Maximum Value of Home Blood Pressure
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Abstract
The maximum office systolic blood pressure (SBP) has been shown to be a strong predictor of cardiovascular events, independently of the mean SBP level. However, the clinical implications of maximum home SBP have never been reported. We investigated the association between the maximum home SBP and target organ damage (TOD). We assessed the left ventricular mass index (LVMI) and carotid intima-media thickness (IMT) using ultrasonography and the urinary albumin/creatinine ratio (UACR) as measures of TOD in 356 never-treated hypertensive subjects. Home BP was taken in triplicate in the morning and evening, respectively, for 14 consecutive days with a memory-equipped device. The maximum home SBP was defined as the maximum mean triplicate BP reading in the 14-day period for each individual and was significantly correlated with LVMI (r=0.51, P<0.001), carotid IMT (r=0.40, P<0.001), and UACR (r=0.29, P<0.001). The correlation coefficients with LVMI and carotid IMT were significantly larger for the maximum home SBP than the mean home SBP. In multivariate regression analyses, the maximum home SBP was independently associated with LVMI and carotid IMT, regardless of the mean home BP level. In the prediction of left ventricular hypertrophy and carotid atherosclerosis, the goodness-of-fit of the model was significantly improved when the maximum home SBP was added to the sum of the mean office and home BPs (P=0.002 and P<0.001, respectively). These findings indicate that assessment of the maximum home SBP, in addition to the mean home SBP, might increase the predictive value of hypertensive TOD in the heart and artery.
See Editorial Commentary, pp 1041–1042
It has been believed that transient increases in blood pressure (BP) might be construed as noise and merely an obstacle to reliable estimation of usual BP (conceived as the true underlying average BP over a period of time). In this case, such increases would result in substantial underestimation of the strength of the real association between usual BP and cardiovascular risk, a so-called “regression dilution bias.”1 Rothwell et al2 recently showed that the maximum systolic BP (SBP) reached in an office setting was a strong predictor of cardiovascular events, independently of the mean SBP over 12 to 36 months. Ko et al3 also showed that the maximum SBP during the first 72 hours of acute ischemic stroke was strongly associated with the development of brain hemorrhagic transformation, independently of the mean SBP level. Thus, subjects with episodic high BP might be at a high cardiovascular risk.
One drawback of the use of the maximum SBP in routine clinical management of hypertension is that obtaining it requires several office visits over a period of time. One possible way to solve this is to observe the maximum SBP derived from self-measurement at home, because this self-measurement makes it possible to obtain multiple values for BP in a relatively short period under well-controlled conditions. Furthermore, there is an increasing body of evidence that home BP is correlated better with target organ damage (TOD)4–9 and that it may predict cardiovascular events10,11 better than office BP. Therefore, home BP measurement can provide more reliable information on maximum BP in a relatively short period than office BP measurement. However, no studies have investigated the significance of maximum home BP in association with TOD or cardiovascular events.
We hypothesized that the maximum home SBP might reflect more correctly the severity of TOD than the mean home SBP, which has been clearly established as a predictor of TOD and a determinant of cardiovascular prognosis. The aim of the present study was to assess the independent association between the maximum home SBP and TOD in subjects with never-treated hypertension and to test whether the maximum home SBP might improve the prediction of the presence of TOD. In this study, we measured the left ventricular mass index (LVMI) as cardiac damage, the carotid intima-media thickness (IMT) as vascular damage, and the urinary albumin/creatinine ratio (UACR) as renal damage. All three have been established markers of subclinical hypertensive TOD12 and independent predictors of future cardiovascular events.13–15
Methods
Study Participants
Never-treated hypertensive subjects were enrolled consecutively from the Department of Internal Medicine for Outpatients in Miwa Municipal Hospital between June 2004 and December 2007. The subjects in this study were recruited from the same population as those in our recent publication.16 Hypertension was defined as an average office SBP of at least 140 mm Hg and/or diastolic BP (DBP) of at least 90 mm Hg or both at 2 different occasions (with at least a 2-week interval) during the run-in period (4 weeks). Subjects who had secondary hypertension, arrhythmia, a history of heart failure, a history of stroke or coronary artery disease, renal insufficiency (serum creatinine >2 mg/dL), mental disorders, severe noncardiovascular disease, or chronic inflammatory disease were excluded. At baseline, these subjects underwent a medical interview, anthropometric measurements, blood/urine examinations, and ultrasonography. This study was approved by the Institutional Review Board of Miwa Municipal Hospital, and written informed consent was obtained from all participants. See http://hyper.ahajournals.org for further information.
