Morning Surge in Blood Pressure as a Predictor of Silent and Clinical Cerebrovascular Disease in Elderly Hypertensives
A Prospective Study
Background— Cardiovascular events occur most frequently in the morning hours. We prospectively studied the association between the morning blood pressure (BP) surge and stroke in elderly hypertensives.
Methods and Results— We studied stroke prognosis in 519 older hypertensives in whom ambulatory BP monitoring was performed and silent cerebral infarct was assessed by brain MRI and who were followed up prospectively. The morning BP surge (MS) was calculated as follows: mean systolic BP during the 2 hours after awakening minus mean systolic BP during the 1 hour that included the lowest sleep BP. During an average duration of 41 months (range 1 to 68 months), 44 stroke events occurred. When the patients were divided into 2 groups according to MS, those in the top decile (MS group; MS ≥55 mm Hg, n=53) had a higher baseline prevalence of multiple infarcts (57% versus 33%, P=0.001) and a higher stroke incidence (19% versus 7.3%, P=0.004) during the follow-up period than the others (non-MS group; MS <55 mm Hg, n=466). After they were matched for age and 24-hour BP, the relative risk of the MS group versus the non-MS group remained significant (relative risk=2.7, P=0.04). The MS was associated with stroke events independently of 24-hour BP, nocturnal BP dipping status, and baseline prevalence of silent infarct (P=0.008).
Conclusions— In older hypertensives, a higher morning BP surge is associated with stroke risk independently of ambulatory BP, nocturnal BP falls, and silent infarct. Reduction of the MS could thus be a new therapeutic target for preventing target organ damage and subsequent cardiovascular events in hypertensive patients.
Received November 11, 2002; accepted December 10, 2002.
There is growing evidence indicating that there is a marked diurnal variation in the onset of cardiovascular events, with a peak incidence of myocardial infarction, sudden cardiac death, and ischemic and hemorrhagic stroke occurring in the morning (6 am to noon), after a nadir in these events during the night.1–4 Further characterization of this circadian pattern has identified the hour of awakening rather than the hour in the day as being most closely related to the occurrence of cardiovascular events.5,6
See p 1347
Blood pressure (BP) shows a similar diurnal variation, reaching the highest level during the morning and then declining to reach a trough value at about midnight. In the early morning, an abrupt and steep acceleration in BP occurs, coincident with arousal and arising from overnight sleep.7 It has been suggested that this morning surge in BP might trigger cardiovascular events, but so far there have been no studies that directly demonstrate an association between morning BP surge (MBPS) and events. However, there is considerable variation in the diurnal rhythm of BP in different patients. Our previous work has indicated that the degree to which BP falls or rises during the night, as measured by the difference or ratio of the average daytime and nighttime BPs, varies greatly from one patient to another and that these different patterns (dipping, nondipping, extreme dipping, and rising) are associated with very different risks of strokes.8 The extreme-dipper group, whose nighttime BP is more than 20% lower than the daytime BP, is at particularly high risk, but it is not clear whether this risk is related to the fall of BP during the night, the low nighttime BP, or the morning surge of BP that occurs on waking. In the present analysis, we have attempted to determine which component of the diurnal BP rhythm (nocturnal BP dipping or MBPS) is more closely related to silent cerebral infarct (SCI) and stroke events.
