(Hypertension. 1996;28:725-731.)
© 1996 American Heart Association, Inc.
Articles |
Blood Pressure Level and Variability in the Prediction of Blood Pressure After 5-Year Follow-up
the Department of Medicine, Medical School, University of Tampere (Finland) (S.M.); Department of Internal Medicine, Division of Hypertension, University of Michigan, Ann Arbor (S.M., A.B.W., H.L.); and Department of Clinical Physiology, Medical School, University of Tampere and Department of Clinical Physiology, Tampere (Finland) University Hospital (V.T., M.T.T., A.U.).
Correspondence to Silja Majahalme, MD, Tampere University Hospital, Department of Internal Medicine/Cardiology, P.O. Box 2000, FIN-33521, Tampere, Finland.
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Abstract |
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We compared mean intra-arterial ambulatory blood pressure (IAMB), blood pressure (BP) diurnal profiles and variability, and postural measurements with casual sphygmomanometric measurements for the prediction of future BP. We studied 97 healthy, unmedicated men classified as normotensive (NT, n=34), borderline hypertensive (BHT, n=29), or mildly hypertensive (HT, n=34) by repeated casual measurements during the 2 months before IAMB. Five years later, we reassessed 79 subjects (81%) using casual BP measurements and noninvasive ambulatory 24-hour BP monitoring (NAMB). IAMB level generally correlated well with follow-up BP and slightly better with NAMB level than with casual measurements (24-hour IAMB versus follow-up NAMB systolic BP [SBP], r=.64, P<.001; versus diastolic BP [DBP], r=.52, P<.001). NT and BHT subgroup correlations were of similar strength, but the relationship in the HT subgroup was not significant. Similarly, when we examined daytime and nighttime BP levels, nighttime BP correlated better with follow-up BP in NT and BHT but not in HT. The only measures that were significantly related to follow-up BP in HT were two BP variability measures, SD and the range of variability (RV80: 90th minus 10th percentile) (initial 24-hour IAMB SD and follow-up BP, r=.42 to r=.52, P<.05 to P<.01; RV80 versus follow-up BP, r=.43 to r=.52, P<.05 to P<.01). Correlations of follow-up BP with postural BP were generally weaker than with casual BP or IAMB level. Linear stepwise regressions for SBP and DBP separately (including all IAMB variables) demonstrated that the best single predictor for follow-up BP was 24-hour IAMB SBP level, which explained 41% of follow-up NAMB SBP level variance (F=52.6, P<.001). However, in a second analysis including casual values, casual SBP alone explained 44% of follow-up NAMB SBP variance (F=62.5, P<.001), whereas IAMB SBP added only 4% (F=5.5, P<.05). Predictions of follow-up DBP were always poorer. After 5 years, 70% of NT and 86% of HT were still in their initial classification group, but 67% of BHT had become hypertensive. In these new HT (n=16), initial IAMB level correlated most strongly with follow-up NAMB level (24-hour SBP, r=.70, P<.01; 24-hour DBP, r=.55, P<.05). The only other significant demographic variable predicting future BP was change in weight over 5 years, which added 10% to the explanation of future casual SBP variance (F=12.5, P=.0007) and 15% to casual DBP variance (F=18.0, P=.0001); for NAMB, the percentages were lower. In logistic regression, those NT and BHT who became hypertensive (n=22) had a 75% probability of becoming hypertensive if they gained 11.7 kg or more during 5 years (
2=4.5, P=.03). To conclude, BP tended to increase in all groups, especially in BHT, during follow-up. Nominal differences were observed between casual measurements and BP level measures in the prediction of future BP, and their explanatory value for future BP was generally less than 50%. However, for BHT who became hypertensive, BP level and variability measurements somewhat improved the prediction of follow-up BP. Weight gain was an important additional predictor for future hypertension in both NT and BHT.
