Abstract

Background:

Home blood pressure (HBP) monitoring plays an increasingly important role in the diagnosis and treatment of hypertension. We evaluated the independent value of HBP compared with ambulatory blood pressure (ABP) and office blood pressure (OBP) in the prediction of cardiovascular end-organ damage in normotensive subjects and untreated patients with mild hypertension.

Methods:

One hundred sixty-three subjects underwent measurements of OBP, HBP, ABP, and echocardiography. A physician using a mercury-column sphygmomanometer performed three OBP measurements. The ABP was recorded using a noninvasive ambulatory monitor (mean, 35.4 awake readings per subject). Participants took HBP readings with an automatic, oscillometric device over a 10-week period (mean, 277.9 readings per subject). The left-ventricular mass index (LVMI) was calculated from measurements obtained from two-dimensionally guided M-mode or linear tracings on echocardiography.

Results:

For systolic and diastolic blood pressures (SBP/DBP), the correlation coefficients of the LVMI with OBP, awake ABP, and HBP were 0.29/0.27, 0.41/0.26, and 0.47/0.35, respectively (all P < .01). In a multivariate regression analysis in which age, sex, body mass index, OBP, awake ABP, and HBP were included, only age, sex, and HBP were significant predictors of LVMI. When only the first 12 home readings were used, the superiority of HBP was no longer evident.

Conclusions:

In contrast to OBP and ABP, HBP measurements, when averaged over a 10-week period, are independently related to LVMI. The HBP adds prognostic information over and above OBP and ABP in the prediction of cardiovascular end-organ damage, but this relationship appears to depend on the number of readings taken. Am J Hypertens 2007;20: 476–482 © 2007 American Journal of Hypertension, Ltd.

Elevated blood pressure is a strong, independent risk factor for incident cardiovascular disease.1 The bulk of our knowledge about the prognostic value of elevated blood pressure is based on the traditional method of taking auscultatory measurements in a clinical setting. However, there is evidence that ambulatory blood pressure (ABP) is a better predictor of target end-organ damage and cardiovascular events than office blood pressure (OBP) in the general population as well as in hypertensive patients.2–4 Thus, it is generally accepted that ABP monitoring (ABPM) is a superior method of blood-pressure assessment, and is increasingly viewed as the “gold standard” for clinical practice.5

Another method of measuring blood pressure is by self-monitoring at home. The risks of target end-organ damage6 and cardiovascular events7 are more strongly correlated with home blood pressure (HBP) than with OBP measurements. Although ABP was proposed as the best measure of target-organ damage, ABPM is expensive and impractical for most patients. These limitations, however, are far less applicable to HBP monitoring.8

Although ABP and HBP both appear to be related to the left-ventricular mass index (LVMI), a marker of cardiovascular end-organ damage,6,9,10 only one previous study in moderately to severely hypertensive patients (a group already at increased cardiovascular risk) examined the independent predictive utility of these measures vis à vis their relationship to LVMI.11 Before HBP monitoring can be routinely recommended for blood-pressure assessment, the relative predictive value of HBP in comparison to ABP needs to be assessed in a broader group of individuals.

Therefore, the aim of the present study was to assess the relative utility of HBP, ABP, and OBP measurements for the prediction of elevated LVMI in mildly hypertensive patients and normotensive individuals.

Methods

Study Population

This study was conducted as part of an investigation of psycho behavioral mechanisms of white-coat hypertension.12,13 Briefly, patients with stage 1 hypertension (140–159 mmHg/90–99 mmHg), according to Joint National Committee (JNC) VI criteria, were recruited initially from the Weill Cornell Hypertension Center of New York Presbyterian Hospital (New York, NY), and later from the Mount Sinai Medical Center (New York, NY). Normotensive participants were recruited through advertisements. For this study, participants were eligible if they: 1) were aged between 18 and 80 years; 2) were willing, with a physician's permission, to come off antihypertensive medication for 2 weeks prior to the first study visit, and remain off for the duration of the study; and 3) had no history of overt cardiovascular disease.