The present study was based on 519 elderly hypertensive patients (mean age 72 years) who were followed up prospectively for an average of 41 months. This represents 98% of the 532 patients who were initially enrolled into the study from 6 participating institutions (3 clinics, 2 hospitals, and 1 outpatient clinic of a medical school) between January 1, 1992, and January 1, 1998. These patients were selected from a larger cohort of hypertensive patients9 by the following criteria: (1) essential hypertension with average clinic systolic BP (SBP) >140 mm Hg and/or average clinic diastolic BP >90 mm Hg (average for each patient on 2 or more occasions on different days); (2) age >50 years; (3) a successful 24-hour ambulatory BP monitoring (ABPM); and (4) assessment of the presence/absence of SCI by brain MRI. No patient had taken any antihypertensive medication for at least 14 days before the ABPM study, but 55% had a prior history of antihypertensive medication use. We excluded from the present study patients with renal failure (serum creatinine level >176 mmol/L), hepatic damage, obvious present illness, a past history of coronary artery disease, stroke (including transient ischemic attacks), congestive heart failure, arrhythmia (including atrial fibrillation), or peripheral vascular disease. All of the subjects studied were ambulatory, and all gave informed consent for the study. The results of the ABPM and brain MRI were returned to the subjects’ treating physicians. This study was approved by the Research Ethics Committee, Department of Cardiology, Jichi Medical School, Japan.
Clinic BP was measured after resting for at least 5 minutes in the sitting position. Diabetes mellitus was defined by a fasting glucose level >7.8 mmol/L, a random nonfasting glucose level >11.1 mmol/L, hemoglobin A1c >6.2%, or the use of an oral hypoglycemic agent or insulin. Hyperlipidemia was defined by a total cholesterol level >6.2 mmol/L or the use of an oral lipid-lowering agent. Smokers were defined as current smokers. Body mass index was calculated as weight (kg)/height (m2). Electrocardiographically verified left ventricular hypertrophy was defined as abnormally high voltages of QRS complexes (R in V5 plus S in V1 >3.5 mV) associated either with flat T waves (<10% of the R wave) or with ST-segment depression and biphasic T-waves.
Noninvasive ABPM was performed on a weekday with 1 of 3 automatic devices (ABPM-630, Nippon Colin Co, TM-2421 or TM-2425, A&D Co Inc, Japan) that recorded BP and pulse rate every 30 minutes for 24 hours. The accuracy of these devices was validated previously. The ambulatory data used in the present study were those obtained by the oscillometric method. We excluded those who obtained less than 80% of either awake or asleep valid BP readings (n=31). Patients who reported in our post-ABPM questionnaire that their sleep was severely disturbed by wearing the ABPM were also excluded from this study (n=23).
Sleep BP was defined as the average of BPs from the time when the patient went to bed until the time he or she got out of bed, and awake BP was defined as the average of BPs recorded during the rest of the day. Morning BP was defined as the average of BPs during the first 2 hours after wake-up time (4 BP readings; Figure 1). The lowest BP was defined as the average BP of 3 readings centered on the lowest nighttime reading (ie, the lowest reading plus the readings immediately before and after). Evening BP was defined as the average BP during the 2 hours before going to bed (4 BP readings). Preawake BP was defined as the average BP during the 2 hours just before wake-up time (4 BP readings). The MBPS was calculated in 2 ways: sleep-trough MBPS, defined as the morning SBP minus the lowest SBP, and prewaking MBPS, defined as the morning SBP minus the preawake SBP. The nocturnal BP fall (mm Hg) was defined as the evening BP minus the lowest BP. The systolic pressures were used for all these calculations.
We subclassified the patients according to the extent of the sleep-trough MBPS as follows: the top decile of sleep-trough MBPS (>55 mm Hg, n=53; the MS group) versus all others (n=466, the non-MS group). We also subclassified the patients according to the percentage of nocturnal SBP reduction [100×(1−sleep SBP/awake SBP)] as follows: extreme dippers if the nocturnal SBP reduction was ≥20%; dippers if the fall was ≥10% but <20%; nondippers if the fall was ≥0% but <10%; and risers if it was <0%.8
Brain MRI was performed with a superconducting magnet with a main strength of 1.5T (Toshiba MRT200FXII, Toshiba; SIGNA-Horizon version 5.8, General Electric Co or Vision, Siemens) within 3 months of the baseline ABPM. T1- and T2-weighted images were obtained in the transverse plane with 7.8-mm- or 8.0-mm-thick sections. An SCI was defined as a low signal intensity area (3 to 15 mm) on T1-weighted images that was also visible as a hyperintense lesion on T2-weighted images, as described previously.8–10 Multiple SCI was defined as 2 or more infarcts. All SCIs detected were lacunar infarcts with a size of <15 mm. The MRI images of the subjects were randomly stored and interpreted without knowledge of the subjects’ names and characteristics. The κ-statistics in assessment of interreader and intrareader agreement (non-SCI, 1 SCI, and multiple SCIs) were 0.70 and 0.80, respectively in our laboratory.
