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Hypertension. 2005;45:505-512
Published online before print March 7, 2005, doi: 10.1161/01.HYP.0000158306.87582.43
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(Hypertension. 2005;45:505.)
© 2005 American Heart Association, Inc.

Original Articles

Time Rate of Blood Pressure Variation Is Associated With Increased Common Carotid Artery Intima-Media Thickness

Nikos A. Zakopoulos; Georgios Tsivgoulis; Gerassimos Barlas; Christos Papamichael; Konstantinos Spengos; Efstathios Manios; Ignatios Ikonomidis; Vassilios Kotsis; Ioanna Spiliopoulou; Konstantinos Vemmos; Myron Mavrikakis; Spyridon D. Moulopoulos

From the Department of Clinical Therapeutics "Alexandra" Hospital, University of Athens, Greece.

Correspondence to Nikos Zakopoulos, MD, Irodou Attikou 58, 15233 Athens, Greece. E-mail nzakop{at}med.uoa.gr


*    Abstract
up arrowTop
 *Abstract
down arrowIntroduction
 down arrowSubjects and Methods
 down arrowResults
 down arrowDiscussion
 down arrowReferences
 
The extent of target-organ damage has been positively associated with the magnitude of blood pressure (BP) variability in essential hypertension. However, the clinical implications of the rate of BP changes have never been investigated. We evaluated the association between the rate of systolic BP (SBP) variation derived from ambulatory BP monitoring (ABPM) data analysis and the extent of common carotid artery (CCA) intima-media thickness (IMT) in normotensive (n=280) and in uncomplicated hypertensive subjects (n=234). The 24-hour rate of SBP variation was significantly (P<0.001) higher in hypertensive (0.608 mm Hg/min; 95% confidence interval [CI], 0.595 to 0.622) than in normotensive individuals (0.567 mm Hg/min; 95% CI, 0.555 to 0.578), even after adjusting for baseline characteristics, day–night BP changes, 24-hour heart rate (HR), SBP, and HR variability. In the entire group of patients, multiple linear regression models revealed independent determinants of CCA-IMT in the following rank order: age (P<0.001), 24-hour rate of SBP variation (P<0.001), male gender (P=0.004), cholesterol (P=0.009), and smoking (P=0.014). A 0.1 mm Hg/min increase in the 24-hour rate of SBP variation was associated to an increment of 0.029 mm (95% CI, 0.018 to 0.040) in CCA-IMT independent of BP and HR levels, BP and HR variability, and dipping status. The rate of SBP variation during the morning BP surge correlated independently (P<0.001) to larger CCA-IMT values after adjustment for baseline characteristics and other ABPM parameters. Thus, the rate of BP fluctuations is greater in hypertensive patients and correlates to increased CCA-IMT. This finding indicates that steeper BP variations may produce a greater stress on the vessel wall and consequently result in medial hypertrophy of the large arteries.


Key Words: blood pressure • carotid arteries • blood pressure monitoring • baroreflex • ultrasonography


*    Introduction
up arrowTop
 up arrowAbstract
 *Introduction
down arrowSubjects and Methods
 down arrowResults
 down arrowDiscussion
 down arrowReferences
 
Prospective studies in treated and untreated hypertensive patients and in the general population have demonstrated that even after adjusting for established risk factors, the incidence of cardiovascular events is correlated with blood pressure (BP) on conventional as well as ambulatory measurements.1,2 However, ambulatory BP monitoring (ABPM) significantly refines the prediction already provided by office recordings because target-organ damage is more closely associated with ambulatory than clinic BP.1,2