In total, 329 participants were enrolled between June 1998 and August 2003. Those recruited prior to May 15, 2002, or between November 20, 2002, and February 15, 2003, had an opportunity to have an echocardiogram (N = 233). Two hundred and eleven subjects had usable OBP, ABP, and HBP data, and 177 (83.9%) of these had an echocardiogram to assess their LVMI. Compared with the 34 nonparticipants who did not have an echocardiogram, the 177 participants were more likely to be women (60.5% of participants v 50.0% of nonparticipants, P = .047). However, there were no differences in age (P = .25) or body mass index (BMI; P = .50) between the two groups. The LVMI could not be determined from 14 of 177 echocardiograms due to poor acoustic penetration, resulting in 163 participants who are the focus of the present report. Written informed consent was obtained from all subjects, and the study was approved by the Institutional Review Boards of the Weill Medical College of Cornell University and the Mount Sinai School of Medicine.

Blood Pressure Assessments

Participants attended visits on two consecutive days (day 1 and day 2). Starting on day 1, ABP measurements were performed using an oscillometric SpaceLabs ABP monitor (Model 90207, Redmond, WA) over a period of 36 h. For about three-quarters of the recordings, the ABPM was programmed to take a blood-pressure reading every 30 min throughout the monitoring period. For the remaining recordings, measurements were taken at 15-min intervals, between 6 AM and 10 PM, and every 30 min between 10 PM and 6 AM. For the purposes of this study, the analyses of ABP readings were restricted to the first 24 h of monitoring, because most of the published studies examining the relationship of LVMI with both ABP and HBP utilized 24-h ABPM.6,9,10 The definitions of awake and sleep systolic blood-pressure (SBP) and diastolic blood-pressure (DBP) levels were based on diary reports of the times subjects woke up and went to sleep. The mean numbers of valid measurements used to compute the mean awake and sleep ABP were 35.4 ± 12.7 and 14.9 ± 4.0, respectively.

The subject, still wearing the ABP monitor, returned the next day (day 2), and physician-obtained OBP readings were taken. The participant was escorted into an examination room and rested for at least 5 min, after which the physician entered and took three OBP measurements using a mercury-column sphygmomanometer and stethoscope.

After the initial ABP recording, HBP was measured over a 10-week period using an Omron HEM-747 IC (an automatic, oscillometric HBP monitor; Omron Health Care, Vernon Hills, IL), which was previously validated.14–16 The patients were instructed to take three HBP measurements, 4 days a week, in the morning and evening. They were also asked to take three additional measurements on two occasions (at midmorning and midafternoon), 2 days a week, for a total of 36 measurements per week. The mean number of valid HBP readings per subject was 277.9 ± 111.2.

Subjects were additionally classified as hypertensive by OBP, ABP, and HBP measurements. Office hypertension was defined as SBP ≥140 mm Hg or DBP ≥90 mm Hg. Ambulatory hypertension (based on mean awake blood pressure) and home hypertension were both defined as SBP ≥135 mm Hg or DBP ≥85 mm Hg, which are internationally accepted limits.17,18

Measurement of Cardiovascular End-Organ Damage: Left-Ventricular Mass Index

M-mode and two-dimensional echocardiograms were performed approximately 10 weeks after the initial assessment visits. Researchers blinded to patients’ clinical characteristics performed left-ventricular measurements from two-dimensionally guided M-mode tracings according to the recommendations of the American Society of Echocardiography.19 If an M-mode tracing was technically inadequate, linear measurements were performed from the two-dimensional study.20 Up to six echocardiographic cycles were measured and averaged. Left ventricular mass (LVM) was calculated using the corrected American Society of Echocardiography formula: 0.8 × (1.04 × [(interventricular septum thickness in diastole + left ventricular internal dimension in diastole + posterior wall thickness in diastole)3 − left ventricular internal dimension in diastole3]) + 0.6. The LVM index (LVMI) was calculated by dividing LVM by the estimated body surface area, calculated from height and weight. The LVMI was also used to identify subjects with left-ventricular hypertrophy (LVH), defined as LVMI ≥125 g/m2 for men and ≥110 g/m2 for women, as previously described.21