Follow-Up and Events
The patients’ medical records were reviewed intermittently after ABPM for the use of antihypertensive drug therapy and the occurrence of cardiovascular events. The follow-up was performed during a 20-month period from 1996 to 1998; the mean follow-up period was 41 months, with a range from 1 to 68 months. When patients failed to come to the clinic, we interviewed them by telephone. There was no significant difference among the MS and non-MS groups in duration of follow-up. Stroke events were diagnosed by each physician who was caring for the patient at the time of the event, and independent neurologists reviewed the cases and confirmed the diagnosis of stroke events. Stroke was diagnosed on the basis of sudden onset of neurological deficit that persisted for >24 hours in the absence of any other disease process that could explain the symptom. Stroke events included ischemic stroke (cerebral infarction and cerebral embolism), hemorrhagic stroke (cerebral hemorrhage and subarachnoid hemorrhage), and undefined type of stroke. We excluded transient ischemic attacks, in which the neurological deficit cleared completely in <24 hours from the onset of symptoms.
Of the total of 532 eligible patients at baseline, follow-up was obtained in 519 (98%) patients, and the data analysis was restricted to these patients. Of these, 292 (56%) were taking antihypertensive medication at the time of the final follow-up.
Data are expressed as mean±SD. Two-sided unpaired t test and χ2 test were used to test differences between the 2 groups in the mean values of continuous measures and prevalence rates, respectively. Adjusted relative risks (RRs) and odds ratio with 95% CIs were calculated with Cox regression analysis and multiple logistic regression analysis, respectively. The proportional hazards assumption was checked and found to hold for the primary predictors in the Cox regression analyses. In one simultaneous model to study the effect of dipping status (extreme dippers, dippers, nondippers, and risers) and sleep-trough MBPS on stroke risk, 3 dummy variables were used to contrast the 4 dipping status groups. The statistical calculations were performed with SPSS version 8.0J (SPSS Inc). Differences with P<0.05, 2-tailed, were considered to be statistically significant.
Baseline Characteristics and SCIs
The mean±SD sleep-trough MBPS in the total sample was 34±18 mm Hg. The cutoff value for identifying the top decile (the MS group) was 55 mm Hg.
The mean age and clinic BPs were significantly higher in the MS group than in the non-MS group (Table 1). Although there were no significant differences in evening and sleep BPs between the 2 groups, awake and morning BPs were significantly higher in the MS group than in the non-MS group. The mean±SD sleep-trough MBPS defined by the difference between the morning SBP and the lowest SBP was 69±12 mm Hg for the MS group and 29±13 mm Hg for the non-MS group, and prewaking MBPS (defined by the difference between morning SBP and preawake SBP) was 34±21 mm Hg for the MS group and 9.1±14 mm Hg for the non-MS group. There were no significant differences in the clinic and ambulatory pulse rates, including the morning pulse rate (MS group 77.8±11.9 bpm versus non-MS group 75.6±10.9 bpm, P=0.25). In addition, the higher morning surge of BP in the MS group than the non-MS group was not associated with any differences between the groups in the changes of pulse rate.
Although the MS group tended to have a higher frequency of electrocardiographically verified left ventricular hypertrophy (P=0.08) and higher levels of preawake SBP (by 4 mm Hg, P=0.23) and 24-hour SBP (by 5 mm Hg, P=0.06) than the non-MS group, the differences were not statistically significant. There were no significant differences among groups in the prevalence of antihypertensive medication use at the final follow-up.
At the baseline examination, SCI was more frequently detected in the MS group than in the non-MS group (Table 2), particularly when there were multiple SCIs. After age and 24-hour SBP were controlled for with multiple logistic regression analysis, MBPS was an independent determinant of multiple SCI (OR 1.91, 95% CI 1.04 to 3.51, P=0.036). When we identified the 145 non-MS subjects who could be matched for age (range 2 years) and 24-hour SBP level (range 4 mm Hg) to 1 or more MS subjects and weighted the controls to simulate a balanced design, the comparison of group results (Table 3) was essentially the same as in the total sample.
During an average duration of 41 months (range 1 to 68 months), 44 stroke events occurred. The MS group had a higher incidence of stroke events (19% versus 7.3%, P=0.004) than the non-MS group (Table 2). In the groups matched for age and 24-hour SBP, the RR in the MS group (versus the non-MS group) calculated from a weighted Cox regression analysis remained significant (RR=2.7, P=0.04; Table 3). When we divided the total group into quartiles by the sleep-trough MBPS, the stroke incidences were significantly increased in the higher quartiles (Q1=4.6%, Q2=5.5%, Q3=9.2%, Q4=14.5%, χ2=10.2, P=0.017).
Table 4 shows the results of a Cox regression analysis with MBPS as a continuous variable in the total sample. Age, 24-hour BP, and baseline prevalence of SCI were associated with stroke risk, whereas there were no significant other confounders (sex, body mass index, smoking status, diabetes, or hyperlipidemia). Sleep-trough MBPS (morning SBP minus lowest SBP; model 1) was significantly associated with stroke events independently of the significant confounders. When we added the prewaking MBPS (morning SBP minus preawake SBP) into model 1 instead of sleep-trough MBPS, prewaking MBPS tended to be associated with stroke risk (10 mm Hg increase; RR 1.14, 95% CI 0.99 to 1.31, P=0.07), although the association was not significant.
To study the effect of antihypertensive medication, we added a medication term (0=absent, 1=present at follow-up) into model 1 of Table 4. Sleep-trough MBPS (10 mm Hg increase; RR 1.24, 95% CI 1.07 to 1.43, P=0.004) and antihypertensive medication (RR 0.41, 95% CI 0.22 to 0.79, P=0.007) were both significantly and independently associated with stroke risk.
Relationships Between Different Measures of Nocturnal BP Changes
Because the definition of sleep-trough MBPS is related in part to the nocturnal BP fall, we also studied the influence of nocturnal BP dipping status. The prevalences of extreme-dippers, dippers, nondippers, and risers were 51% (n=27), 36% (n=19), 11% (n=6), and 2% (n=1), respectively, in the MS group and 18% (n=85), 46% (n=213), 27% (n=126), and 9% (n=42), respectively, in the non-MS group. Looked at another way, 24% of the extreme-dippers but only 8.1% of dippers, 4.5% of nondippers, and 2.3% of risers were classified as being in the MS group.
Because these prevalences were significantly different (χ2=32.0, P<0.0001), we added these 4 dipping status categories using 3 dummy variables into the same Cox regression analysis (Table 4, model 2). Stroke risk was significantly associated both with MBPS ([10 mm Hg increase; RR 1.25, 95% CI 1.06 to 1.48, P=0.008) and with being classified as a riser (RR 2.71, 95% CI 1.02 to 7.21, P=0.047 versus dipper). In this model, being classified as an extreme-dipper was not significantly associated with stroke risk independently of MBPS.