Intra-arterial beat-to-beat monitoring has shown that BP is highly variable.3 Despite difficulties in the assessment of BP variability, particularly with noninvasive techniques,4 evidence from cross-sectional5–9 and longitudinal studies10–12 has suggested an independent and positive relationship between the extent of target-organ damage (measured by left ventricular mass, early carotid atherosclerosis, subcortical brain lesions, or a comprehensive end-organ damage score) and the magnitude of BP variability in essential hypertension. Besides, BP variability was an independent predictor for cardiovascular mortality in the general population.13 Interestingly, Mancia et al reported recently that hypertensive patients compared with normotensive subjects present steeper fast- and short-duration beat-to-beat BP changes, documented by means of intra-arterial BP monitoring.14 Furthermore, experimental studies have suggested that the traumatic effect of intravascular pressure on the vessel wall, which results in vascular remodeling and atherosclerosis, may be more closely associated to oscillatory than to steady laminar shear stress.15–17 This evidence raises the issue of whether a hypertensive patient’s prognosis depends not only on average BP level but, to some extent, also on the degree and rate of BP variation.

However, the clinical implications of the time rate of noninvasive ambulatory BP changes have never been investigated in essential hypertension. Quantitative B-mode ultrasound imaging offers the opportunity to assess the intima-media thickness (IMT) of the common carotid artery (CCA), which is considered a reliable marker for the extent of early atherosclerosis18 and an indicator of the risk of cardiovascular diseases.19 Moreover, Zanchetti et al reported that CCA-IMT mostly reflects the degree of hypertension-induced hypertrophy of the CCA, whereas the atherosclerotic complications of hypertension are more likely to affect the internal carotid artery.20,21 In view of these considerations, the aim of the present study was to evaluate the possible association between the rate of BP variation, derived from computerized analysis of ABPM data, and the extent of CCA-IMT in normotensive and uncomplicated hypertensive subjects.


*    Subjects and Methods
up arrowTop
 up arrowAbstract
 up arrowIntroduction
 *Subjects and Methods
down arrowResults
 down arrowDiscussion
 down arrowReferences
 
Subjects
From a consecutive series of 3173 subjects referred for evaluation to the hypertension center of our department between January 1998 and January 2004, 539 individuals fulfilled the following inclusion criteria: (1) no history or clinical evidence of hypertension-related complications (coronary artery disease, heart failure, cerebrovascular disease, renal insufficiency, or peripheral artery disease); (2) no clinical signs or laboratory evidence of secondary causes of arterial hypertension; (3) no previous antihypertensive treatment; (4) no previous lipid-lowering treatment; (5) no history or laboratory evidence of diabetes mellitus (fasting serum glucose <7.0 mmol/L; nonfasting serum glucose <11.1 mmol/L)22 and no previous treatment with blood sugar–lowering drugs; (6) no history or electrocardiographic evidence of atrial fibrillation; and (7) no atherosclerotic plaques (1% to 29% reduction in lumen diameter) and no moderate (30% to 70% reduction) or severe (>70% reduction) stenosis at a high-resolution, B-mode ultrasonographic evaluation of the carotid arteries, according to the European Carotid Surgery Trial criteria.23

Height and weight were recorded, and body mass index was calculated as weight-to-height squared. After an overnight fast of ≥8 hours, a venous blood sample was collected, and plasma total cholesterol, triglycerides, and glucose were measured. The entire group of patients was investigated prospectively with ABPM and carotid ultrasonography.