BP Measurements
Office BP was measured during the screening period (twice) and at the end of the home BP measurement term, using the same device as used for home BP. At each office visit, 3 consecutive readings were taken on the nondominant arm with a 15-second interval after a 5-minute rest in a sitting position. Office BP was taken by the study investigators (Y.M. and S.S.) in the morning.
Home BP was measured in a sitting position 3 times each in the morning and evening for 14 consecutive days after the enrollment for this study. The subjects were instructed to place the cuff on the nondominant arm, take a 5-minute rest before the first reading, and take a 15-second interval between the readings. Morning BP was measured within 1 hour after waking, after urination, and before breakfast. Evening BP was measured just before going to bed and at least 60 minutes after taking a bath. These methods are based on Japanese home BP guidelines.17 The device used for home BP was a validated oscillometric device (HEM-747IC; Omron Healthcare Co, Ltd, Kyoto, Japan) that incorporates an integrated circuit memory and clock to store the BP readings and time of measurement.18 The arm circumferences of subjects ranged between 22 and 32 cm, so the standard arm cuff could be used for BP measurements in all cases. Patients who conducted home BP measurement for fewer than 5 consecutive days were excluded from the analysis.
Definition of BP Indices
The maximum home BP was calculated as follows. The average triplicate morning BP and average triplicate evening BP were calculated for each day. The highest among these averages for each individual was adopted as the maximum home BP. The mean home BP was defined as the average of all readings for each individual. “Peak size in home SBP” was defined as the difference between the maximum home SBP and the mean home SBP based on a recent report.19 Day-by-day home BP variability was defined as the SD of home BP (average of morning and evening BPs) for each individual.20,21 The mean office BP was defined as the mean of the office BPs on 3 occasions.
Echocardiography and Carotid Ultrasonography
Ultrasonographic investigations were performed using a high-resolution B-mode ultrasound scanner (EUB 6500; Hitachi, Tokyo, Japan). M-mode echocardiography, guided by 2-dimensional echocardiography, was performed as described previously.16 End diastolic dimensions were used to calculate LVM using an anatomically validated formula.22 The LVMI was calculated from LVM divided by body surface area. The presence of left ventricular hypertrophy (LVH) was defined as LVMI ≥125 g/m2 in men and ≥110 g/m2 in women.12
Carotid IMT was assessed for the right and left common carotid artery and was measured at 3 points proximal to the bilateral carotid bulbus (far wall) in 10-mm segments at the end diastole and always in plaque-free segments. If plaque existed at the IMT measuring point, an appropriate adjacent portion was chosen. The mean of the right and left carotid IMT (totally 6 points) was used in the analyses. Carotid atherosclerosis was diagnosed when there was diffuse common carotid artery thickening defined as an average IMT >0.9 mm.12 Echocardiography and carotid ultrasonography were performed by 2 cardiologists who were unaware of subjects' clinical conditions including the results from home BP measurement. The reproducibility of the measurement of LVMI and carotid IMT using this ultrasonography has been described in previous reports.9,16
Urinary Albumin Excretion
Blood and urine samples were collected in the morning in a fasting state. The urinary albumin level was determined from a spot urine sample using a turbidimetric immunoassay and expressed as UACR (mg/gCr). Urine creatinine was measured by enzymatic assay. All assays were performed at Mitsubishi Biochemical Laboratory (Tokyo, Japan). The intracoefficients and intercoefficients of variation for the urinary albumin assay were 1.30% and 1.85%, respectively. Albuminuria was defined as UACR ≥22 mg/gCr in men and ≥31 mg/gCr in women.12 See supplemental material for the other measurements.
