Besides BPV variables, we also examined the correlation between the mean BP level and segment-specific carotid IMT. We only found that 24 hours mean DBP and daytime mean DBP were negatively correlated with mean ICA-IMT in the diabetes group (r = −0.518, P = 0.009; r = −0.540, P = 0.006, respectively). Besides these, no mean BP level were associated with carotid IMT.
Furthermore, we excluded the subjects with plaque to examine the relationship between BPV variables and initial thickening of the arterial wall. The significant results of nondiabetes are shown in Fig. 3. For nondiabetics, 24 hours and daytime SBPV/DBPV were correlated with the carotid IMT in 3 segments. However, for diabetics, only nighttime SBPV was related to the carotid CCA-IMT (r = 0.840, P < 0.001) and the correlation coefficients were higher than that in the above analysis.
3.4 Multiple regression analysis
Multiple regression analysis was performed using stepwise selection to estimate the associations between carotid IMT and BPV. Mean CCA-IMT, carotid bulb IMT, and ICA-IMT were dependent factors for both diabetes and nondiabetes patients. The BPV variables significantly correlated with each segment of carotid IMT in Tables 2 and 3 were considered independent factors for the corresponding model. As only mean ICA-IMT was correlated with mean BP, 24 hours mean DBP and daytime mean DBP were added into model 6 as the independent factors. Besides, all the statistical models were adjusted for age, sex, current smoking, and heart disease. Table 4 shows the results of the multiple regression analysis. Models 1 to 3 show the multiple regression analysis results for nondiabetes patients. Models 4 to 6 describe the regression analysis functions pertaining to patient with diabetes. These results showed the segment-specific associations between carotid IMT and BPV. For nondiabetes patients, the results in model 1 showed that age and smoking correlated in a linear fashion with mean CCA-IMT (P < 0.001 for both). In model 2, mean carotid bulb IMT was the dependent factor, and only age remained in the model (P = 0.003). However, in model 3, age (P = 0.001) and sex (P = 0.002) were the factors correlated with increased mean ICA-IMT.
The results for diabetes patients differed entirely. Models 4 and 5 had similar results in which, instead of age and sex, nighttime SBPV using the ARV index (P = 0.007 for model 4, P = 0.006 for model 5) and heart disease (P = 0.006 for model 4, P = 0.037 for model 5) were significantly associated with mean CCA-IMT and carotid bulb IMT. In model 6, age was also not found to be an independent factor in the model. However, smoking (P = 0.001) and 24 hours mean DBP (P < 0.001) and daytime SBPV (ARV) (P = 0.012) were the factors in this model which evaluated the increased mean ICA-IMT. Among these models, all the linear models pertaining to patients with diabetes had better linear fitting than did the models for nondiabetes patients.
Our study provided fresh insight into the influence of 24 hours ambulatory BPV on early carotid atherosclerosis in hypertension with and without diabetes. Early carotid atherosclerosis was evaluated using different segments of carotid IMT measurements in the asymptomatic individuals. It contributed 3 major findings. First, ambulatory BPV variables were closely associated with segment-specific measures of carotid IMT, which were revealed not only in different sites of the carotid artery, but also in the bilateral carotid artery. Second, the associations uncovered varied in patients with and without diabetes. In patients with diabetes, nighttime SBPV was an independent risk factor related to CCA-IMT and carotid bulb IMT. In nondiabetes patients, daytime and 24 hours SBPV was positively associated with CCA-IMT and ICA-IMT. However, they could not explain the progression of carotid IMT after adjusting for baseline characteristics. Third, although different segments of the carotid artery had similar prognostic significance for early arteriosclerosis or plaque prevalence, the underlying mechanisms of BPV for increasing vessel wall thickness may have been different.