Key Words: blood pressure, ambulatory • posture • follow-up studies
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Introduction |
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Many studies have shown that casual BP predicts cardiovascular events and target-organ damage in hypertension,1 2 3 4 and evidence is accumulating that ambulatory BP may improve the prediction of target-organ damage5 6 7 8 9 10 and the prognosis of hypertension.11 12 13 14 15 16 Prediction of future BP levels has been more problematic. One approach has been to use acute stressors,17 18 19 20 21 22 but results vary, and stressors generally seem to increase the predictive value of BP only moderately, if at all. Because ambulatory BP measurements23 have only recently been introduced, they have seldom been used to predict future BP level.
Our aim in this study was to evaluate the usefulness of BP level and variability, as assessed by ambulatory measurement, as well as postural BP in the prediction of future BP trends in NT, BHT, and HT groups. Intra-arterial measurements were used for ambulatory and postural measurements in the initial phase, and follow-up measurements were done with standardized noninvasive techniques.
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Methods |
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Subjects
In the baseline phase, 97 healthy male volunteers were recruited from a routine health checkup carried out on all 35-, 40-, and 45-year-old people at the Communal Health Center of the City of Tampere from 1987 through 1990. Detailed protocols for recruitment and BP measurements have been described.24 Subjects were classified according to World Health Organization criteria25 on the basis of repeated casual BP measurements (mean of six to nine measurements) obtained during the 2 months before the trial. During the initial phase, the study group included 34 NT (SBP
140 and DBP 90 mm Hg), 29 BHT (SBP 141 to 159 or DBP 91 to 94 mm Hg), and 34 HT (SBP 
160 or DBP 95 mm Hg). Classification BP values and demographic characteristics of the subjects are shown in Table 1
. Clinical examination, chest x-ray, electrocardiography, and screening hematology and serum biochemistry tests were normal in each subject. No subject had ever taken antihypertensive medication or other chronic medications.
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The mean follow-up period was 5.2 years (range, 4 to 6 years). From the original group, 84 were contacted successfully, and 79 were able to participate in follow-up tests and measurements. One of those 5 who declined had had a stroke, and the others declined because of personal reasons. Thirteen subjects had moved out of the area and could not be contacted.
The study was approved by the Ethics Committee of Tampere University Hospital. Written informed consent was obtained from all subjects before the study.
Intra-arterial BP Measurements
Initial BP was measured intra-arterially with the Oxford method as described in detail elsewhere.26 27 The brachial artery of the nondominant arm was cannulated under local anesthesia with the Seldinger technique. Signals were collected on Medilog 20 FM recorders (Oxford Medical Systems, Ltd). The signal-analyzing system is described and was validated in previous studies.28 29 30 After signal processing, 30-second means of BP were used for calculations.
Postural intra-arterial BP was determined as a mean of the final minute of sitting and supine periods, each of which lasted 10 minutes. Measurements were done in a standardized laboratory setting; during the procedure, subjects were awake but were not allowed to speak.
Diurnal BP Level
For comparison, we used mean 24-hour IAMB as well as means of two 5-hour segments: daytime (8:30 AM to 1:30 PM), representing the working period, and nighttime (12:30 to 5:30 AM), representing the sleeping period. During recording, all subjects were living in their normal environment, and a majority of the subjects went to work during the daytime period. Those who stayed at home (23 men) did work-related tasks, such as paperwork, computer tasks, and telephoning, as well as leisure activities, such as walking outside or shopping. The most common reasons for not going to work were either inconvenience in organizing their daily schedule (businessmen, white-collar workers) or the impossibility of performing work-related physical tasks during recording (blue-collar workers).
Variability was characterized by calculating the SD for the 5-hour periods as well as the entire 24-hour period and by the 80% range of variability (RV80). The RV80 is the difference between the 90th and 10th percentiles of the cumulative distribution curve, as described by Turjanmaa et al.31
Noninvasive BP Measurements
Follow-up NAMB measurements were done with the previously validated32 33 DIASYS 200 device (Novacor SA), which uses an auscultatory method. Measurements were done every 15 minutes between 6 AM and 10 PM and every 20 minutes between 10 PM and 6 AM. Only recordings with less than 10% missing or inappropriate values were accepted. The raw data were manually checked and inappropriate readings34 removed. Follow-up casual BP measurements were done with a calibrated standard auscultatory method using an aneroid barometer (Speidel and Keller). All measurements were done according to World Health Organization recommendations25 by the same trained nurse whose audiogram was examined before the study and found to be normal. Measurements were done with subjects in a sitting position after they had rested quietly for 10 minutes. A mean of repeated casual measurements was used in comparisons. Measurements were done on 2 consecutive days before the ambulatory measurement was started (three repeated measurements at least 1 minute apart) and after it was finished (two repeated measurements at least 1 minute apart).