Statistical Analyses
All data are expressed as means±SD or a percentage unless otherwise specified. UACR was log-transformed because of its positively skewed distribution. One-way ANOVA was performed to detect differences among groups, and Tukey's honestly significant differences test was also performed for multiple pairwise comparisons of the means among groups. The χ2 test was used to compare proportions. Analysis of covariance was performed to detect differences among groups after adjustment for covariates, and the Bonferroni test was used for multiple pairwise comparisons. The univariate correlations between the BPs and TODs were assessed using Pearson's correlations. Differences between values of correlation coefficients were compared with Fisher's z tests. The maximum home SBP and mean home SBP could not be included together in the same model, because of their strong correlation (r=0.92, P<0.001) and high degree of multicollinearity (variance inflation factor [VIF] was 7.49 to 7.97 when both variables were included in the same model). Therefore, we performed multivariate linear regression analyses after dividing subjects into 2 groups with mean home BP cut-off values of 135 mm Hg SBP and 85 mm Hg DBP23 to explore independent associations between the maximum home SBP and TODs. Variables significantly correlated with each TOD in the univariate analysis were included in the multivariate regression analyses. To estimate the relationship between BP indices and the presence of TOD, logistic regression analyses were performed. In those analyses, the likelihood ratio test was used to assess the goodness-of-fit between models by adding home BP indices. The null hypothesis was rejected when the 2-tailed P value was <0.05. All statistical analyses were performed with SPSS version 16.0 (SPSS Inc, Chicago, IL).
Results
Characteristics of the Subjects
Characteristics of the study subjects are shown in Table 1. The mean age of the total population was 66.6 years, and 44.7% (n=159) was aged 70 years or older. The average number of home BP measurements per subject during the 14-day study period was 79.8±7.9 (mean±SD). Figure 1 shows the distribution of the days on which the maximum home SBP was measured during the 14-day period. As we expected, the largest number of subjects had maximum home SBP on day 1 (n=71, 19.9%).
| Variable | Total Population (n=356) |
|---|---|
| General characteristics | |
| Age, years | 66.6±11.0 |
| Male sex, % | 47 |
| Body height, cm | 154.9±9.4 |
| Body mass index, kg/m2 | 23.3±3.2 |
| Waist circumference, cm | 82.3±9.2 |
| Hypertension duration, years | 3.2±5.9 |
| Smoking, % | 16 |
| Habitual drinking, % | 28 |
| Diabetes mellitus, % | 9 |
| Hyperlipidemia, % | 31 |
| Hemodynamic parameters | |
| Mean office SBP, mm Hg | 153.2±17.9 |
| Mean office DBP, mm Hg | 84.9±10.5 |
| Mean home SBP, mm Hg | 141.4±17.7 |
| Mean home DBP, mm Hg | 78.6±10.2 |
| Maximum home SBP, mm Hg | 164.3±21.1 |
| Maximum home DBP, mm Hg | 91.1±11.7 |
| Day-by-day home SBP variability, mm Hg | 8.0±2.7 |
| Day-by-day home DBP variability, mm Hg | 4.4±1.6 |
| baPWV, m/sec | 18.2±4.2 |
| TOD | |
| LVMI, g/m2 | 115.3±33.4 |
| Prevalence of left ventricular hypertrophy, % | 42 |
| Carotid IMT, mm | 0.87±0.17 |
| Prevalence of carotid atherosclerosis, % | 37 |
| UACR, mg/gCr | 22.0 (19.5–25.0) |
| Prevalence of albuminuria, % | 33 |
Figure 1. The distribution of the days when the maximum home SBP was observed. M indicates morning; E, evening.
