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STATE-OF-THE-ART PAPER

Home Blood Pressure Measurement

A Systematic Review

Willem J. Verberk, MSc^_*, Abraham A. Kroon, MD, PhD^_*, Alfons G.H. Kessels, MD, MSc and Peter W. de Leeuw, MD, PhD^_*,_*

^_* Department of Medicine, University Hospital Maastricht and Cardiovascular Research Institute Maastricht (CARIM), Maastricht, the Netherlands
Department of Clinical Epidemiology and Technology Assessment, University Hospital Maastricht, Maastricht, the Netherlands

Manuscript received March 21, 2005; revised manuscript received May 2, 2005, accepted May 16, 2005.

^_* Reprint requests and correspondence: Prof. Dr. Peter W. de Leeuw, Department of Medicine, University Hospital Maastricht, P.O. Box 5800, 6202 AZ Maastricht, the Netherlands (Email: p.deleeuw{at}intmed.unimaas.nl).

	Abstract

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The purpose of this research was to review the literature on home blood pressure measurement (HBPM) and to provide recommendations regarding HBPM assessment. Observational studies on HBPM, published after 1992, as identified by PubMed, EMBASE, and Cochrane literature searches were reviewed. Studies were selected if they met the following criteria: 1) self-measurements had been performed with validated devices; 2) measurement procedures were described in sufficient detail; and 3) papers clearly explained how final HBPM results were calculated upon which conclusions and/or treatment decisions were based. Office blood pressure measurement (OBPM) yields higher blood pressure values than HBPM. For systolic blood pressure, differences between OBPM and HBPM increase with age and the height of office pressure. Differences also tend to be greater in men than in women and greater in patients without than in those with antihypertensive treatment. Furthermore, HBPM can diagnose normotension with almost absolute certainty; it correlates better with target organ damage and cardiovascular mortality than OBPM, it enables prediction of sustained hypertension in patients with borderline hypertension, and it proves to be an appropriate tool for assessing drug efficacy. Despite some limitations and although more data are needed, HBPM is suitable for routine clinical practice.

Abbreviations and Acronyms   AAMI = Association for the Advancement of Medical Instrumentation   ABPM = ambulatory blood pressure measurement   BHS = British Hypertension Society   BP = blood pressure   CI = confidence interval   DBP = diastolic blood pressure   ESH = European Society of Hypertension   HBP(M) = home blood pressure (measurement)   OBPM = office blood pressure measurement   SBP = systolic blood pressure   TOD = target organ damage

However, the introduction of HBPM into clinical practice has also faced us with new problems. These include questions such as: how many measurements are needed to estimate a patient’s usual blood pressure (BP), what are normal values for HBPM, how does antihypertensive treatment affect HBPM, and to what extent can HBPM predict prognosis? The intention of this review, therefore, is to evaluate current knowledge about HBPM to find answers to these questions. To this end, we performed a systematic review of the literature on HBPM.

	Methods

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Identification of papers.   We performed systematic searches of HBPM in PubMed, EMBASE, and the Cochrane database. The search strategy used six key words in various combinations: BP, hypertension, self-measurement, home measurement, ambulatory measurement, and compliance. Additional studies were found from reference lists of identified articles and reviews.

Study selection.   Because the first protocol with guidelines for validation of BP monitoring devices dates back from July 1990 (4), we wanted to include in our review only those papers that have been published after that time. Allowing for some lag time before the guidelines were fully implemented, we took 1992 as the starting year for our literature search. Decisions on inclusion of studies into the systematic review were based on three criteria:

1) Self-measurements were performed with devices that have passed the validation protocols of the British Hypertension Society (BHS) (4), Association for the Advancement of Medical Instrumentation (AAMI) (5), and/or European Society of Hypertension (ESH) (6);

2) HBPM or self-measurement procedures used were described in sufficient detail;

3) The methods section clearly explained how authors calculated from their original data the finally reported home blood pressure (HBP) results.

Two investigators screened the full text of all potentially relevant articles. When more than one paper by the same author or research group was available, these were included for analysis only when it was likely that a different patient sample had been used.