Initial casual measurements used in the classification of BP were measured during a 2-month period before the baseline study (six to nine readings were averaged for comparisons).
Statistical analyses included one-way ANOVA with Tukey's multiple comparison tests and multiple linear and logistic regression analyses with the use of SAS 6.09 UNIX statistical software. Data are presented as mean (SD). Correlations were calculated as Pearson correlation coefficients. Values of P<.05 were considered significant.
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Results |
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All results shown concern subjects who were eligible in both phases. At the initial evaluation, as shown in Table 1
, demographic and anthropometric variables did not differ significantly between the groups, except for a tendency for body mass index to be higher in HT. During the follow-up phase, 79 of 97 (81%) men were available, and again, no differences in demographic values were seen between groups. Eight of these subjects had been treated with a single antihypertensive medication; all but 1 were classified originally as HT, and the remaining 1 had belonged to the original BHT group. Of these 8 men, 4 (including 1 originally classified as BHT) were examined in the follow-up period after an at least 2-week interruption of antihypertensive medication. Four others were not willing to discontinue their medication, which was in 2 cases a cardioselective ß-blocking agent and in 2 cases an angiotensin-converting enzyme inhibitor. Correlation coefficients between initial and follow-up BPs were similar or slightly higher when these 8 subjects were excluded compared with analyses which included them; statistical significance did not change. Correlation coefficients presented include these 8 subjects. However, because antihypertensive treatment may have reduced the expected BP rise over time, we show regression analyses for the groups both including and excluding the treated subjects. These results are shown in Tables 7 and 8, and as seen, differences are minor. Nonetheless, we cannot exclude a possible confounding effect of drug treatment.
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One subject had been diagnosed with Parkinson's disease soon after the initial phase, and he had also developed coronary artery disease and undergone coronary artery bypass grafting; his original classification was BHT.
No other cardiovascular events developed during follow-up. One NT person, who did not participate in the follow-up ambulatory study, had had a fulminant stroke about 1 year after the baseline study. Neither diabetes nor medically treated dyslipidemia was diagnosed in the follow-up phase.
IAMB Level and Follow-up BP
IAMB levels are shown in Table 2 and correlations with follow-up BP in Tables 3 through 5. For the whole study sample, IAMB measurements generally correlated well with follow-up BP, somewhat better with NAMB than casual measurements, although the differences were not large (24-hour IAMB versus casual SBP, r=.54, P<.001; versus NAMB SBP, r=.64, P<.001; versus casual DBP, r=.43, P<.001; and versus NAMB DBP, r=.52, P<.001). In the NT and BHT groups, correlations between 24-hour IAMB level and follow-up BP were similar to those for the whole sample, but in the HT group, the correlation between initial 24-hour BP level and follow-up BP was not significant (Table 3). In day-night comparisons, daytime BP levels generally correlated less consistently than nighttime BP levels with follow-up BPs in NT and BHT (Tables 4 and 5).
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Postural Versus Ambulatory BP and Follow-up BP
When we compared postural and IAMB measurements with follow-up BP in the whole sample, supine BP correlations were almost equally well correlated with follow-up BP as IAMB values (supine SBP versus casual SBP, r=.46, P<.001, and versus NAMB SBP, r=.50, P<.001; supine DBP versus casual DBP, r=.44, P<.001, and versus NAMB, DBP r=.52, P<.001). Substantial differences between subgroups were seen: In the NT group, postural BPs correlated significantly with follow-up BP, whereas in the BHT and HT groups, no statistically significant correlations were observed (Table 6).