Univariate Correlations Between BP Levels and TODs
In univariate analyses, all SBP measures were significantly correlated with all TODs (Table 2). As shown in Figure 2, the maximum home SBP was strongly and linearly correlated with LVMI and carotid IMT. Even after the BP data at day 1 were excluded, the univariate correlations between home BP indices and TODs were similar (see supplemental Table S1). Next, we compared the correlation coefficients between the maximum home SBP and the mean home SBP; the correlation coefficients were significantly different for LVMI (0.51 versus 0.46, P=0.008) and carotid IMT (0.40 versus 0.31, P<0.001) but not for UACR (0.29 versus 0.30, P=0.65). The morning SBP at day 1 was not more closely correlated with LVMI (r=0.43), carotid IMT (r=0.31), and UACR (r=0.26) than was the mean home SBP (probability for the difference was 0.32, 0.90, and 0.18, respectively).
| Variable | LVMI | Carotid IMT | Log UACR | |||
|---|---|---|---|---|---|---|
| r | P | r | P | r | P | |
| Mean office SBP, mm Hg | 0.41 | <0.001 | 0.24 | <0.001 | 0.29 | <0.001 |
| Mean office DBP, mm Hg | 0.05 | 0.34 | 0.03 | 0.56 | 0.05 | 0.34 |
| Mean home SBP, mm Hg | 0.46 | <0.001 | 0.31 | <0.001 | 0.30 | <0.001 |
| Mean home DBP, mm Hg | 0.13 | 0.02 | 0.09 | 0.10 | 0.08 | 0.15 |
| Maximum home SBP, mm Hg | 0.51 | <0.001 | 0.40 | <0.001 | 0.29 | <0.001 |
| Maximum home DBP, mm Hg | 0.23 | <0.001 | 0.13 | 0.012 | 0.08 | 0.16 |
| Day-by-day home SBP variability, mm Hg | 0.31 | <0.001 | 0.23 | <0.001 | 0.20 | <0.001 |
| Day-by-day home DBP variability, mm Hg | 0.22 | <0.001 | 0.10 | 0.07 | 0.06 | 0.29 |
Figure 2. Univariate correlation between the maximum home SBP and left ventricular mass index (A), carotid IMT (B), and Log UACR (C) in 356 hypertensive patients. SBP indicates systolic blood pressure; LVMI, left ventricular mass index; IMT, intima-media thickness; UACR, urinary albumin/creatinine ratio.
Multivariate Analyses Between Maximum Home SBP and TOD
Table 3 shows the results of the multivariate linear regression analyses that determined the independent association of the maximum home SBP with TODs in the total population and subgroups divided by the mean home BP level of 135/85 mm Hg. We did not observe any multicollinearity in any models; VIF was <1.8 in all models. The maximum home SBP was independently associated with the LVMI and carotid IMT in all groups, even after adjustment for significant covariates including age, sex, and mean office SBP. On the other hand, the maximum home SBP was independently associated with the UACR in the total population, but not in either subgroup. When the BP data at day 1 were excluded, these results were essentially the same (data not shown). As shown in supplemental Table S2, day-by-day home SBP variability was significantly associated with LVMI, but not with carotid IMT or UACR, after adjustments for covariates including the mean home SBP.
| Dependent Variable | Total Population (n=356) | Subgroup Analysis | ||||
|---|---|---|---|---|---|---|
| Mean Home BP <135/85 mm Hg (n=135) | Mean Home BP ≥135/85 mm Hg (n=221) | |||||
| β (SE) | P | β (SE) | P | β (SE) | P | |
| LVMI*, g/m2 | ||||||
| Maximum home SBP, mm Hg | 0.598 (0.094) | <0.001 | 0.512 (0.188) | 0.007 | 0.655 (0.145) | <0.001 |
| Model R2=0.32 | Model R2=0.21 | Model R2=0.24 | ||||
| Carotid IMT†, mm | ||||||
| Maximum home SBP, mm Hg | 0.003 (<0.001) | <0.001 | 0.003 (0.001) | 0.006 | 0.003 (0.001) | <0.001 |
| Model R2=0.27 | Model R2=0.26 | Model R2=0.24 | ||||
| Log UACR‡, mg/gCr | ||||||
| Maximum home SBP, mm Hg | 0.004 (0.002) | 0.02 | 0.001 (0.003) | 0.68 | 0.003 (0.002) | 0.18 |
| Model R2=0.20 | Model R2=0.15 | Model R2=0.17 | ||||
Goodness-of-Fit by Adding Home SBP Indices
Table 4 shows the goodness-of-fit of various models. Each prediction model for the presence of LVH, carotid atherosclerosis, and albuminuria was significantly improved when the mean home SBP was added to model 1 based on the mean office SBP, as indicated by the likelihood ratio test (P<0.001, P=0.002, and P=0.006, respectively). Furthermore, in predicting the presence of LVH and carotid atherosclerosis, the model fit was significantly improved when the maximum home SBP was added to model 2 (P=0.002 and P<0.001, respectively). In models including maximum home SBP, the mean home SBP turned out to be not significant (P=0.32) in the prediction of LVH, and the office SBP turned out to be not significant (P=0.54) in the prediction of carotid atherosclerosis. On the other hand, in predicting the presence of albuminuria, model improvement was not observed when the maximum home SBP was added to model 2 (P=0.11).