Time of Stroke Onset and Stroke Subtype
We identified the time of stroke onset in 36 of the 44 events. Seven (78%) of the 9 stroke events in the MS group occurred in the morning period (6 am to noon), whereas 11 (41%) of the 27 events in the non-MS group occurred in this period (χ2=3.70, P=0.05). In extreme-dippers, 6 (60%) of the 10 stroke events occurred during the morning period (6 am to noon), and 3 (30%) occurred during the nighttime period (midnight to 6 am), whereas in the other groups (dippers and nondippers), 12 (46%) of the 26 events occurred in the morning period, and 2 (7.7%) occurred during the night (χ2=5.48, P=0.06).
Of the 44 stroke events, 30 were ischemic, 6 were hemorrhagic, and 8 were of unknown type. There was no significant difference in the stroke subtypes between the MS and non-MS groups.
This study is the first to show that an excessive MPBS is a predictor of subsequent stroke events in elderly hypertensive patients independent of ambulatory BP levels and target organ damage. The MS group, with the highest sleep-trough MBPS (>55 mm Hg), had a higher stroke incidence than the non-MS group (MBPS <55 mm Hg). After they were matched for age and 24-hour SBP, the RR in the MS group versus the non-MS group was 3.2. Because the classification of the MS and the non-MS groups was arbitrary, we repeated the analysis using sleep-trough MBPS as a continuous variable and again found a significant association between MBPS and stroke risk.
Definition of MBPS
There is no consensus concerning the definition of the MBPS. We defined it in 2 ways: sleep-trough MBPS (morning SBP minus lowest SBP during the night) and prewaking MBPS (morning SBP minus preawake SBP). The sleep-trough MBPS was significantly and independently associated with stroke risk, and a 10-mm Hg increase in sleep-trough MBPS increased the stroke risk by 22%. Prewaking MBPS increased stroke by 14%, but this increase was not significant (P=0.07). Thus, our results suggest that sleep-trough MBPS gives a more clinically relevant definition of the MBPS.
MBPS Versus Nocturnal BP Fall
Because the definition of sleep-trough MBPS is related in part to the nocturnal BP fall, we studied the association between MBPS and dipping status of nocturnal BP. We have previously demonstrated that in elderly hypertensive patients, extreme-dippers have more frequent SCI8,10 and a poor stroke prognosis.10 In the present study, 51% of the patients in the MS group were classified as extreme-dippers; thus, whereas the MS group was defined to make up only 10% of the sample (top decile), they made up 24% of the 112 extreme-dippers, and the extreme-dippers and MS groups therefore overlapped significantly. This overlap may explain in part the reason extreme-dippers not only have more frequent sleep-onset ischemic strokes but also have more strokes in the morning, which would be predominantly associated with excessive MBPS.
When we combined dipping status (extreme-dippers, dippers, nondippers, and risers) and MBPS into the same Cox regression analysis model, stroke risk was significantly associated both with MBPS (10-mm Hg increase, RR 1.25, P=0.008) and with being classified as a riser (RR 2.71, P=0.047 versus dippers). In this model, being classified as an extreme-dipper was not significantly associated with stroke risk independently of MBPS. Thus, the fall of BP that occurs during the night appears to be of less importance than the morning surge. The mechanism underlying the increased stroke risk of extreme-dippers might depend on either an excessive morning surge of BP or on cerebral hypoperfusion due to the low nocturnal BP. Two lines of evidence argue for the former mechanism. First, in the extreme-dippers, 60% of strokes occurred during the morning period (6 am to noon) and only 30% during the night (midnight to 6 am), whereas in the dippers and nondippers, 46% of strokes occurred in the morning period and 7.7% during the night. Second, as shown above, extreme-dipping pattern of nocturnal BP did not predict stroke occurrence independently of MBPS.