Data extraction.   Papers that fulfilled the selection criteria and provided both OBPM and HBPM data were collected. When multiple drug treatment studies were performed using the same population, only the results of the first study mentioned were used for analysis. Studies that combined subjects with and without antihypertensive drug treatment, without the possibility to distinguish both groups, were excluded for analysis.

Data synthesis.   To test for differences between OBPM and HBPM, we pooled the results weighted with inverse variances (direct pooling) (7). In case the variance was not reported, we imputed the highest variance of the study that was included. Changes in home and office BP, obtained before and after treatment, were compared conservatively by considering these outcomes as unpaired data. To investigate whether age and gender could explain heterogeneity in differences between OBPM and HBPM, we performed linear regression analysis with age and gender (as proportion of men) as independent variables and the difference between OBPM and HBPM as the dependent variable. All statistical calculations were performed using SPSS (SPSS Inc., Chicago, Illinois).

	Results

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How many measurements are needed?.   To determine the number of measurements that are needed to obtain a reliable estimate of a patient’s usual BP when applying HBPM, several studies assessed the reproducibility and/or accuracy of the technique (8–11). The results from these studies are summarized in Table 1. From all studies, which addressed the number of measurements required to obtain an accurate impression of BP for a period of at least one month (8–11), we may conclude that the minimum number of measurements should be two duplicates a day (twice in the morning and twice in the evening) for three consecutive days with exclusion of BP readings taken at the first day.

1) Calculating the mean + two standard deviations for HBPM data in a population and to consider this as the upper limit of normal (normal distribution criterion) (14);

2) Computing the 95th percentile of the distribution of HBPM data in subjects who were normotensive on conventional sphygmomanometry and to consider every value above that percentile as abnormal (percentile criterion) (13–15);

3) Determining the self-recorded BP that corresponds to a conventional (office) BP of 140/90 mm Hg (correspondence [12–14,16–18] or regression criterion [13,14,18]).

4) Conducting a long-term follow-up trial in which normal values are based on the morbidity and mortality patterns from hypertension-related complications (16).

Taken together, the data from these studies suggest that the upper limit for normal HBPM values should be set at 135 mm Hg systolic and 85 mm Hg diastolic.

Differences between HBPM and OBPM.   A pooled analysis of untreated subjects in the studies (13,17,19–32) is listed in Table 3 and shows that the mean overall difference between OBPM and HBPM was 6.9 mm Hg (95% confidence interval [CI] 6.6 to 7.2, p < 0.001) for systolic BP (SBP), and 4.9 mm Hg (95% CI 4.7 to 5.1, p < 0.001) for diastolic BP (DBP). Differences between OBPM and HBPM increase with age for SBP but not for DBP (Fig. 1). Bland-Altman analysis of the data shows that the difference between OBPM and HBPM also increases significantly with higher SBP (Fig. 2) but not DBP. Finally, a higher percentage of men in a study population resulted in larger differences between OBPM and HBPM for SBP (p < 0.01).

View larger version (11K): [in this window] [in a new window]   Figure 1 Differences between systolic (left) and diastolic (right) office blood pressure measurement (OBPM) and home blood pressure measurement (HBPM) as a function of age in patients without antihypertensive treatment. Results were derived from 18 studies with a total of 6,979 subjects (Table 3). The relationship was statistically significant for systolic pressure only (p = 0.036). The regression line was calculated for equal proportions of men and women, and studies were weighted for the number of subjects.

View larger version (14K): [in this window] [in a new window]   Figure 2 Bland-Altman plots for the differences between systolic office blood pressure measurement (OBPM) and home blood pressure measurement (HBPM) as a function of the average of OBPM and HBPM in patients without (left) or with (right) antihypertensive treatment. Results were derived from the studies mentioned in Tables 3 and 4. The relationship was statistically significant for untreated subjects only (p = 0.007). Studies were weighted for the number of subjects.

View larger version (14K): [in this window] [in a new window]   Figure 3 Differences between pretreatment and treatment pressures for both office blood pressure measurement (OBPM) and home blood pressure measurement (HBPM) as derived from eight studies with a total of 3,256 subjects (Table 5). Results for systolic (closed symbols, S) and diastolic (open symbols, D) blood pressure are presented as the mean difference with the 95% confidence interval; OBPM differences were significantly greater than HBPM differences for both systolic and diastolic blood pressure (p < 0.001).