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BP Variability and Follow-up BP
In the whole group, 24-hour IAMB standard deviation correlated weakly with follow-up casual BP (SBP, r=.30, P<.01; DBP, r=.26, P<.05) and follow-up NAMB (SBP, r=.24, P<.05; DBP, r=.25, P<.05). Variability measures correlated significantly with follow-up BP only in the HT group and almost equally with casual BP and NAMB levels (Table 3).
Initial Casual BP and Follow-up
Initial casual BP measurements correlated as well as IAMB measurements with follow-up BP in the whole sample (versus follow-up NAMB: SBP, r=.67, P<.001; DBP, r=.56, P<.001). Generally, casual SBP correlated better than DBP with follow-up in the subgroups and in the NT group better than other subgroups (Table 6).
In stepwise multiple regressions (Tables 7 and 8) separately for SBP and DBP (including both IAMB level and variability variables), the best predictor of follow-up SBP and DBP was 24-hour IAMB level. When initial casual measurements were included in the model, they were slightly more strongly related than IAMB level to both follow-up measurements, especially to casual SBP.
Separate linear regressions (results not shown) for NT, BHT, and HT showed that the prediction of future BP was generally better in NT than in BHT or HT. The prediction of follow-up NAMB level was better than the prediction of casual follow-up BP in all subgroups. BP levels were better predictors than variability measures in NT and BHT, whereas in HT, variability measures were the only predictors of future BP.
Future Hypertension
NT and HT group classifications were very stable compared with BHT: 70% of NT and 86% of HT remained in their initial classification group at follow-up, whereas 67% of BHT became hypertensive (Figure). In these new HT (n=16), initial IAMB correlated quite well with follow-up NAMB levels (daytime SBP, r=.53, P<.05; nighttime SBP, r=.72, P<.01; 24-hour SBP, r=.72, P<.01; 24-hour DBP, r=.55, P<.05). Results are shown in Tables 7 and 8. Postural and casual BP correlations were somewhat weaker than BP level correlations (data not shown). Initial BP did not differ significantly between the subgroup of BHT who progressed to essential hypertension and those who did not.
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For the combined group of NT and BHT who became hypertensive (n=22) during 5 years, the increment in BP (from casual initial to casual follow-up) was 3.3 (8.9) mm Hg for SBP and 13.1 (6.4) mm Hg for DBP. For those HT and BHT who became normotensive (n=7), the decrease of BP was 23.9 (9.6) mm Hg for SBP and 11.3 (5.7) mm Hg for DBP. The change of BP was significantly correlated only with nighttime SD and RV80 values (r=.42 to r=.49 for future HT; r=.84 to r=.90 for future NT). In a logistic regression model for these NT and BHT who became hypertensive, the change of weight from initial phase to follow-up was a significant predictor of progression to hypertension (2=4.5, P=.03): Those who gained more than 11.7 kg during 5 years had a greater than 75% probability of becoming hypertensive. When classification BPs, 24-hour IAMBs, change of weight, and age were included in a logistic regression model, the only predictor for future hypertension was 24-hour IAMB DBP.
We also calculated day-night BP differences (both absolute and the percentage change from daytime BP level) and found that the percentage SBP change during the initial phase correlated significantly inversely with follow-up nighttime SBP (r=-.30, P<.01) as well as with nighttime DBP (r=-.28, P<.05), but we found no other significant correlations. The mean percentage BP change from day to night was 23.1% (7.4%) for SBP and 22.3% (8.8%) for DBP. The number of true nondippers (percentage BP change 10%) in the initial phase was very small, only three HT subjects, and thus further statistical analyses in that group were not possible.
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Discussion |
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This study followed a relatively small but well-defined sample of NT and newly detected BHT and HT men for 5 years. In the initial phase, they were unmedicated and in good health. To characterize BP in these subjects, we performed multiple techniques, including several casual readings, by which BP was classified before the ambulatory recording, and IAMB recording, a gold standard for BP measurement.