| TOD | Model | −2 Log Likelihood | Likelihood Ratio (χ2 on df 1) | P |
|---|---|---|---|---|
| LVH | Model 1. Mean office SBP | 431.2 | – | – |
| Model 2. Model 1 +mean home SBP | 418.6 | 12.6 | <0.001 | |
| Model 3. Model 2 +maximum home SBP | 408.8 | 9.8 | 0.002 | |
| Carotid Atherosclerosis | Model 1. Mean office SBP | 453.6 | – | – |
| Model 2. Model 1 +mean home SBP | 443.8 | 9.8 | 0.002 | |
| Model 3. Model 2 +maximum home SBP | 420.6 | 23.2 | <0.001 | |
| Albuminuria | Model 1. Mean office SBP | 428.7 | – | – |
| Model 2. Model 1 +mean home SBP | 421.3 | 7.4 | 0.006 | |
| Model 3. Model 2 +maximum home SBP | 418.7 | 2.6 | 0.11 |
Characteristics of the Subjects With Increased Peak Size of Home SBP
We divided all subjects into 3 groups (Q1, Q2, and Q3) according to the peak size in home SBP to clarify the characteristics of subjects with a greater rise of maximum home SBP from mean SBP levels (see supplemental Table S3). The Q2 and Q3 groups, with the highest peaks, were significantly older than the Q1 group, and the Q3 group had a higher proportion of habitual drinkers than the Q1 group. The Q3 group had a higher brachial-ankle pulse-wave velocity (baPWV), LVMI, and carotid IMT than the other groups, and these differences were still significant in relation to the Q1 group after adjusting for age, sex, hypertension duration, habitual drinking, and the mean office SBP (P=0.005, P=0.001, and P=0.003, respectively). In a multivariate regression analysis, age (β=0.109, SE=0.045, P=0.01), habitual drinking (β=2.365, SE=1.164, P=0.04), and baPWV (β=0.004, SE=0.001, P=0.001) were significant determinants of the peak size in home SBP, whereas sex, hypertension duration, and mean office SBP level were not.
Discussion
The important findings of this study were that (1) the maximum home SBP was better correlated with LVMI and carotid IMT than the mean home SBP; (2) the maximum home SBP was independently associated with LVMI and carotid IMT, even when the mean home BP level was normal; and (3) for the presence of LVH and carotid atherosclerosis, the maximum home SBP provided additional predictive value to the mean levels of office SBP and home SBP. This is the first study to demonstrate the clinical implications of the maximum home SBP in untreated hypertensive patients.