BP Measurements
All 539 subjects underwent 24-hour ABPM on a usual working day. They were instructed to act and work as usual and to keep their nondominant arm still and relaxed at the side during measurements. Ambulatory BP was recorded using oscillometric Spacelabs 90207 equipment (Spacelabs). Readings were obtained automatically at 15-minute intervals throughout the 24-hour study period. Daytime was defined as the interval between 6:00 AM and 10:00 PM, and nighttime was the interval between 10:00 PM and 6:00 AM. We excluded from further analysis individuals with <3 valid readings per hour during the 24-hour recording (n=17). The resulting 72 to 96 pairs of systolic BP (SBP) and diastolic BP (DBP) readings per recording, together with the corresponding time of measurement, were used to calculate BP derivatives. For each patient, we computed 24-hour, daytime, and nighttime average SBP and DBP and heart rate (HR) values. All subjects were instructed to rest or sleep during nighttime and to maintain their usual activities during daytime. Moreover, they were specifically advised to avoid strenuous exercise and sleeping during daytime and to rise from bed after 6:00 AM even if they were awake earlier than this time of the day. None of the study participants were bedridden or hospitalized during ABPM. Individuals who stated that they had not rested during the night interval were excluded from further evaluation (n=8). All patients maintained a number-coded diary in which activities and particular events were recorded. The analysis of this diary revealed no significant differences for several activities between the normotensive and hypertensive subgroups. Details concerning the accuracy of the automatic BP readings against manual recordings have been described previously.24 The final study population consisted of 514 individuals fulfilling all the above-mentioned inclusion criteria. All subjects gave their informed consent to participate in the study.

Awakening in the morning is accompanied by a steep rise in SBP and DBP. Physical activity on arousal and rising from bed is regarded as the major determinant of this morning surge in BP,2 which occurs at {approx}6:00 AM and continues for 4 to 6 hours after awakening.25 Because all subjects underwent ABPM on a usual working day and were instructed to rise from bed after 6:00 AM, the time period of the "morning BP surge" was defined as the time interval between 6:00 AM and 10:00 AM. The recorded 9 to 12 pairs of SBP and DBP readings during this time window, together with their corresponding time of measurement, were used to calculate BP derivatives during the morning BP surge. Consequently, for each patient, we computed average SBP and DBP and HR values throughout this time period.

ABPM Data Analysis
On the basis of ABPM results, subjects with an average daytime BP >135/85 mm Hg were classified as hypertensive and those with average daytime BP levels ≤135/85 mm Hg as normotensive.2,12 For each patient, the day–night BP changes (mm Hg) were computed as average daytime BP minus average night–time BP and the nocturnal BP dipping (%) as 100x[1–nighttime BP/daytime BP ratio].9,26 BP variability was defined as the within-subject SD of all SBP and DBP recordings during the 24-hour measurement period.9 HR variability was defined as the within-subject SD of mean HR during the 24-hour measurement period. The time rate of SBP variation was defined as the first derivative of the SBP values against time. This parameter, derived from ABPM data analysis, aimed to measure how fast or how slow and in which direction SBP values change. Because we have discrete values, the derivatives are approximated by differences. Given 2 SBP readings, Si and Si+1 at time indices ti and ti+1, respectively, the rate of BP change was defined as follows: Down


{11MM1}

at time index Down


{11MM2}

Figure 1 illustrates an example for computing the rate of noninvasive ambulatory BP changes. However, it should be acknowledged that the former ABPM parameter assesses the rate of relatively "long-term" BP fluctuations because of the limitations imposed by discontinuous noninvasive ABPM.



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  		Figure 1. An example of computing the rate (r) of noninvasive ambulatory BP changes. S0, S1, S2, and S3 stand for 4 consecutive SBP readings at time indices of t0, t1, t2, and t3, respectively.

Given N recordings of SBP during the 24-hour period of ABPM, we can compute N-1 values for the rate of SBP variation at N-1 different time indices. To derive a metric that could describe the magnitude of BP increases and decreases in relation to time, the mean of the absolute rate of SBP variation values during the whole 24-hour period was estimated. Thus, for each patient with N SBP recordings, the following variable, to which we refer as 24-hour rate of SBP variation (mm Hg/min), was calculated: Down


{11MM3}

SBP and DBP variability during the morning BP surge (6:00 AM to 10:00 AM) were quantified as the within-subject SD of all SBP and DBP recordings documented throughout the former time period. In addition the rate of SBP variation during the morning, BP surge was estimated as the mean of the absolute rate of SBP variation values computed during this 4-hour time window.