Statistical Analyses

Results are presented as mean ± SD. Fisher's exact test and independent-samples t-tests were used to compare proportions and means, respectively. Paired t-tests were used to test for differences in mean levels of the various blood-pressure measures. Pearson correlations were used to assess the associations of OBP, ABP, and HBP measurements with LVMI. To assess the independent predictive utility of the different blood-pressure measurements, multiple regression models were estimated, including age, sex, and BMI as covariates, and the blood-pressure measurements as primary predictors. Separate analyses were performed for SBP and DBP. Variance inflation factors were calculated to examine the possible existence of substantial multicollinearity among the predictors. The validity of the regression model's inferential statistics was assessed using the bootstrap technique.22,23 One thousand random bootstrap samples were drawn (with replacements) from the full sample. Statistical significance was defined by α = 0.05, two-tailed. Statistical analyses were performed using SPSS version 11 (SPSS, Inc., Chicago, IL) and SAS version 8.2 (SAS Institute, Cary, NC).

Results

Table 1 shows the characteristics of the study participants. There were significant differences among the blood-pressure measures (OBP, awake ABP, sleep ABP, and HBP) for both SBP (P < .001) and DBP (P < .001). The t-tests indicated that HBP measurements were significantly lower than both OBP and awake ABP measurements. There were no significant differences in SBP or DBP between the OBP and awake ABP measurements. Sleep ABP levels were significantly lower than HBP, OBP, and awake ABP.

Table 1

Sample characteristics*

Characteristics Total sample (N = 163) 
Age (y) 53.9 ± 14.5 
Sex (% women) 60.1 
Race  
 % White (non-Hispanic) 66.3 
 % White (Hispanic) 8.6 
 % Black (non-Hispanic) 13.5 
 % Black (Hispanic) 0.6 
 % Asian/Indian/Pacific Islander 6.1 
 % Native American/Alaskan Native 0.6 
 % other 4.3 
Body mass index (kg/m225.9 ± 4.9 
Office  
 Systolic blood pressure (mm Hg) 134 ± 21 
 Diastolic blood pressure (mm Hg) 83 ± 12 
 % hypertensive 46.0 
Ambulatory (awake)  
 Systolic blood pressure (mm Hg) 134 ± 14 
 Diastolic blood pressure (mm Hg) 82 ± 10 
 % hypertensive 57.1 
Ambulatory (sleep)  
 Systolic blood pressure (mm Hg) 119 ± 14 
 Diastolic blood pressure (mm Hg) 69 ± 11 
Home  
 Systolic blood pressure (mm Hg) 130 ± 16§ 
 Diastolic blood pressure (mm Hg) 79 ± 10§ 
 % hypertensive 42.3 
Left-ventricular mass (g) 145 ± 46 
Left-ventricular mass index (g/m278.6 ± 18.7 
Characteristics Total sample (N = 163) 
Age (y) 53.9 ± 14.5 
Sex (% women) 60.1 
Race  
 % White (non-Hispanic) 66.3 
 % White (Hispanic) 8.6 
 % Black (non-Hispanic) 13.5 
 % Black (Hispanic) 0.6 
 % Asian/Indian/Pacific Islander 6.1 
 % Native American/Alaskan Native 0.6 
 % other 4.3 
Body mass index (kg/m225.9 ± 4.9 
Office  
 Systolic blood pressure (mm Hg) 134 ± 21 
 Diastolic blood pressure (mm Hg) 83 ± 12 
 % hypertensive 46.0 
Ambulatory (awake)  
 Systolic blood pressure (mm Hg) 134 ± 14 
 Diastolic blood pressure (mm Hg) 82 ± 10 
 % hypertensive 57.1 
Ambulatory (sleep)  
 Systolic blood pressure (mm Hg) 119 ± 14 
 Diastolic blood pressure (mm Hg) 69 ± 11 
Home  
 Systolic blood pressure (mm Hg) 130 ± 16§ 
 Diastolic blood pressure (mm Hg) 79 ± 10§ 
 % hypertensive 42.3 
Left-ventricular mass (g) 145 ± 46 
Left-ventricular mass index (g/m278.6 ± 18.7 
*

Data are expressed as percentage or mean ± SD

Defined by systolic blood pressure ≥140 or diastolic blood pressure ≥90

Defined by systolic blood pressure ≥135 or diastolic blood pressure ≥85

§

P < .001 v OBP, and v awake ABP

P < .001 vs. OBP, v awake ABP, and v HBP.