Because of the invasive nature of the study, the number of subjects was necessarily relatively small. We realize that intra-arterial recording is not a practical tool for clinical assessment, but its ability to characterize BP variability and to estimate average BP precisely during everyday activities is unmatched by other methods. Therefore, we used it to see the potential of daily BP level and variability measures in predicting future BP. One of our main findings is that even with this approach, we can explain only a fraction of the variance of future BP level, whether measured with repeated casual or ambulatory readings. When we compared the average of multiple casual BP readings in the initial phase with intra-arterial readings, there was no important difference in explanatory power.
It is well known that hypertension is an independent risk factor for cardiovascular events.2 BP values tend to trend over time, but the prediction of future BP and the identification of future hypertension from baseline values has proved difficult. Some studies using different stressors have tried to improve the prediction of future hypertension,20 21 35 36 37 but that has not been constantly beneficial, and even exercise BP seems to explain only a moderate part of the variance of future BP. We asked the question, Can we increase the reliability of prediction by increasing the accuracy of the measurement method and by using BP level and variability measures? De Faire et al23 used NAMB recording to determine whether BP measurements could predict future hypertension in a group of BHT. In that study, 15% of BHT had become hypertensive after a 1-year follow-up, but predictive values for future BP were low for both basal BP (19% for DBP and 27% for SBP) and ambulatory BP (23% for daytime SBP). In our study, with a mean follow-up period of 5.2 years, the best prediction of follow-up BP was found for those BHT who became hypertensive. For this group, initial nighttime SBP level and nighttime SBP variability together explained 67% of follow-up ambulatory SBP level variance, but generally, the explanation of follow-up BP variance did not exceed 50%. Generally, we found no great differences between BP level and postural BP in the prediction of future BP level compared with casual BP. For those BHT who became hypertensive, BP level measurements were useful, especially when follow-up measurements were also done with an ambulatory method. The outcome of NT and BHT in the present study were comparable to Framingham results: 22% of NT and 67% of BHT became hypertensive. Leitschuh et al38 from the Framingham Heart Study showed that in 26 years of follow-up, 54% of men with high-normal BP at baseline (DBP 85 to 89 mm Hg) became hypertensive compared with 24% of men with normal baseline BP (DBP <85 mm Hg). Risk factors for future hypertension in their study were baseline SBP and change in weight, and those subjects with high-normal BP at baseline had a twofold to threefold probability of developing hypertension compared with the low-normal BP group. In our study, change of weight also predicted future hypertension and thus seems to be a potentially important modifiable risk factor preventing the progression of borderline hypertension to established hypertension. In our study, outcomes similar to those of the Framingham Heart Study were seen over a much shorter time, possibly because of the way we classified the initial BP groups and because we had very accurate BP data.
Most of our HT stayed in the hypertensive range, although their future absolute BP level was very difficult to predict from initial BP values. Instead, we found that BP variability predicts the future BP level of hypertensive individuals. These findings are in line with the observations of Frattola et al,15 who evaluated the prognostic value of 24-hour BP averages and variability for future end-organ damage related to hypertension. They reported that cardiovascular complications may depend on the degree of 24-hour BP variability.
To conclude, the BP of NT, untreated BHT, and HT middle-aged men in general tends to rise, especially in BHT men. Both casual BP and BP level measurements explained a maximum of 50% of future BP variance, but for BHT who became hypertensive, BP level and variability measurements together explained 67% of future BP variance. In those initially HT subjects, BP variability measures were of use in the prediction of follow-up BP as well as the magnitude of change in BP. For BHT who became hypertensive, weight gain was an important modifiable risk factor and should always be considered in the evaluation and treatment of BHT.
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Selected Abbreviations and Acronyms |
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Acknowledgments |
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This study was financially supported by the Medical Research Fund of Tampere University Hospital and Research Fund of the University of Tampere. We would like to express our gratitude to Pirjo Jarventausta for her technical assistance during the study.
Received January 22, 1996;
first decision February 16, 1996; first decision May 24, 1996;
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