Carotid Artery Ultrasonographic Measurements
The left and right CCA were examined in the anterolateral, posterolateral, and mediolateral directions with a high-resolution ultrasound Doppler system (Acuson 128XP), equipped with a 7-MHz linear-array transducer. Subjects were examined in the supine position, with the head turned 45° from the site being scanned. Both carotid arteries were scanned longitudinally to visualize the IMT in the far wall of the artery. The best images of the far wall that could be obtained were used to determine the CCA. Measurements were made on frozen images, magnified to standard size online. The CCA-IMT value was defined as the mean of the right and left IMT of the CCA, calculated from 10 measurements on each side, taken 10 mm proximal to the carotid bifurcation. The lumen/intima leading edge (I-line) to media/adventitia leading edge (M-line) method, which has been previously validated anatomically, was used.27 The longitudinal B-scan frames were digitized and analyzed using a computerized image analysis by 2 investigators blinded to the BP recordings. The reproducibility of IMT measurements between and within sonographers had been checked previously.24,28

Statistical Analyses
Statistical comparisons were performed between hypertensive and normotensive subjects in terms of baseline characteristics, ABPM parameters, and carotid ultrasonographic measurements. Dichotomous variables were compared with the {chi}2 test and continuous variables with the unpaired t test. All values are given as mean with their corresponding 95% confidence interval (CI). The variation in CCA-IMT between the 2 subgroups according to baseline characteristics was tested by ANCOVA. The 24-hour rate of SBP variation (after adjustment for baseline characteristics and ABPM parameters) was also compared between normotensive and hypertensive individuals by means of ANCOVA. The covariate adjusted mean values were computed and are presented with their corresponding 95% CI. Simple and multiple linear regression analyses were performed to assess which factors are associated independently with CCA-IMT in the combined group of hypertensives and normotensives. Baseline characteristics and office and ABPM parameters were selected as independent variables; CCA-IMT was the dependent variable. The CCA-IMT data were entered as continuous values in the model. In the initial simple regression analysis, a threshold of P<0.1 was used to identify candidate variables for inclusion in the final model (because of the risk of type II error attributable to low statistical power in such an analysis). The multiple regression analyses were performed using the backward procedure and repeated using a forward-selection procedure. Statistical significance was achieved with a 2-tailed value of P<0.05. The associations between CCA-IMT and the other variables are presented by means of linear regression coefficients with their corresponding 95% CI. In multiple regression, a given regression coefficient indicates how much the predicted value of the dependent variable (CCA-IMT) changes each time the respective variable increases by 1 U, holding the values of all other variables in the regression equation constant. Finally, the significant independent variables selected by the multiple regression models were ranked according to the absolute value of their standardized effect, quantified by the standardized regression coefficient (ß). A standardized regression coefficient is defined as a regression coefficient that has the effect of the measurement scale removed so that the size of the coefficient can be interpreted; it is computed by multiplying the regression coefficient by the ratio of the SD (SDx) of the independent variable to the SD (SDy) of the dependent variable (ß=regression coefficientxSDx/SDy). All covariates included in the final models were tested for interactions with each other. Because the tolerance values for each covariate were >0.5, no correction for the collinearity of data were necessary. The Statistical Package for Social Science (version 10.0 for Windows; SPSS) was used for statistical analyses.


*    Results
up arrowTop
 up arrowAbstract
 up arrowIntroduction
 up arrowSubjects and Methods
 *Results
down arrowDiscussion
 down arrowReferences
 