Time of Onset and Stroke Subtypes
Both ischemic and hemorrhagic strokes showed a greater tendency to cluster in the morning period (6 am to noon) in the MS group than in the non-MS group. Thus, it is reasonable to suppose that an excessive MBPS might trigger strokes through some hemodynamic mechanism such as increased shear stress on the atherosclerotic cerebral vessels, but there are several other factors that change during the morning hours. These include an increase of sympathetic nervous activity, particularly α-adrenergic activity,11,12 and other related acute risk factors such as platelet hyperactivity, hypercoagulability and hypofibrinolysis, blood viscosity, and increased vascular spasm.6,13,14 This potentiation of acute risk factors might also be greater in the MS group than in the non-MS group and contribute to triggering the morning strokes, and it should be investigated in future research.
Association With SCI
There are a few studies that have demonstrated an association between MBPS and target organ damage. Kuwajima et al15 reported that in 23 elderly hypertensive patients, the SBP change after arising in the morning was significantly correlated with the left ventricular mass index and the A/E ratio, which represents diastolic function. SCI is reported to be a strong predictor of subsequent clinical stroke (approximate OR 6 to 10)9,16 and can be considered to be the most important hypertensive target organ damage marker for stroke. In the present study, MBPS was significantly associated cross-sectionally with baseline prevalence of SCI detected by brain MRI and prospectively with stroke events. This association was particularly strong for multiple SCIs. Although SCI prevalence was a strong predictor of a subsequent stroke event in the present study population, the association between MBPS and stroke risk was independent of SCI. Thus, the identification of a “high morning surge” group in elderly hypertensive patients may have some clinical significance even after assessment of target organ damage.
Although the present study was not designed to study the effect of antihypertensive medication on stroke risk, it was found that the use of antihypertensive medication was associated with a significantly reduced stroke risk. In addition, MBPS was significantly associated with stroke risk independently of antihypertensive medication use. Thus, controlling the MBPS with antihypertensive medication might improve stroke prognosis.
Despite the relatively large size of this prospective study, the number of strokes was relatively small. In addition, there are marked differences in the epidemiology of cardiovascular disease between Japan and the United States or European countries. Among Japanese, coronary artery disease is much less common, whereas stroke is more common than among whites or blacks. Further research in a larger sample of Japanese and in the other racial populations is needed to confirm the generalizability of our new findings.
In this study, an excessive MBPS was an independent predictor of stroke in elderly Japanese hypertensive patients. It extends previous work showing that extreme-dippers are at increased risk of stroke and that the principle mechanism may be the morning surge rather than an excessively low BP during the night. This suggests that the morning surge in BP could be a new therapeutic target for preventing target organ damage and subsequent cardiovascular events in hypertensive patients. This finding should be investigated in other racial populations and in a large randomized, controlled trial using antihypertensive medication aimed at suppressing the MBPS.
This study was supported by grants-in-aid (1992-2001) from the Foundation for the Development of the Community (Dr Kario), Tochigi, Japan, and by a grant (HL57450) from the US National Heart, Lung, and Blood Institute (Dr Pickering).
Muller JE, Ludmer PL, Willich SN, et al. Circadian variation in the frequency of sudden cardiac death. Circulation. 1987; 75: 131–138.
Muller JE, Tofler GH, Stone PH. Circadian variation and triggers of onset of acute cardiovascular disease. Circulation. 1989; 79: 733–743.
Kario K, Pickering TG, Matsuo T, et al. Stroke prognosis and abnormal nocturnal blood pressure falls in older hypertensives. Hypertension. 2001; 38: 852–857.
Kario K, Matsuo T, Kobayashi H, et al. Relation between nocturnal fall of blood pressure and silent cerebrovascular damage in elderly hypertensives: advanced silent cerebrovascular damage in extreme-dippers. Hypertension. 1996; 27: 130–135.
Kuwajima I, Mitani K, Miyao M, et al. Cardiac implications of the morning surge in blood pressure in elderly hypertensive patients: relation to arising time. Am J Hypertens. 1995; 8: 29–33.
Kobayashi S, Okada K, Koide H, et al. Subcortical silent brain infarction as a risk factor for clinical stroke. Stroke. 1997; 28: 1932–1939.