	Discussion

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How many measurements are needed?.   Recently, results from the Ohasama study (40) indicated that one should obtain as many measurements as possible, although with any number of measurements HBPM was already superior to OBPM in predicting future risk.

Because it is possible that BP at home differs from BP at work due to job stress or other factors, BP recorded at work might, in such situations, give a better indication of the overall BP value (10). Despite some discrepancies in the results with regard to morning and evening HBPM, the fact remains that the early morning surge has immense prognostic potential (41–44). For that reason, HBPM in the morning is probably more valuable as compared to evening HBPM in terms of assessing cardiovascular prognosis. On the other hand, Brook (45) showed that the accuracy of HBPM does not depend on a particular monitoring schedule parameter such as number of measurements per day, replications per measurement session, or total duration of home monitoring.

Taking all available information together, it seems that the minimum number of measurements should be two duplicates a day (twice in the morning and twice in the evening) for three consecutive days. Measurements on the first day are persistently higher than subsequent measurements, and for that reason the data from the first day should be discarded (9).

Upper limit of normal values.   Normal values for HBPM have been established on the basis of an international database composed by Thijs et al. (15). Because the 95th percentile method for normotensive subjects was used for obtaining normal values, these normal data were not directly dependent upon OBPM values. In our view, the proclamation of HBPM normal data according to OBPM values, as has been done in other studies, is not a priori justified because OBPM values are highly variable and subject to observer bias as well as the white coat effect.

Preferably, normal values should be based on prognostic studies such as those from Tsuji et al. (16), who defined hypertension as a BP value 137/84 mm Hg and normal BP as SBP <137 mm Hg and DBP between 66 and 83 mm Hg. Fortunately, these values are in line with the reference values from the international database (namely 137/85 mm Hg). In accordance with recent guidelines (46,47), it is fair to set the upper limit of normal values at 135 mm Hg systolic and 85 mm Hg diastolic.

Differences between OBPM and HBPM.   Our analysis shows that the difference in SBP between OBPM and HBPM in untreated patients tends to be larger in men than in women and to rise with age and the level of BP. However, whether age and the degree of hypertension are independent predictors of the difference between OBPM and HBPM cannot be derived from the available data. We further found that the difference between OBPM and HBPM is greater before than during antihypertensive treatment. Although the difference during treatment still tended to increase with the height of pressure, the relationship was no longer statistically significant. Differences in DBP were more or less constant, regardless of age, gender, severity of hypertension, or treatment status.

The most important clinical consequence of the above is that HBPM can largely eliminate the white coat effect, which is defined as an elevation of BP measured in the office compared to either ABPM or HBPM (48). Detection of the white coat effect is relevant to avoid overestimation of daily BP and unnecessary drug prescription. Because the white coat effect also increases with age (49) and is more related to untreated than to treated hypertension (50), HBPM seems to be particularly suitable to assess elderly people with hypertension. Although HBPM may not detect the same patients with the white coat effect as ABPM would (2), it serves at least the purpose of being a reasonable screening test for that phenomenon.

Still, a word of caution is in order because most studies that addressed HBPM in relation to OBPM used different devices for both methods; OBPM was usually assessed with manual mercury sphygmomanometers (auscultatory method), which carries the risk of observer bias due to, for example, hearing loss, impaired ability to react, and digit preference (31,51,52). On the other hand, HBPM was commonly performed with automatic or semiautomatic devices that used an oscillometric method to record the pressure. This may at least in part explain some of the differences between OBPM and HBPM. Additionally, most studies from Table 5 that addressed drug efficacy using HBPM and OBPM showed a larger decline in OBPM after treatment as compared with HBPM. Such differences could be due to the physician expecting a decline in BP after drug administration. This assumption is supported by the study of Vaur et al. (31) who showed a decline in OBPM after treatment while the patient was using a placebo whereas this effect was absent in HBPM. Therefore, in order to exclude measurement bias in future clinical trials, OBPM and HBPM should be performed with the same device, preferably an automatic one (53). In the ongoing Home versus Office blood pressure MEasurements: Reduction of Unnecessary treatment Study (HOMERUS) trial (54), this approach has already been adopted.

HBPM and assessment of drug efficacy.   The possibility of HBPM to obtain multiple measurements within a relatively short period of time makes the technique particularly useful to determine drug efficacy (21,30,32). As an index of efficacy, the morning-to-evening ratio has been introduced as an alternative for the "trough-to-peak ratio," which is used with ABPM (55). With respect to the morning-to-evening ratio, one assumes that if medication is taken at a 24-h interval, the trough is reached just before the new medication is taken after 24 h in the morning, while 12 h earlier in the evening, the full effect of the drug can be expected (the peak).

HBPM and cardiovascular prognosis.   Although only a few studies have addressed the relationship between HBPM and TOD, they are consistent in their results. Clearly, HBPM is superior to OBPM and comparable to ABPM in predicting cardiac as well as renal damage (33,36). As far as long-term cardiovascular prognosis is concerned, data also indicate that HBPM is the better predictor of outcome when compared to OBPM. For instance, the Ohasama study (38) clearly established a relationship between HBPM and mortality risk. When home BP values and screening BP values from this population study were simultaneously incorporated into a Cox model, only the average of multiple (more than three) home systolic BP values was significantly and strongly related to cardiovascular mortality risk. The average of the two initial home BP values was also better related to mortality risk than were the screening BP values. More recently, the same investigators presented their ten-year follow-up data (40), which indicated that the predictive value of HBP increases progressively with the number of measurements. When at least 14 measurements are obtained, HBPM shows a 35% increase in the risk of stroke per 10 mm Hg elevation in BP. Nevertheless, even if one considers only initial HBP values (one measurement), stroke risk is better predicted by HBPM than by OBPM.

Despite some limitations of this study (other risk factors were ignored in the analysis, there was a higher overall mortality from cerebrovascular disease in Ohasama than in the rest of the country, and an arbitrarily chosen end point was used for determining acceptable risk), this is an important long-term follow-up study linking HBPM to cerebrovascular risk. The study also suggested that the correlation between home DBP and mortality is nonlinear (U-shaped curve) and that a very low DBP may be associated with increased mortality as well.

Conclusions.   Although more research is needed, several arguments already speak in favor of implementing HBPM into daily clinical practice. First of all, it eliminates the white coat effect and allows identification of patients with white coat hypertension. Second, it offers the possibility to obtain multiple readings under standardized conditions with little measurement variability. This increases knowledge of usual BP value in such conditions as borderline hypertension (28,56), type II diabetes mellitus (57,58), and older age (35,59–61). In addition, it allows better judgment of drug efficacy (21,24,26,29–32). Third, HBPM data correlate better than OBPM values with TOD, in particular left ventricular hypertrophy (33,36,37,58), with cardiovascular events (39), and with cardiovascular mortality (38,39). The predictive power of HBPM increases with the number of measurements and should perhaps be based on the average of at least 14 data points (40). Finally, HBPM may increase patients’ awareness of hypertension and compliance with drug treatment, potentially leading to reduced mortality and costs (62). In line with this supposition, a recent meta-analysis by Cappuccio et al. (63) showed that subjects using HBPM had lower BP values and were more likely to achieve their target BP value than subjects without HBPM.

In practice, many factors can influence HBPM. It is important, therefore, that established guidelines for procedures of self-monitoring of BP (64,65) are meticulously followed and that patients receive extensive instruction from a well-trained nurse or physician (66). Recordings must be taken with devices (67–75) that have been validated according to AAMI (5), BHS (4), and/or ESH (6) standards (Table 6). Moreover, BP devices should be memory-equipped in order to prevent reporting bias (76). Because manual devices, which require the patient to inflate the cuff and/or to determine BP himself, are subject to the same forms of measurement bias as office recordings, automated ones are to be preferred.

Still, due to an ever-increasing workload for physicians, it seems to be only a matter of time before people measure their BP at home and transmit it through the internet to the hospital, instead of visiting the doctor at the clinic. This modern approach of hypertension management is already put into practice at the HOMED-BP trial (83).7

	Footnotes

 
Supported by grant 945-01-043 from ZONMW (Den Haag).

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