No significant differences were documented between hypertensive (n=234) and normotensive (n=280) patients regarding baseline characteristics and HR variability (Table 1). In contrast, CCA-IMT (before and after adjustment for baseline characteristics), SBP and DBP variability, and 24-hour HR were significantly higher in the hypertensive population. The 24-hour rate of SBP variation was significantly higher (P<0.001) in hypertensive (0.608 mm Hg/min; 95% CI, 0.595 to 0.622) than normotensive subjects (0.567 mm Hg/min; 95% CI, 0.555 to 0.578), even after adjusting for baseline characteristics, day–night SBP and DBP change, nocturnal SBP and DBP dipping, and SBP and HR variability. An example of the higher rate of SBP variation in a hypertensive patient compared with a normotensive subject is illustrated in Figure 2. The average rate of SBP variation during daytime (6:00 AM to 10:00 PM), nighttime (10:00 PM to 6:00 AM), and the morning BP surge (6:00 AM to 10:00 AM) was significantly higher (P<0.001) in the hypertensive than the normotensive subgroup (Table 1).


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  		TABLE 1. Baseline Characteristics, ABPM Parameters, and Carotid Ultrasonographic Measurements in Normotensive and Hypertensive Subjects



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  		Figure 2. Twenty-four–hour profiles of SBP and rate of SBP variation values in a normotensive (a and c) and hypertensive subject (b and d). The dotted lines in c and d depict the means of the absolute time rate values (24-hour rate of SBP variation).

In the combined normotensive and hypertensive group, the magnitude of day–night SBP change correlated with the 24-hour rate of SBP variation (linear regression coefficient, 0.0015; 95% CI, 0.000 to 0.003; P=0.015), in contrast to SBP dipping, which was not associated with the rate of SBP changes (linear regression coefficient, 0.001; 95% CI, –0.001 to 0.003; P=0.201). The multiple linear regression model (performed by the backward procedure) revealed significant and independent determinants of CCA-IMT in the following rank order (Table 2): age (ß=0.358; P<0.001), 24-hour rate of SBP variation (ß=0.202; P<0.001), male gender (ß=0.119; P=0.004), cholesterol (ß=0.105; P=0.009), and smoking status (ß=0.099; P=0.014). A 0.1-mm Hg/min increase in the 24-hour rate of SBP variation correlated to an increment of 0.029 mm (95% CI, 0.018 to 0.040) in the CCA-IMT. The predicted model accounted jointly for 28.2% of the variation in CCA-IMT (R2=0.282). This association was independent of BP and HR levels, the magnitude of BP and HR variability, and the components of diurnal BP variation. Its statistical significance was retained after repeating the analyses using the forward-selection procedure.


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  		TABLE 2. Simple and Multiple Linear Regression Analyses of Factors Associated With CCA-IMT

Calculation of the morning BP rise is a difficult task because it may be affected by the degree of the nocturnal BP fall. We assessed the relationship between the rate of SBP variation during the morning BP surge (6:00 AM to 10:00 AM) and the CCA-IMT after adjusting for baseline characteristics and other ABPM parameters during this time period (Table 3). A 0.1-mm Hg/min increase in the rate of SBP variation during the morning BP surge correlated to an increment of 0.010 mm (95% CI, 0.003 to 0.017; P=0.008) in the CCA-IMT (Table 3). Moreover, a 0.1-mm Hg/min increase in the daytime and nighttime rate of SBP variation was associated independently with an increment of 0.024 mm (95% CI, 0.015 to 0.033; P<0.001) and 0.016 mm (95% CI, 0.007 to 0.025; P=0.001) in the CCA-IMT, respectively, even after adjusting for baseline characteristics. However, the daytime rate of SBP variation correlated more strongly to CCA-IMT (Pearson correlation coefficient, 0.298; P<0.001) than the nighttime (Pearson correlation coefficient, 0.234; P<0.001) and the 24-hour rate (Pearson correlation coefficient, 0.292; P<0.001) of SBP variation.


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  		TABLE 3. Association of ABPM Variables Recorded During the Morning BP Surge (6:00 AM to 10:00 AM) and CCA-IMT

The correlation between the 24-hour rate of SBP variation and CCA-IMT (independent of the average 24-hour SBP levels) is demonstrated in Figure 3. Subjects were classified into tertiles of 24-hour SBP average ambulatory values (lower tertile ≤120.6 mm Hg; median tertile >120.6 mm Hg and ≥132.7 mm Hg; and higher tertile >132.7 mm Hg). Each of the 3 tertiles was further subdivided into 2 subgroups, with a 24-hour rate of SBP variation smaller (subgroup A) or greater (subgroup B) than the median 24-hour rate in the respective tertile. For each tertile, significantly larger CCA-IMT values were documented in patients of subgroup B than in subjects of subgroup A.



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  		Figure 3. Association between 24-hour rate of SBP variation and CCA-IMT. Subjects are classified into tertiles of 24-hour SBP average ambulatory values. For each tertile, subjects are divided into 2 subgroups with a 24-hour rate of SBP variation smaller (subgroup A) or greater (subgroup B) than the median 24-hour rate of the respective tertile.


*    Discussion
up arrowTop
 up arrowAbstract
 up arrowIntroduction
 up arrowSubjects and Methods
 up arrowResults
 *Discussion
down arrowReferences
 
The results of this cross-sectional study indicate that the 24-hour rate of SBP variation derived from computerized analysis of ABPM data was greater in hypertensive than in normotensive subjects and was the only office or ABPM parameter that was linearly and independently associated with CCA intima-media thickening.

Our first finding corroborates the recently reported results of Mancia et al, who investigated the rate of beat-to-beat BP changes in 21 uncomplicated hypertensive subjects and 13 normotensive controls by means of intra-arterial BP monitoring. After documenting a markedly greater slope of the rapid- and short-duration SBP changes in the hypertensive group, the investigators concluded that hypertensive patients are characterized not only by wider but also steeper BP changes.14 In our study, the rate of noninvasive ambulatory BP changes derived from ABPM data analysis was also more pronounced in the hypertensive population compared with normotensive controls. However, it should be stressed that in our report, we investigated relatively long-term BP fluctuations in relation to time, whereas in the study of Mancia et al, the slope of beat-to-beat BP changes was quantified using continuous intra-arterial monitoring.

The mechanisms responsible for this phenomenon cannot be clarified by the nature of the present investigation. However, because the former difference persisted even after adjusting for all baseline characteristics and SBP variability, it is unlikely that it could be attributed to the greater absolute magnitude of BP variation in hypertensive subjects per se or to selection bias concerning the 2 patient groups. A disturbed baroreflex function is related to an exaggerated pressor response to mental stress and physical stimuli resulting in increased BP variability.29 In contrast, HR variability positively correlates baroreflex sensitivity, and an inverse relationship between BP (greater extent of BP variations) and HR (more stable HR) variabilities has been shown to reflect an impaired baroreflex function.29,30 However, in our report, the 2 subgroups did not differ significantly in terms of HR variability, although a higher SBP variability was documented in the hypertensive group. Moreover, given that the rate of SBP variation remained significantly increased in the hypertensive subgroup even after adjustment for 24-hour SBP and HR variability, it is unlikely that impaired baroreflex function is the chief mechanism explaining the steeper ambulatory BP changes in essential hypertension. Increased arterial stiffness, which reflects the damaging effect on the arterial wall of age and hypertension,31 may account for the above-mentioned phenomenon. In hypertensive individuals, large arteries become stiffer and less compliant. Consequently, because of the impaired elastic recoil of the aorta, less buffering of BP changes may occur,32 resulting in a wider SBP oscillation for any given change in the stroke volume.

We also documented that the 24-hour rate of SBP variation correlated with the day–night differences in BP but not with the dipping rate. This observation displays different relationships between the rate of SBP changes and 2 quantifications of the same phenomenon. Furthermore, it emphasizes the inconsistencies that may characterize the conventional approaches to quantify the change in BP between wakefulness and sleep. The usual falls in BP and HR that occur with sleep have been associated with a decrease in sympathetic nervous tone.33 Thus, the rate of SBP changes occurring every 15 minutes throughout the 24-hour period and the reduction of BP that takes place during night sleep may be attributable to different mechanisms and may reflect opposite patterns of sympathetic cardiovascular modulation.

In cross-sectional and longitudinal data, higher SBP variability and 24-hour SBP or pulse pressure values have been found to correlate with early carotid artery atherosclerosis7,9 and be a strong predictor of CCA-IMT progression.12 In our study, the initial associations of the 24-hour SBP, SBP variability, and nocturnal SBP dipping with the CCA-IMT failed to retain their statistical significance in the multiple regression model. In contrast, the 24-hour rate of SBP variation was the second (to age) most significant determinant of CCA-IMT. This indicates that the time rate (quantified as the first derivate of SBP values against time) and not the magnitude (quantified as the SD of the ABPM parameters) of BP changes may correlate more strongly with medial hypertrophy of the CCA in uncomplicated hypertensive as well as normotensive subjects. The differences concerning baseline characteristics between our study group (younger age, no prevalence of diabetes mellitus or concomitant cardiovascular disease, and normal carotid arteries without atherosclerotic plaques) and the populations of other studies7,9,12 may account for the nonsignificant associations of other ABPM parameters with CCA-IMT we reported.

In animal models, it has been demonstrated that oscillatory shear stress enhances stiffening of the aortic wall structure15 and stimulates mononuclear leukocyte adhesion and migration in the arterial wall, which leads to initiation of atherosclerosis.16 In addition, according to experimental evidence, the continuous exposure of endothelial cells to oscillatory shear stress has been shown to cause a sustained activation of pro-oxidant processes, resulting in redox-sensitive expression of endothelial proinflammatory genes.17 Furthermore, exaggerated cardiovascular reactivity to mental stress was a significant and independent correlate of atherosclerosis in a population sample of Finnish men.34 Therefore, we can assume that steep BP variations increase the oscillatory shear stress in the vessel wall of large arteries. This enhances the traumatic effect of intravascular pressures on the vessel wall that ultimately results in intima-media hypertrophy.

We also documented an independent association between the time rate of SBP variation during the morning BP surge and the extent of CCA-IMT. This finding is in line with previous work showing that in older hypertensives, a higher morning BP surge is associated with advanced silent cerebrovascular disease35 and also is an independent predictor of subsequent stroke events.36 Moreover, Kario has suggested recently that in addition to the current well-documented major predictors of cardiovascular risk (status of target-organ damage and ambulatory BP levels), phenotypes of abnormal diurnal BP variation, such as marked nocturnal BP decreases or exaggerated morning BP surge, may constitute a possible new axis of cardiovascular risk stratification.37 Thus, abrupt and steep BP accelerations during the morning hours leading to early atherosclerosis may be a major mechanism involved in the association between the morning BP surge and cardiovascular or cerebrovascular disease.

Finally, certain limitations of the present study should be acknowledged. First, in contrast to intra-arterial BP measurement, ABPM is not adequate to assess the rate of relatively short-term variability of each BP level with 15-minute interval. In the present report, we investigated the association of carotid atherosclerosis with the rate of noninvasive BP changes that occur with a much longer wavelength (during the morning BP surge and during the whole 24-hour period). Thus, the role of short-term and, in particular, beat-to-beat BP changes in causing alterations in the vessel walls of hypertensive patients should be addressed by means of invasive intra-arterial BP recording. Second, when the interval of BP measurement by ABPM is fixed, the time rate of SBP variation is determined predominantly by the magnitude of each BP difference. In view of the former consideration, one may argue that there is theoretically no significant implication of the rate of BP variation when compared with the actual BP variability in the study setting of intermittent ambulatory BP measurements. However, the rate of BP variations was the only ABPM parameter that was retained as an independent determinant of the CCA-IMT in the multiple regression models. This finding implies that the rate and not the magnitude of BP changes may be more strongly associated with target-organ damage such as the medial hypertrophy of the CCA. Third, the rate of DBP changes was not quantified in the present report. This issue remains to be addressed in future studies. Fourth, the limitations in assessing the rate of SBP changes when analyzing discontinuous, low frequency, and sometimes unevenly spaced BP measurements should be noted. More specifically, the possibility of artifact in the computation of the 24-hour rate of SBP variation increases with a decreasing number of successful measurements during the ABPM because of the missing data. Fifth, association does not mean causality. Although measures were taken to enhance the interpretation of our results (strict inclusion criteria to reduce the influence of concomitant diseases on the reported associations, covariate adjustment for baseline characteristics, components of day–night BP variations, and HR and SBP variability), a cause–effect relationship between steeper SBP variations and CCA intima-media thickening cannot be inferred from our cross-sectional data. Prospective studies are needed to assess whether the rate of SBP variation predicts the progression of early carotid atherosclerosis.