Relationships Between Blood Pressure Levels and Cardiovascular End-Organ Damage

The correlation coefficients of LVMI with OBP, awake ABP, sleep ABP, and HBP were 0.29/0.27 (SBP/DBP; P < .001), 0.41/0.26 (SBP/DBP; P < .001 for SBP and P < .01 for DBP), 0.32/0.18 (SBP/DBP; P < .001 for SBP and P = .02 for DBP), and 0.47/0.35 (SBP/DBP; P < .001), respectively. For SBP, the correlations of LVMI with awake ABP and HBP did not differ significantly, but both were significantly greater than the correlation of LVMI with OBP (P < .05 for the ABP and OBP comparison; P < .01 for the HBP and OBP comparison). However, the correlation of LVMI with sleep ABP was significantly lower than with HBP (P < .01) and was not significantly different than with OBP. For DBP, none of the differences among the correlations of LVMI with awake ABP, HBP, and OBP was significant. Further, the correlation of LVMI with sleep ABP was significantly lower than its correlation with HBP (P < .01).

Separate age-, sex-, and BMI-adjusted models were examined for each of the blood-pressure measures. Each blood-pressure measure was a significant predictor of LVMI, independent of age, sex, and BMI: OBP, P = .01 for SBP, P < .01 for DBP; awake ABP, P < .01 for SBP and DBP; and HBP, P < .01 for SBP and DBP>. The percentages of variance in LVMI that were predicted by age, sex, BMI, and each of the blood-pressure measures are shown in Table 2 (models 1–7). Sleep systolic ABP (data not shown in Table 2) was also a significant predictor (P = .02) of LVMI, independent of age, sex, and BMI (R2 = .21). Sleep diastolic ABP was not a significant predictor of LVMI (P = .22) after adjusting for age, sex, and BMI.

Table 2

Variance in LVMI explained by age, sex, body mass index, office, awake ambulatory, and home blood-pressure levels

Model R2 P value 
1. Age, sex, and body mass index 0.15 <.001 
2. Age, sex, body mass index, and office SBP 0.19* <.001 
3. Age, sex, body mass index, and awake ambulatory SBP 0.24 <.001 
4. Age, sex, body mass index, and home SBP 0.27 <.001 
5. Age, sex, body mass index, and office DBP 0.19 <.001 
6. Age, sex, body mass index, and awake ambulatory DBP 0.20 <.001 
7. Age, sex, body mass index, and home DBP 0.21 <.001 
8. Age, sex, body mass index, office SBP, and awake ambulatory SBP 0.24 <.001 
9. Age, sex, body mass index, office SBP, awake ambulatory SBP, and home SBP 0.28§ <.001 
10. Age, sex, body mass index, office DBP, and awake ambulatory DBP 0.20 <.001 
11. Age, sex, body mass index, office DBP, awake ambulatory DBP, and home DBP 0.23 <.001 
Model R2 P value 
1. Age, sex, and body mass index 0.15 <.001 
2. Age, sex, body mass index, and office SBP 0.19* <.001 
3. Age, sex, body mass index, and awake ambulatory SBP 0.24 <.001 
4. Age, sex, body mass index, and home SBP 0.27 <.001 
5. Age, sex, body mass index, and office DBP 0.19 <.001 
6. Age, sex, body mass index, and awake ambulatory DBP 0.20 <.001 
7. Age, sex, body mass index, and home DBP 0.21 <.001 
8. Age, sex, body mass index, office SBP, and awake ambulatory SBP 0.24 <.001 
9. Age, sex, body mass index, office SBP, awake ambulatory SBP, and home SBP 0.28§ <.001 
10. Age, sex, body mass index, office DBP, and awake ambulatory DBP 0.20 <.001 
11. Age, sex, body mass index, office DBP, awake ambulatory DBP, and home DBP 0.23 <.001 

DBP = diastolic blood pressure; LVMI = left-ventricular mass index; SBP = systolic blood pressure.