The present study demonstrated that the maximum home SBP value was more closely associated with LVMI and carotid IMT than the mean home SBP, despite previous reports that the reliability of home BP as a predictor of cardiovascular disease was improved by averaging more measurements.4,10 In the present study, the maximum home SBP was most commonly reported on the first day. Even after the exclusion of day 1 BP data, the close associations between the maximum home SBP and LVMI/carotid IMT were essentially the same. Although the maximum home SBP differs from BP variability in that it refers specifically to transient changes in BP, these 2 variables often have similar associations with other clinical indices, such as arterial stiffness and baroreceptor dysfunction.1,24,25 In the present study, age and PWV, both of which may be involved in the impairment of the arterial baroreflex,26,27 were independent determinants of the size of the maximum home SBP. Thus, a baroreceptor dysfunction could be potentially involved in the mechanisms of larger-value maximum home SBP. Because a baroreceptor dysfunction itself has been reported to be associated with LVH27 and carotid atherosclerosis,28 this might underlie the close associations between maximum home SBP and cardiac/vascular damage. Whether the maximum home SBP has a pathogenetic role in the progression of TOD or is just a secondary phenomenon of subclinical vascular damage remains to be determined.
The current results showed that the maximum home SBP did not improve information about potential kidney damage inherent in the mean home SBP level. This finding might indirectly coincide with previous reports that have reported a relatively weak association between awake SBP variability and albuminuria, in contrast to the strong associations between SBP variability and LVMI or carotid IMT.24,29 Furthermore, Lantelme et al27 reported that no significant correlation between baroreceptor sensitivity and albuminuria was observed, despite a significant correlation between SBP variability and LVMI. An experimental study using the rat kidney model has demonstrated that renal autoregulation could prevent acute exaggerated BP fluctuations from being transmitted to the glomerular capillary circulation and attenuate glomerular injury.30 These findings indicate that the kidney might not be affected by a transient increase in BP, as long as autoregulatory mechanisms are normally functioning.
In the present study, subjects with increased peak size of home SBP were characterized by older age and habitual drinking. These results are similar to previous reports, which demonstrated that both older age and excessive use of alcohol were significant determinants of home SBP variability, defined as either the variability between morning and evening SBP values16,20 or day-by-day SBP values.20,21 Aging was reported to contribute to decreased baroreceptor sensitivity,26 and this mechanism can explain transient BP increases observed in the elderly. We have reported that repeated alcohol intake in the evening causes an elevation in morning BP and a reduction in late evening BP.31 This biphasic effect could increase the maximum home BP level in the morning, but not the mean home BP levels31; that is, it could lead to an increased level of peak size in home SBP.
It has been reported that day-by-day home SBP variability32 and visit-to-visit office SBP variability2,33 are significant predictors of cardiovascular events, independent of the mean SBP level. In the present study, day-by-day home SBP variability was a significant determinant of LVMI, even after adjustments for covariates including mean home SBP. This is the first study to demonstrate an independent association between day-by-day home SBP variability and TOD. On the other hand, day-by-day home SBP variability was not an independent determinant of carotid IMT. Our results suggest that carotid atherosclerosis might be more strongly associated with transient BP fluctuations (BP instability) than with day-by-day BP variability, which reflects typical fluctuations.
Study Limitations
First, the directional nature of the cause-and-effect relationship between the maximum home SBP and TODs remains to be clarified because the present study was cross-sectional. Second, the reproducibility of the maximum home SBP is unknown, whereas the maximum office SBP was reproducible and not a random phenomenon.19 Third, the quality of the measurement procedure could have affected the maximum home BP value, although we asked participants to measure BP under controlled conditions. Fourth, whether the maximum BP obtained by 14 days of home BP monitoring is a reflection of short-term BP variability or long-term BP variability remains to be clarified. Finally, although the latest home BP guideline23 recommends a 1-minute interval between readings, in the present study, we set the interval at 15 seconds34 to improve the patients' compliance with home BP measurement.
Perspectives
Our study suggests that transiently high BP readings at home are not disregarded as noise, but rather should be taken seriously as meaningful indicators for hypertensive TOD in the heart and artery. These findings also indicate the importance of monitoring the severity of the maximum home SBP, in addition to mean home BP levels, at the first evaluation of hypertension. Further investigation is needed to evaluate the physiological mechanisms of exaggerated fluctuations in home BP and to prospectively assess the clinical implications of this BP phenomenon.
Sources of Funding
This study was supported in part by a research grant from
Disclosures
None.
Footnotes
References
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