Perspectives
Our study provides for the first time data concerning a linear and independent relationship between the rate of relatively long-term, noninvasive BP changes assessed by means of ABPM data analysis and the extent of CCA intima-media thickening in uncomplicated hypertensive and normotensive patients. This finding indicates that the alteration of vessel wall tension associated with steeper BP increases and reductions may initiate medial hypertrophy and early atherosclerosis formation in the arterial wall of large vessels. Thus, target-organ damage in essential hypertension, in addition to the level of BP values and the magnitude of BP fluctuations, may be also related to BP changes occurring with a greater rate. Further investigation is currently needed to evaluate the mechanisms and to prospectively assess the clinical implications of this BP phenomenon.

Received September 13, 2004; first decision November 4, 2004; accepted January 3, 2005.


*    References
up arrowTop
 up arrowAbstract
 up arrowIntroduction
 up arrowSubjects and Methods
 up arrowResults
 up arrowDiscussion
 *References
 

  1. Mancia G, Parati G. Ambulatory blood pressure monitoring and organ damage. Hypertension. 2000; 36: 894–900.[Abstract/Free Full Text]
  2. Staessen JA, Asmar R, De Buyzere M, Imai Y, Parati G, Shimada K, Stergiou G, Redon J, Verdecchia P; Participants of the 2001 Consensus Conference on Ambulatory Blood Pressure Monitoring. Task Force II: blood pressure measurement and cardiovascular outcome. Blood Press Monit. 2001; 6: 355–370.[CrossRef][Medline] [Order article via Infotrieve]
  3. Mancia G, Ferrari A, Gregorini L, Parati G, Pomidossi G, Bertinieri G, Grassi G, Di Rienzo M, Pedotti A, Zanchetti A. Blood pressure and heart rate variabilities in normotensive and hypertensive human beings. Circ Res. 1983; 53: 96–104.[Medline] [Order article via Infotrieve]
  4. Di Rienzo M, Grassi G, Pedotti A, Mancia G. Continuous vs intermittent blood pressure measurements in estimating 24-hour average blood pressure. Hypertension. 1983; 5: 264–269.[Abstract]
  5. Parati G, Pomidossi G, Albini F, Malaspina D, Mancia G. Relationship of 24-hour blood pressure mean and variability to severity of target organ damage in hypertension. J Hypertens. 1987; 5: 93–98.[CrossRef][Medline] [Order article via Infotrieve]
  6. Palatini P, Penzo M, Racioppa A, Zugno E, Guzzardi G, Anaclerio M, Pessina AC. Clinical relevance of night-time blood pressure and of day-time blood pressure variability. Arch Intern Med. 1992; 152: 1855–1860.[Abstract]
  7. Sander D, Klingelhofer J. Diurnal systolic blood pressure variability is the strongest predictor of early carotid atherosclerosis. Neurology. 1996; 47: 500–507.[Abstract/Free Full Text]
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