*

P = .01 v model 1

P < .01 v model 1

P = .001 v model 2

§

P = .004 v model 8

P = .02 v model 10.

A multiple regression model (Table 3) was then estimated predicting LVMI from age, sex, BMI, and all three blood-pressure measures (OBP, ABP, and HBP). Because the relationship of LVMI with awake ABP appeared to be stronger than with sleep ABP in our study, awake ABP was used in this model. As Table 3 shows, age and sex were significant predictors of LVMI when controlling for all other predictors. Of the blood-pressure measures, only HBP (SBP and DBP) emerged as a significant independent predictor of LVMI. The variance inflation factors for OBP, awake ABP, and HBP ranged from 1.97 to 3.69 (both SBP and DBP), indicating no strong evidence of multicollinearity among the predictors.23 As expected, the bootstrap analysis resulted in larger estimates of standard errors and somewhat weaker P values. Nevertheless, the conclusions were similar for SBP (P = .01 for age, P = .02 for sex, P = .19 for BMI, P = .25 for OBP, P = .49 for awake ABP, and P = .02 for HBP) and DBP (P < .001 for age, P = .004 for sex, P = .06 for BMI, P = .69 for OBP, P = .65 for awake ABP, and P = .09 for HBP), although diastolic HBP was not quite statistically significant.

Table 3

Regression analysis for predictors of LVMI

 Unstandardized coefficient Standardized coefficient     
 SE Beta t P value 
 SBP DBP SBP DBP SBP DBP SBP DBP SBP DBP 
Age 0.24 0.36 0.10 0.09 0.19 0.28 2.44 3.83 0.02 <0.001 
Sex −6.32 −7.60 2.74 2.80 −0.17 −0.20 −2.31 −2.72 0.02 .007 
BMI 0.35 0.49 0.28 0.28 0.09 0.13 1.24 1.74 0.22 .08 
OBP −.11 0.07 0.09 0.16 −0.12 0.04 −1.15 0.42 0.25 .67 
Awake ABP 0.13 −0.11 0.17 0.25 0.10 −0.05 0.76 −0.43 0.45 .67 
HBP 0.45 0.58 0.16 0.24 0.38 0.31 2.92 2.42 0.004 .02 
 Unstandardized coefficient Standardized coefficient     
 SE Beta t P value 
 SBP DBP SBP DBP SBP DBP SBP DBP SBP DBP 
Age 0.24 0.36 0.10 0.09 0.19 0.28 2.44 3.83 0.02 <0.001 
Sex −6.32 −7.60 2.74 2.80 −0.17 −0.20 −2.31 −2.72 0.02 .007 
BMI 0.35 0.49 0.28 0.28 0.09 0.13 1.24 1.74 0.22 .08 
OBP −.11 0.07 0.09 0.16 −0.12 0.04 −1.15 0.42 0.25 .67 
Awake ABP 0.13 −0.11 0.17 0.25 0.10 −0.05 0.76 −0.43 0.45 .67 
HBP 0.45 0.58 0.16 0.24 0.38 0.31 2.92 2.42 0.004 .02 

ABP = ambulatory blood pressure; BMI = body mass index; DBP = diastolic blood pressure; HBP = home blood pressure; LVMI = left-ventricular mass index; OBP = office blood pressure; SBP = systolic blood pressure.

Predictors with significant P values are in bold type.

To determine the incremental variation in LVMI accounted for by HBP, over and above OBP and awake ABP, a multivariate regression model was estimated that included age, sex, and BMI in the first step, OBP in the second step, awake ABP in the third step, and HBP in the final step (see Table 2, models 8–11). For SBP only, awake ABP was statistically significant when added to the model that included age, sex, BMI, and OBP. For both SBP and DBP, HBP was statistically significant when added to the model that included age, sex, BMI, OBP, and awake ABP.

