the Student t test.
AF = atrial fibrillation, BMI = body mass index, DM = diabetes mellitus, FBG = fasting blood glucose, HDL = high density lipoprotein cholesterol, HLP = hyperlipidemia, HT = hypertension, LDL = low density lipoprotein cholesterol, PE = physical exercise, Stroke F = family history of stroke, TC = total cholesterol, TG = total triglyceride, TIA = transient ischemic attack.
P<0.05 vs N-CCAIMT group.
Table 7.
The risk factors of CCAIMT
| OR | OR (95% CI) | P | |
|---|---|---|---|
| Sex | 2.539 | 1.410–4.574 | .002 |
| Age | 1.030 | 1.006–1.056 | .016 |
| TC | 0.488 | 0.243–0.981 | .044 |
| LDL | 2.544 | 1.006–6.439 | .049 |
The P value was determined by the binary logistic regression analysis.
LDL = low density lipoprotein cholesterol, TC = total cholesterol.
Finally, Table 8 shows the distribution of the demographic and clinical data of all participants, grouped according to the CCAIMT side. The percentages of different sex, lack of physical exercise, and age were quite different among subgroups (P < .05). Risk factors for left-sided CCAIMT included a history of hyperlipidemia, the level of LDL cholesterol, while lack of physical exercise and the level of total cholesterol were with lower risk. Male sex was a risk factor for right-sided CCAIMT, whereas smoking was with lower risk. Moreover, risk factors for dual-sided CCAIMT were age and male sex (Table 9).
Table 8.
Demographic characteristics of the participants, based on the side of CCAIMT
| None | Left | Right | Dual | P | |
|---|---|---|---|---|---|
| Total, n (%) | 126 (29.3) | 23 (5.3) | 31 (7.2) | 250 (58.1) | – |
| Men (%) | 59 (46.8) | 14 (60.9) | 20 (64.5) | 158 (63.2) | .020 |
| Women (%) | 67 (53.2) | 9 (39.1) | 11 (35.5) | 92 (36.8) | .020 |
| Age | 66.6 ± 10.4 | 65.4 ± 10.5 | 65.6 ± 11.2 | 69.8 ± 10.6 | .008 |
| HT (%) | 86 (68.3) | 15 (65.2) | 21 (67.7) | 189 (75.6) | .349 |
| DM (%) | 40 (31.7) | 6 (26.1) | 9 (29.0) | 79 (31.6) | .944 |
| AF (%) | 5 (4.0) | 2 (8.7) | 0 (0) | 9 (3.6) | .420 |
| HLP (%) | 63 (50.0) | 16 (69.6) | 20 (64.5) | 122 (48.8) | .051 |
| Smoke (%) | 37 (29.4) | 8 (34.8) | 7 (22.6) | 81 (32.7) | .658 |
| Stroke F (%) | 7 (5.6) | 1 (4.3) | 1 (3.2) | 13 (5.2) | .958 |
| Obesity (%) | 68 (54.0) | 10 (43.5) | 19 (61.3) | 118 (47.2) | .280 |
| PE (%) | 112 (88.9) | 17 (73.9) | 24 (77.4) | 235 (94.0) | .000 |
| TIA (%) | 62 (49.2) | 10 (43.5) | 14 (45.2) | 142 (56.8) | .286 |
| BMI (kg/m2) | 24.7 ± 3.7 | 24.0 ± 4.1 | 24.4 ± 2.4 | 24.1 ± 3.4 | .579 |
| FBG (mmol/L) | 6.7 ± 3.1 | 6.6 ± 2.7 | 6.5 ± 3.2 | 6.8 ± 3.3 | .955 |
| TC (mmol/L) | 5.2 ± 1.3 | 4.9 ± 1.5 | 5.2 ± 1.0 | 4.9 ± 1.2 | .253 |
| TG (mmol/L) | 2.0 ± 1.9 | 2.4 ± 2.0 | 2.3 ± 2.2 | 1.9 ± 1.5 | .440 |
| HDL (mmol/L) | 1.2 ± 0.3 | 1.1 ± 0.4 | 1.2 ± 0.3 | 1.1 ± 0.3 | .217 |
| LDL (mmol/L) | 2.8 ± 0.8 | 2.7 ± 1.1 | 2.9 ± 0.6 | 2.7 ± 0.8 | .607 |
The P value was determined by the chi-square test and the analysis of variance (ANOVA).
AF = atrial fibrillation, BMI = body mass index, DM = diabetes mellitus, FBG = fasting blood glucose, HDL = high density lipoprotein cholesterol, HLP = hyperlipidemia, HT = hypertension, LDL = low density lipoprotein cholesterol, PE = physical exercise, Stroke F = family history of stroke, TC = total cholesterol, TG = total triglyceride, TIA = transient ischemic attack.
Table 9.
Analysis of the association between CCAIMT side and risk factors
| OR | OR (95% CI) | P | |
|---|---|---|---|
| Left* | |||
| HLP | 4.314 | 1.115–16.687 | .034 |
| TC | 0.088 | 0.017–0.448 | .003 |
| PE | 0.239 | 0.059–0.972 | .045 |
| LDL | 13.411 | 1.584–113.527 | .017 |
| Right* | |||
| Sex | 3.348 | 1.201–9.332 | .021 |
| Smoke | 0.298 | 0.090–0.980 | .046 |
| Dual* | |||
| Sex | 2.441 | 1.330–4.481 | .004 |
| Age | 1.034 | 1.009–1.061 | .009 |
The P value was determined by the multinomial logistic regression analysis.
HLP = hyperlipidemia, LDL = low density lipoprotein cholesterol, PE = physical exercise, TC = total cholesterol.
Compared with the N-CCAIMT subgroup.
4. Discussion
In this study, we aimed to identify the risk factors for CP and CCAIMT, as well as the association between carotid ultrasound and risk factors in a high-stroke-risk population in Qujing, the second largest city of Yunnan province, China. This study initially enrolled 430 patients, among whom basic statistical analyses identified age and lack of physical exercise as risk factors for CP; male gender, age, level of the LDL cholesterol in this high-stroke-risk population as risk factors for CCAIMT. Further statistical analyses indicated that the risk factors differed according to CP number and CCAIMT side in this population. In a previous study, researchers attempted to determine the differences in the prevalence of classical risk factors that account for the differences in the CVD burden between racial and ethnic groups.[17] Another study demonstrated that racial and ethnic variations exist in the association between classical cardiovascular risk factors and common carotid intima-media thickness in African American individuals.[18] Differences in the association of CVD risk factors with CP and CCAIMT have implications for ethnic- or district- specific primary prevention strategies for CVD. To our knowledge, our study is the first to investigate risk factors for carotid atherosclerosis in a specific population in Yunnan province in China. As such, the results of this study may provide insight into the prevention and treatment of carotid atherosclerotic diseases in a population at a high risk for stroke in this district.
Carotid intima-media thickness is a proxy for subclinical atherosclerosis which has been shown to be related to CVD risk.[18] Increased carotid intima-media thickness and the progression of atherosclerosis are associated with the major CVD risk factors. Carotid intima-media thickness has been suggested as a marker of vascular aging, whereas carotid plaque, an indicator of subclinical atherosclerosis, has been demonstrated as having a stronger predictive ability for future CVD.[19] In the Japan Atherosclerosis Society guideline, the intima-media thickness is used to assess subclinical atherosclerosis to prevent atherosclerotic cardiovascular disease.[20] It also has been demonstrated that stroke patients with younger age are at a huge risk for new CVD, ae well as death, especially due to atherosclerosis, which is mostly attributable to modifiable risk factors.[21] Many studies have previously investigated the risk factors for carotid atherosclerotic disease, with most yielding similar results. In brief, the risk factors for carotid atherosclerosis have been identified as follows: obesity, smoking, dyslipidemia (total cholesterol, high density lipoprotein cholesterol, and LDL-C), hypertension, age, diabetes mellitus, smoking, increased BMI, male sex, low education, alcohol consumption, and physical inactivity.[19,21–25] The conclusion of our study is consistent with all of the above studies.
In our previous studies in another high-stroke-risk population, we identified an association between risk factors and carotid ultrasound results, including the number of CP and the side of CCAIMT.[11] In the present study, we aimed to verify this conclusion in another high-stroke-risk population in another province, to identify different strategies to protect people from the damage of carotid atherosclerosis in different districts.
In this study, risk factors for a single CP were lack of physical exercise, and age, smoking, lack of physical exercise were the risk factors for multiple CPs. As for CCAIMT, risk factors for left CCAIMT include hyperlipidemia and LDL cholesterol level, while the only identified risk factor for right CCAIMT was male gender. Risk factors for dual CCAIMT consist of age and male sex. There may be several explanations for these differences. A search of similar studies showed that many have indicated patients with metabolic syndrome have a higher total plaque area than non-affected individuals, while the risk of carotid atherosclerosis associated with metabolic syndrome components.[26,27] These results were also applications to Chinese individuals, with other studies based on populations enrolled from different areas of China showing the same results.[28–30] Researchers from Greece revealed that the left and right CCAIMT differed in their values and associations, with the left CCAIMT being higher and more closely related to cardiovascular risk factors (mainly systolic blood pressure).[31] Other studies have revealed in general and hypertensive adult populations, the CCAIMT is higher on the left side than on the right side.[32–34] In addition, there is evidence to suggest that subclinical damage at different sites in the arterial tree is not uniformly determined by the same cardiovascular risk factors.[35,36] With regard to the indices of carotid ultrasonography, one recent study found that most of the parameters were significant on the left side, suggesting that carotid atherosclerosis may not be symmetrical. In this study, researchers revealed the significantly higher values of resistive index and pulsatility index in the left internal carotid artery of the older patients, while smoking history was found to be significantly associated with the left common carotid artery resistive index and pulsatility index values.[37] Chinese researchers have also found that hemodynamic and biochemical changes had different effects on the carotid artery intima-media thickness (CIMT) depending on the side affected. Specifically, right CIMT correlated better with hemodynamic parameters, while left CIMT showed better correlation with biochemical indices.[38] In our study, the risk factors for right and dual CCAIMT included age and male sex, which is consistent with prior studies. Further, the risk factors for left CCAIMT included abnormal blood lipid indices, which confirmed the conclusion of the previous study.[38] To our knowledge, studies on the different effects of risk factors on CCAIMT are limited; therefore, further investigation is needed in the future.
Overall, this study revealed several risk factors have influence on the results of the carotid ultrasound. In China, reducing the mortality and morbidity associated with stroke has always been a challenge. Early intervention of carotid atherosclerotic disease and targeted prevention strategies in different regions may help to reduce the mortality and morbidity of stroke, particularly in individuals with high-risk factors. For specific patients, control strategies should be emphasized, as preventive measures against these modifiable risk factors have been shown to effectively reduce the risk of CVD.[39]
5. Conclusion
Overall, the results of this study indicated risk factors for CP and CCAIMT, as well as the relationship between risk factors and CP number and the side of CCAIMT.
Acknowledgments
We thank the School-enterprise joint special fund of Qujing Medical College (2022XQ003) and Yunnan Provincial Department of Science and Technology-Yunnan University of Traditional Chinese Medicine Application Fundamental Joint Special Fund Project (202001AZ070001-080). And We also would like to thank Editage (www.editage.com) for English language editing.
Author contributions statement
Conceptualization: ChunFang Wang.
Data curation: ChunFang Wang.
Formal analysis: ChunFang Wang.
Funding acquisition: ChunFang Wang, Lijun Hou.
Investigation: ChunFang Wang.
Methodology: ChunFang Wang, Lijun Hou.
Project administration: ChunFang Wang.
Resources: ChunFang Wang, Lijun Hou.
Software: ChunFang Wang.
Supervision: ChunFang Wang, Lirong Geng.
Writing – original draft: ChunFang Wang.
Writing – review & editing: ChunFang Wang.
Abbreviations:
- BMI
- body mass index
- CCAIMT
- carotid common artery intima-media thickening
- CI
- confidence intervals
- CIMT
- carotid artery intima-media thickness
- CP
- carotid plaque
- CVD
- cardiovascular disease
- LDL-C
- low density lipoprotein cholesterol
- TIA
- transient ischemic attack
This work was supported by the School-Enterprise Joint Special Fund of Qujing Medical College under Grant (2022XQ003) and Yunnan Provincial Department of Science and Technology-Yunnan University of Traditional Chinese Medicine Application Fundamental Joint Special Fund Project under Grant (202001AZ070001-080).
All participants provided written informed consent before enrolling in the study. The study was approved by the Clinical Experimentation Committee of Human of the Qujing Second People Hospital (2022-006-01) and was conducted according to the Declaration of Helsinki.
The authors have no conflicts of interest to disclose.
All data generated or analyzed during this study are included in this published article [and its supplementary information files].
How to cite this article: Wang C, Geng L, Hou L. Analysis of carotid ultrasound in a high-stroke-risk population. Medicine 2024;103:44(e40383).
Contributor Information
Lirong Geng, Email: 13988916370@163.com.
Lijun Hou, Email: 15887458287@163.com.
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