Several studies have investigated the associations between carotid IMT and traditional risk factors, such as age, sex, body mass index, and BP.[13,21] Nguyen et al have reported the association between progression of segment-specific carotid IMT and traditional risk factors such as age, race, glucose, cholesterol, and BP level. However, the influence of BPV on different carotid artery locations has been scantly studied. Thus, our present study explored the associations between BPV and segment-specific measurements of carotid IMT. We found that CCA-IMT and ICA-IMT had stronger associations with BPV than did carotid bulb IMT. In addition, in all subjects, BPV was clearly associated with left CCA-IMT but not right CCA-IMT. These results support our hypothesis that BPV has distinct effects on different sites of carotid IMT and may lead to segment-specific early atherosclerosis progression. Possible explanations for these results are listed as follows.
First, the CCA is an elastic artery, the carotid bulb is situated in a transitional zone between elastic and muscular artery types, and the ICA is a muscular artery. Therefore, the mechanisms through which foam-cell lesions form are different at these carotid sites, thereby contributing to differences in atherosclerosis expression. Second, the left CCA stems directly from the aortic arch and is affected by aortic arch pressure. The right CCA stems from the innominate artery, which is an extension of the ascending aorta, and is subject to significant pressure from ascending aortic blood flow. Thus, segment-specific associations might account for these hemodynamic and anatomical differences. Luo et al also proposed this hypothesis and found that left carotid IMT was associated mainly with blood biochemical indices, whereas right carotid IMT correlated mainly with hemodynamic parameters. Another study found that CCA-IMT, carotid bulb IMT, and ICA-IMT showed segment-specific associations with cardiovascular risk factors in young white and black men and women. Fasting glucose and diastolic BP had higher correlations with CCA than for other segments. These studies support our view on segment-specific associations. Thus, we conclude that BPV plays a distinct role in arteriosclerosis progression within the different segments of the carotid artery.
Many studies have investigated the relationship between BPV and carotid IMT but reported inconsistent results. Several studies found that daytime or/and 24 hours SBPV was positively associated with increased carotid IMT, early atherosclerosis, or organ damage.[25–29] Other studies suggested that only nighttime variability in SBP, but not daytime variability in SBP, was related to carotid atherosclerosis or cardiovascular outcomes.[30,31] A recent study reported that time rate of BP variation but not ambulatory BPV was correlated with carotid IMT. These controversial results may have arisen from differences in patient population selection, BPV index, sample size, study endpoints, and other factors. In our previous study, we found that, for the nondiabetes patients, SBP fluctuations during daytime and during a 24 hours period were significantly associated with increased CCA-IMT. In the present study, we divided patients into 2 subgroups: nondiabetes and diabetes. We found that for diabetes patients, nighttime SBPV was strongly associated with CCA-IMT and carotid bulb IMT and was independently correlated with mean CCA-IMT and bulb IMT after adjusting for age, sex, smoking, and heart disease. In contrast, for hypertension patients without diabetes, daytime and 24 hours SBPV had a positive significant correlation with CCA-IMT and ICA-IMT. However, they were not remained in the adjusted regression models. Not only was BPV associated with increased IMT, but nighttime BPV and daytime BPV had distinct associations with IMT according to patient population. This finding is in line with the study of Eguchi et al, who found that instead of diurnal BP variation, nighttime SBPV was a strong independent predictor of cardiovascular events in patients with type 2 diabetes. However, the relationship between IMT and BPV in patients without diabetes has not been extensively examined. We can only speculate that BPV has different mechanisms of action on artery alteration in individuals with and without diabetes. Moreover, these results indicate that for nondiabetes patients, nighttime SBPV can be as significant a predictor for increased carotid IMT. All these findings will enhance our understanding of the progression of arteriosclerosis in these 2 groups, and they promise to provide a fresh perspective on prevention and treatment of early carotid atherosclerosis and its complications.
Our study also provided evidence that different segments of the carotid artery have similar prognostic significance for arteriosclerosis or the prevalence of plaque. This evidence corroborates the conclusions of Damiano et al. In addition, we found that carotid bulb IMT and CCA-IMT were associated more closely with the number of plaques than was ICA-IMT. The results implied how atherosclerosis manifests within different arteries. Dalager et al established that, owing to its structure, the carotid bifurcation could easily develop foam-cell lesions and lipid core plaques from an early stage. Furthermore, this study clarified that the carotid bulb is a common site of plaque development. Accordingly, the wall thickness at this site is greater when more plaques form. This observation could explain our result that carotid bulb IMT correlated more closely with the number of plaques. In a related finding, Bots et al found that CCA-IMT could predict atherosclerosis formation elsewhere in the carotid artery, such as at the bifurcation and the near and far walls of the distal CCA. Their findings agree with our results about the linear correlation between increased CCA-IMT and the percentage of plaque prevalence. Thus, we conclude that CCA-IMT and bulb IMT have higher prognostic significance for plaque prevalence than do IMTs measured at ICA.
Several other findings of our study deserve to be briefly discussed. First, the results from Tables 2 and 3 showed that the ARV index had higher correlation coefficient with carotid IMT, especially in the patients without plaque. Thus, we concluded that the ARV index had better prognostic significance for evaluating the increased carotid IMT. This finding is consistent with the conclusion of Mena et al, who reported that the ARV index showed better prognostic significance for organ damage and cardiovascular risk than did the SD index. Hansen et al also indicated that although both daytime BPV (using the SD index) and 24 hours BPV (using the ARV index) were useful measures, BPV estimated using the SD index over 24 hours was not. Thus, the ARV index is a more reliable measurement for BPV. Second, we discussed whether BPV was an independent factor for predicting increased carotid IMT at different sites, an idea that had proven controversial based on the results of previous studies.[7,37,38] In our multiple regression analysis, we adjusted for age, sex, smoking, and heart disease, and found that various risk factors influenced segment-specific carotid IMT. For nondiabetes patients, age was a factor in all the regression models. However, for diabetes patients, heart disease and smoking were risk factors for increased carotid artery wall thickness. The mean BP level did not contribute for the progression of the carotid artery wall, except for the ICA-IMT. The increased ICA-IMT can be explained both by 24 hours mean DBP and daytime SBPV. Third, mean daytime DBP and daytime SBPV showed a strong negative correlation with mean ICA-IMT, and this association persisted even after adjusting for baseline characteristics. Lastly, we examined the relations between BPV and carotid IMT in patients without plaque. In Sander's study published in Circulation, they investigated the relationship between circadian BP pattern and progression of early carotid. It is a follow-up study, and all the patients were >55 years old. In their research, early atherosclerosis was defined as an age-adjusted IMT>1.5 mm. In our study, IMT>1.5 mm indicated the presence of plaque, which is the early sighs of the atherosclerosis. However, in our results shown in Fig. 3, BPV is highly correlated with the increased carotid IMT before the plaque formation. Maybe it will provide a possible pattern to predict the carotid atherosclerosis in the early stage.
Finally, some limitations of our study should be acknowledged. First, this was a cross-sectional descriptive design, and therefore we could not infer the cause-and-effect relationship between BPV and increased IMT or plaque formation. Second, we measured nighttime BP once per hour, so this frequency of reading provided limit BP data for computing BPV. Third, the number of subjects in our study was limited, especially for patients with diabetes. We referred to several small sample studies and similar studies,[39–41] the conclusion is reasonable although the limited data. However, further study with a large-scale patient population is still needed to verify our results.
The present study provided initial data about the relationship between ambulatory BPV and different carotid segment IMTs in hypertension with and without diabetes. Its findings indicate that for all subjects, the association between bilateral carotid IMT and ambulatory BPV had clear differences that appeared not only in different carotid artery segments, but also in the left and right carotid artery. We speculate that these phenomena resulted from different anatomical structures and hemodynamic. However, scant evidence is available to verify this hypothesis. Thus, a further study is needed to explore the effects of BPV on arteriosclerosis progression.
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Keywords:Copyright © 2016 The Authors. Published by Wolters Kluwer Health, Inc. All rights reserved.
atherosclerosis; blood pressure variability; carotid intima-media thickness; diabetes; nondiabetes