Table 4 shows the number and percentage of patients who had LVH according to the presence of office, ambulatory, and home hypertension. The LVH was significantly more common in subjects who had home hypertension compared with subjects who had normal HBP levels (10.1% v 2.1%). In contrast, the associations of LVH with office and ambulatory hypertension were not statistically significant.

Table 4

Associations of LVH with office, ambulatory, and home hypertension

 Office hypertension* Awake ambulatory hypertension Home hypertension 
 Yes (n = 75) No (n = 88) Yes (n = 93) No (n = 70) Yes (n = 69) No (n = 94) 
LVH       
 Present 6 (8.0%) 3 (3.4%) 6 (6.5%) 3 (4.3%) 7 (10.1%) 2 (2.1%) 
 Absent 69 (92.0%) 85 (96.6%) 87 (93.5%) 67 (95.7%) 62 (89.9%) 92 (97.9%) 
P value .30 .73 .04 
 Office hypertension* Awake ambulatory hypertension Home hypertension 
 Yes (n = 75) No (n = 88) Yes (n = 93) No (n = 70) Yes (n = 69) No (n = 94) 
LVH       
 Present 6 (8.0%) 3 (3.4%) 6 (6.5%) 3 (4.3%) 7 (10.1%) 2 (2.1%) 
 Absent 69 (92.0%) 85 (96.6%) 87 (93.5%) 67 (95.7%) 62 (89.9%) 92 (97.9%) 
P value .30 .73 .04 

LVH = left-ventricular hypertrophy.

*

Defined by systolic blood pressure ≥140 or diastolic blood pressure ≥90

Defined by systolic blood pressure ≥135 or diastolic blood pressure ≥85

Fisher's exact test.

To determine whether findings would be similar with a smaller number of HBP readings, post hoc analyses were performed with the HBP levels averaged over the first 12 assessments. Both home SBP and DBP were significantly correlated with LVMI (r = .34, P < .001 for SBP; r = .22, and P = .006 for DBP), but these correlations were lower than those for the full set of home readings and for awake ABP. In the multivariate regression analysis including age, sex, BMI, and the three SBP measures (office, awake ambulatory, and home), age (P = .02), sex (P = .01), BMI (P = .04), and ABP levels (P = .006) were significant predictors of increased LVMI. In the analysis that included the three DBP measures, age (P < 0.001), sex (P = .007), and BMI (P = .03) were the only significant predictors. The OBP and HBP were not significant independent predictors of LVMI for either SBP (P = .72 for office; P = .72 for home) or DBP (P = .23 for office; P = .96 for home). Further, awake ambulatory DBP (P = .18) was not a significant independent predictor of LVMI. Finally, when the diagnosis of home hypertension was based on the average of 12 readings, there was no longer a significant association between LVH and home hypertension (P = .17).

Discussion

The results of our study show that HBP, measured over a 10-week period, was an independent predictor of LVMI after adjusting for age, sex, BMI, OBP, and awake ABP. In contrast, neither OBP nor awake ABP was independently related to LVMI. In addition, a diagnosis of hypertension based on HBP monitoring was related to echocardiographic LVH, while diagnoses based on ABPM and OBP were not.

Other investigators found that ABP and HBP are both correlated with LVMI.6,9,10 However, these studies did not examine whether these measures are redundant or independent in their relationship with LVMI. Our findings confirm the correlations reported in these earlier studies, but suggest that while awake ambulatory SBP has independent prognostic value over and above OBP, only HBP (for both SBP and DBP) is independently associated with an increased risk of cardiovascular end-organ damage over and above OBP and ABP. Thus, when sufficient numbers of readings are taken, HBP may be a better indicator than ABP or OBP of cardiovascular end-organ damage. Our results are consistent with data published by Jula et al,11 who found that HBP, measured twice, two times a day for seven consecutive days (total of 28 readings), was independently associated with LVMI after adjusting for age, sex, OBP, and various ABP measurements in patients with moderate to severe hypertension. Our study sample consisted of normotensive participants and mild hypertensive patients, indicating that the superior predictive value of HBP over ABP and OBP for cardiovascular end-organ damage may generalize to a broader population.

In the Ohasama Study, the first to establish the prognostic value of home readings, the prediction of risk of stroke became stronger with more home readings; the highest predictive value was found with a minimum of 14 and an average of 25 measurements.24 Similarly, a recently published systematic review conducted by Verberk et al8 concluded that the minimum number of home measurements needed to obtain a reliable estimate of a subject's usual blood pressure is 12 (ie, two in the morning and two in the evening for three consecutive days). Our findings that significant correlations were observed between HBP and LVMI, even when HBP was analyzed using the first 12 readings, are supportive of these conclusions. However, in this latter scenario, HBP was no longer independently predictive of LVMI, over and above OBP and ABP. With the full set of HBP measurements, we speculate that HBP was the only independent predictor of increased LVMI, because the mean number of HBP readings, and therefore the resultant measurement reliability, was substantially greater than the number of ABP and OBP readings.

Our results are at odds with a recent report from the Pressioni Arteriose Monitorate e Loro Associazioni (PAMELA) Study.25 Although HBP in the PAMELA Study was determined by averaging only two measurements, there was an increasing risk of cardiovascular death in subjects in whom HBP and ABP were normal to those with elevations in one or both blood pressure levels, suggesting that HBP and ABP have independent predictive values. It is likely that the prognostic value of HBP monitoring increases progressively with the number of measurements. Thus, the minimum number of HBP readings needed to maintain at least an equivalent predictive value compared with ABP is unclear and should be further investigated. This question is particularly relevant, because HBP monitoring, based on hundreds of readings over a 10-week period, as performed in our study, may be considered impractical for many patients. However, the device we used did not require the subject to write down the readings, and monitors now being developed have memories that can accommodate several hundred readings. Therefore, this is less likely to be an issue in the future. Further, the minimum number of HBP readings is also likely to be dependent on the study sample and machine characteristics. Study subjects better trained in HBP monitoring, a sample with less day-to-day variability, or a more reliable machine, may reduce the number of HBP measurements required.

Home blood-pressure monitoring is an economical and widely available method of blood-pressure assessment. Many HBP monitors have passed the British Hypertension Society and American Association of Medical Instrumentation validation criteria.14,26,27 The monitors are easy to use, because oscillometric measurement algorithms are used, which do not require locating the subject's brachial artery for cuff placement. The method requires little work on the part of the health provider, unlike ABPM, which must be downloaded at the physician's office, and the data uploaded to software programs designed for this purpose. From the clinician's point of view, HBP monitoring may hold many advantages over ambulatory monitoring.

There are potential limitations of our study. Given the relatively small percentage of patients with LVH, caution is warranted in interpreting the finding that LVH was only related to home and not office or ambulatory hypertension. Three OBP measurements were performed during one visit, and ABPM was performed only once. Therefore, we cannot exclude the possibility that HBP would not have been an independent predictor of LVMI, if a larger number of OBP or ABP assessments were obtained. Another limitation is that OBP and ABP measurements were performed at the beginning of the study, closer to when antihypertensive medications were withdrawn in treated patients, while HBP readings were obtained over the study period. Because echocardiograms were performed approximately at the end of the 10-week period, it is possible that the relationship between LVMI and HBP was less influenced by any lingering effects of medications beyond the 2-week washout period. Finally, in our study, HBP levels were significantly lower than awake ABP levels, yet the same diagnostic threshold (ie, 135/85 mm Hg) was used to classify home and ambulatory hypertension, respectively. However, it is generally accepted that the diagnostic threshold for both HBP and awake ABP is 135/85 mm Hg.28 Further, since HBP readings are taken at rest, and awake ABP readings include periods of activity, it is not unusual for awake ABP readings to be higher.

In conclusion, our data suggest that, compared with OBP and ABP, HBP measurements, when averaged over a 10-week period, are independently related to cardiovascular end-organ damage. Further research is needed to determine the minimum number of readings required for HBP to be at least an equivalent predictor of cardiovascular end-organ damage and long-term cardiovascular events compared with ABP, and to determine the threshold for HBP at which treatment should be initiated or adjusted.8,29

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Author notes

*
Supported by grants HL47540, HL72866, and HL76857 from the National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland.