Summary
Background and objectives
Abnormal ambulatory BP (ABP) profiles are commonplace in CKD, yet the prognostic value of ABP for renal and cardiovascular outcomes is uncertain. This study assessed the relationship of baseline ABP profiles with CKD progression and subsequent cardiovascular outcomes to determine the prognostic value of ABP beyond that of clinic BP measurements.
Design, setting, participants, & measurements
Between 2002 and 2003, 617 African Americans with hypertensive CKD treated to a clinic BP goal of <130/80 mmHg were enrolled in this prospective, observational study. Participants were followed for a median of 5 years. Primary renal outcome was a composite of doubling of serum creatinine, ESRD, or death. The primary cardiovascular outcome was a composite of myocardial infarction, hospitalized congestive heart failure, stroke, revascularization procedures, cardiovascular death, and ESRD.
Results
Multivariable Cox proportional hazard analysis showed that higher 24-hour systolic BP (SBP), daytime, night-time, and clinic SBP were each associated with subsequent renal (hazard ratio, 1.17–1.28; P<0.001) and cardiovascular outcomes (hazard ratio, 1.22–1.32; P<0.001). After controlling for clinic SBP, ABP measures were predictive of renal outcomes in participants with clinic SBP <130 mmHg (P<0.05 for interaction). ABP predicted cardiovascular outcomes with no interaction based on clinic BP control.
Conclusions
ABP provides additional information beyond that of multiple clinic BP measures in predicting renal and cardiovascular outcomes in African Americans with hypertensive CKD. The primary utility of ABP in these CKD patients was to identify high-risk individuals among those patients with controlled clinic BP.
Introduction
Ambulatory BP monitoring (ABPM) is a noninvasive technique in which BP is recorded frequently and automatically over an extended period of time, typically 24 hours. Compared with standard office BP, ABPM provides unique information, including diurnal BP patterns, that might be prognostically relevant (1–3). Previous studies have shown that microalbuminuria, progression of renal disease, left ventricular hypertrophy, cardiovascular mortality, and silent cerebrovascular disease are associated with higher night-time BP and are more frequent in nondippers (<10% nocturnal BP reduction) compared with dippers (>10% nocturnal reduction) (4–10) and in those with masked hypertension (11). Studies have also demonstrated that renal disease is associated with a nondipping pattern, and that nondipper patients with renal disease progress more rapidly to ESRD than dippers (8–10,12–15).
A critical, yet unresolved, issue is whether ABPM provides useful information beyond that of multiple, high-quality office BP measurements. As a result, clinical use of ABPM is limited, and insurance payers and the Centers for Medicare and Medicaid Services typically only reimburse for ABPM when it is used to diagnose white-coat hypertension (elevated clinic BP and normal 24-hour BP). Because of its well characterized population and standardized measurement of both clinic and ambulatory BP, the African American Study of Kidney Disease and Hypertension Cohort Study (AASK-CS) provides a unique opportunity to determine if ABPM adds incremental prognostic information in terms of progression of renal disease and cardiovascular events in participants with CKD.
Materials and Methods
The AASK-CS was a 5-year prospective, observational study that began in 2002 after completion of the AASK trial (16). The AASK-CS protocol was approved by the institutional review board of each participating center, and all participants provided written informed consent (ClinicalTrials.gov registration number NCT00582777). A scientific advisory board, established by the National Institute of Diabetes and Digestive and Kidney Diseases, provided external oversight.
The AASK-CS was designed to identify risk factors for the progression of renal disease in participants treated to a BP goal of <130/80 mmHg. Initial drug therapy included an angiotensin converting enzyme inhibitor (ACEI); among those who did not tolerate an ACEI, an angiotensin II receptor blocker was used. The rationale, design, and baseline characteristics of AASK-CS participants have been published (16).
Inclusion in the AASK-CS required prior participation in the AASK trial. The AASK trial was a 3×2 factorial design study that enrolled hypertensive African-American participants, aged 18–70 years with a GFR of 20–65 ml/min per 1.73 m2. In the trial, participants were randomized to initial treatment with one of three BP medications (an ACEI, a sustained release β blocker, or a dihydropyridine calcium channel blocker) and to one of two BP goals (a usual mean arterial pressure of 102–107 mmHg or a lower BP goal <92 mmHg). Exclusion criteria for the trial included diabetes mellitus, a urinary protein/creatinine ratio >2.5, history of malignancy, accelerated hypertension or history of cardiovascular event within 6 months of enrollment, history of clinical heart failure, evidence of renal disease other than hypertensive nephrosclerosis, or absolute indication or contraindication for any of the randomized drugs.
The primary renal outcome of the AASK-CS was a composite defined by a doubling of the serum creatinine level from trial baseline, ESRD, or death. ESRD was defined by the start of dialysis or occurrence of renal transplantation. The primary cardiovascular outcome was a composite event of hospitalization for myocardial infarction, congestive heart failure, stroke, or revascularization procedure. Cardiovascular events and ESRD were adjudicated by an endpoints committee. Of the 1094 participants who initiated the AASK trial, 795 participants were eligible to participate in the AASK-CS. Of these, 617 enrolled in AASK-CS and had a baseline ABPM.
Cohort baseline visit data included BP measurement, weight, electrocardiogram, and blood and urine samples. Antihypertensive medication was provided to participants without charge. Participants were followed regularly every 3 months for BP measurement and adjustment of their antihypertensive regimen. Serum creatinine was measured every 6 months in the same central laboratory for the trial and cohort study.
Ambulatory BP Measurement
Twenty-four hour ABPM was performed with the SpaceLabs 90207 Ambulatory BP Device (Redmond, WA). Arm circumference was measured to ensure use of an appropriate size cuff, and the center of the inflatable bladder was placed over the brachial artery. The monitor was programmed to record BP every 30 minutes, and set so that the monitor readings were not displayed to the participant. As per our protocol in the Dietary Approaches to Stop Hypertension study, the ABPM was considered adequate if the monitor had been worn for a full 24 hours and if there were at least 14 acceptable reading between 6:00 am and midnight (daytime), and six acceptable readings between midnight and 6:00 am (night-time) (17). Data from the monitors were sent to the central Cardiovascular Core Laboratory and entered into the study database (11). Participants with a reduction in BP of >10% at night-time compared with daytime were considered dippers. Nondippers had <10% reduction at night-time and reverse dippers had higher SBP at night-time compared with daytime. Masked hypertension was defined as clinic BP <140/90 mmHg, whereas the 24-hour value was ≥125/79 mmHg (18).
Clinic BP Measurement
Trained and certified coordinators performed all BP measurements using a Tycos classic hand-held aneroid device. Three consecutive seated readings were recorded with the mean of the last two readings documented as the clinic visit value. Baseline clinic BP was the average of all clinic BP measurements obtained during a 60-day window of the ABPM (usually three separate days, each with three readings).
Statistical Analyses
Baseline characteristics were summarized as means ± SDs for continuous variables and as frequencies and percentages for categorical variables. Participants lost to follow-up were included in the analysis, and their last follow-up times were treated as the censored times for both renal and cardiovascular outcomes.
The two-sample t test, Wilcoxon rank sum test, and chi-squared test were used to compare the baseline variables of participants stratified on whether they had controlled clinic systolic BP (<130 mmHg versus ≥130 mmHg). Cox proportional hazard models were used to relate each BP measurement and dipping status to the renal and cardiovascular outcomes. The models were stratified by randomization groups and controlled for age, sex, smoking status, LDL cholesterol, and diabetes mellitus (15% of the participants developed diabetes mellitus after the inception of the AASK trial) for cardiovascular outcomes and age, sex, body mass index (BMI), number of comorbidity conditions, diabetes, and baseline estimated GFR (eGFR) for renal outcomes. The assumption of proportional hazard was assessed by the Kolmogorov-type supremum test, and the functional forms of the covariates were assessed by checking the martingale residuals. The covariates were transformed using restricted cubic spline if needed. To examine whether ABPM provides additional predictability for the clinical outcomes, the significance of each ABPM variable was first examined for clinic SBP controlled and uncontrolled patients, respectively. The interaction between that ABPM variable and clinic SBP groups, which was specified a priori, was then tested in a full model with all patients. These models all control for clinic SBP and other prespecified covariates. No other interactions were tested. All P values are two sided, without adjustment of multiple comparisons. Analyses were performed using SAS 9.1.3 (Cary, NC) and R 2.7.1 software.
Results
This analysis includes 617 participants with ABPM variables measured at baseline. Table 1 presents the characteristics of the participants at the beginning of the cohort stratified by baseline clinic SBP (controlled SBP <130 mmHg; uncontrolled SBP >130 mmHg). Mean age of the participants was 60.3±10.1 years, 38.1% were women, BMI was 31.2±7 kg/m2, and eGFR was 43.5±15.9 ml/min. Forty-three percent of participants had controlled SBP at baseline with a mean clinic SBP of 118.2±8.4 mmHg compared with 145.3±13 mmHg in the uncontrolled group. Diastolic DB (DBP) was 74.6±8.2 mmHg and 83.3±10.4 mmHg, respectively. Proteinuria was low, with a mean urinary protein/creatinine ratio (mg/mg) of 0.35±0.79 for the overall group. More participants with clinic SBP <130 mmHg had been randomized to the low BP group during the trial phase of AASK (low BP versus usual BP goal) but there was no statistically significant difference with respect to the drug assignment during the trial.
Table 1.
Baseline variables by baseline clinic SBP status
| Variable | Overall (n=617) | Uncontrolled, Baseline SBP <130 mmHg (n=350) | Controlled, Baseline SBP ≥130 mmHg (n=267) | P |
|---|---|---|---|---|
| Age (yr) | 60.3±10.1 | 61.2±9.6 | 59±10.5 | 0.01 |
| Sex | 0.01 | |||
| Male | 382 (61.9) | 200 (57.1) | 182 (68.2) | |
| Female | 235 (38.1) | 150 (42.9) | 85 (31.8) | |
| Weight (kg) | 91.1±21.7 | 90.9±21.4 | 91.3±22.1 | 0.86 |
| BMI (kg/m2) | 31.2±6.9 | 31.4±6.8 | 30.9±7.1 | 0.33 |
| 24-h SBP (mmHg) | 135.9±17.8 | 143.9±16.5 | 125.5±13.5 | <0.001 |
| Nocturnal SBP (mmHg) | 134.3±20.8 | 142.3±20.2 | 123.7±16.4 | <0.001 |
| Daytime SBP (mmHg) | 137.6±16.8 | 145.4±15.4 | 127.3±12.6 | <0.001 |
| Clinic SBP (mmHg)a | 133.6±17.4 | 145.2±13 | 118.2±8.4 | <0.001 |
| Clinic DBP (mmHg) | 79.5±10.5 | 83.3±10.4 | 74.6±8.2 | <0.001 |
| MAP (mmHg) | 97.5±11.3 | 104.1±9.6 | 89.1±7.1 | <0.001 |
| Dipping status | <0.001 | |||
| Dipper | 124 (20.1) | 67 (19.1) | 57 (21.3) | |
| Reverse dipper | 241 (39.1) | 136 (38.9) | 105 (39.3) | |
| Nondipper | 252 (40.8) | 147 (42) | 105 (39.3) | |
| Masked hypertension | 162 (26) | NA | 162 (61) | NA |
| Estimated GFR (ml/min per 1.73 m2) | 43.5±15.9 | 42.5±15.8 | 44.7±15.9 | 0.10 |
| Serum creatinine (mg/dl) | 2.2±1.3 | 2.3±1.5 | 2.2±1.1 | 0.15 |
| UP/Cr group | <0.001 | |||
| ≤0.22 mg/mg | 435 (70.5) | 225 (64.2) | 210 (78.7) | |
| >0.22 mg/mg | 182 (29.5) | 125 (35.8) | 57 (21.3) | |
| Experience in AASK clinical trial phase BP goal | <0.001 | |||
| Low BP group | 310 (50.2) | 149 (42.6) | 161 (60.3) | |
| Usual BP group | 307 (49.8) | 99 (41.9) | 65 (45.8) | |
| Randomized drug | 0.49 | |||
| Ramipril | 256 (41.5) | 140 (40) | 116 (43.4) | |
| Metoprolol | 250 (40.5) | 149 (42.6) | 101 (37.8) | |
| Amlodipine | 111 (18) | 61 (17.4) | 50 (18.7) |
Means ± SDs were summarized for continuous variables and n (%) were summarized for categorical variables. For the P values, the ANOVA method was used for continuous variables and the chi-squared test was used for categorical variables. SBP, systolic BP; BMI, body mass index; MAP, mean arterial pressure; UP/Cr: urine protein/creatinine ratio; AASK, African American Study of Kidney Disease and Hypertension; NA, not applicable.
Clinic SBP is the average of all clinic BP measurements (usually three) obtained during a 60-day window of the ABPM measurement.
The pattern of ambulatory SBP was similar to that of clinic SBP, with higher values in the uncontrolled group compared with the controlled group. In those patients whose BP was controlled on the basis of clinic BP, 61% had either uncontrolled daytime or night-time BP (i.e., had masked hypertension). Mean nocturnal SBP (134.3±20.8 mmHg) was higher than clinic SBP (133.6±17.4 mmHg), both overall and among those with controlled clinic SBP (123.7±16.4 versus 118.2±8.4 mmHg, respectively). Only 20% of the participants had a normal dipping profile (i.e., dippers), whereas nondippers and reverse dippers each comprised approximately 40% in each group.
Mean BP during the AASK-CS was 132/78 mmHg, with 84% of the participants receiving either an ACEI or an angiotensin II receptor blocker. During a median follow-up of up to 5 years, 65 participants had a doubling of serum creatinine (10.5%), 106 reached ESRD (17.1%), 95 died (15.4%), and 99 had a cardiovascular event (16%). Some participants had ≥2 events; however, only the first of those events was ascertained in the renal composite outcome. Twelve participants were lost in follow-up.
ABPM Values and Dipping Status as Predictors of Renal Outcomes
Table 2 presents the Cox regression analyses relating clinic and ambulatory SBP variables with incident primary renal outcome, after stratifying by randomization assignments and controlling for age, sex, BMI, number of comorbid conditions, diabetes, and eGFR. Mean 24-hour, daytime, night-time, and clinic SBP measured at baseline were all significantly associated with incident renal outcomes 5 years later (model 1, P<0.001). After controlling for proteinuria, nocturnal SBP was of borderline significance (model 2). Controlling for phosphorus, albumin, and hemoglobin did not change the results. In contrast with SBP variables, dipping status was not predictive of outcomes after controlling for daytime ABPM SBP in the model.
Table 2.
HRs relating renal outcomes to SBP variables
| Model 1 | Model 2 | |||
|---|---|---|---|---|
| HR (95% CI) | P | HR (95% CI) | P | |
| 24-h SBP | 1.24 (1.15, 1.34) | <0.001 | 1.10 (1.01, 1.20) | 0.03 |
| Nocturnal SBP | 1.17 (1.10, 1.25) | <0.001 | 1.07 (1.00, 1.15) | 0.05 |
| Daytime SBP | 1.27 (1.16, 1.37) | <0.001 | 1.11 (1.01, 1.22) | 0.03 |
| Clinic SBP | 1.28 (1.18, 1.38) | <0.001 | 1.16 (1.07, 1.27) | 0.001 |
| Dipping status | ||||
| Reverse dipper versus dipper | 1.32 (0.88, 1.97) | 0.17 | 1.25 (0.84, 1.86) | 0.26 |
| Nondipper versus dipper | 1.03 (0.69, 1.54) | 0.87 | 0.90 (0.60, 1.35) | 0.60 |
| NDT versus dippera | 1.17 (0.81, 1.67) | 0.40 | 1.06 (0.74, 1.53) | 0.75 |
HR is expressed as per 10-mmHg increment in systolic BP. For model 1, the models were controlled for age, sex, body mass index, comorbid conditions, estimated GFR, and diabetes, and were stratified by randomization group; for model 2, the models were further controlled for proteinuria. HR, hazard ratio; SBP, systolic BP; 95% CI, 95% confidence interval.
NDT includes nondipper and reverse dipper. Results for dipping status were obtained by controlling for daytime ambulatory BP monitoring SBP in the model.
ABPM Values and Dipping Status as Predictors of Cardiovascular Outcomes
Ninety-nine participants developed a cardiovascular event during the course of the study. Table 3 presents Cox regression analyses relating cardiovascular outcomes to baseline clinic and ambulatory BP variables, stratifying by randomization assignments, and controlling for age, sex, smoking status, LDL cholesterol, diabetes mellitus (model 1), and proteinuria (model 2). In these analyses, 24-hour, night-time, daytime, and clinic SBP were significantly associated with subsequent cardiovascular outcomes (P<0.001). Dipping status did not predict cardiovascular outcomes in our population.
Table 3.
HRs relating cardiovascular outcomes to SBP variables
| Model 1 | Model 2 | |||
|---|---|---|---|---|
| HR (95% CI) | P | HR (95% CI) | P | |
| 24-h SBP | 1.30 (1.17, 1.45) | <0.001 | 1.26 (1.12, 1.41) | <0.001 |
| Nocturnal SBP | 1.22 (1.12, 1.34) | <0.001 | 1.19 (1.08, 1.31) | <0.001 |
| Daytime SBP | 1.32 (1.17, 1.48) | <0.001 | 1.26 (1.12, 1.43) | <0.001 |
| Clinical SBP | 1.24 (1.11, 1.39) | <0.001 | 1.20 (1.07, 1.35) | 0.002 |
| Dipping status | ||||
| Reverse dipper versus dipper | 1.80 (0.96, 3.38) | 0.06 | 1.77 (0.94, 3.32) | 0.07 |
| Nondipper versus dipper | 1.68 (0.90, 3.15) | 0.11 | 1.66 (0.88, 3.13) | 0.11 |
| NDT versus dippera | 1.74 (0.96, 3.13) | 0.06 | 1.72 (0.95, 3.10) | 0.07 |
HR is expressed as per 10-mmHg increment in systolic BP. The models were stratified by randomization group (BP and drug) and controlled for age, sex, smoking status, LDL cholesterol, diabetes mellitus (model 1), and proteinuria (model 2). HR, hazard ratio; SBP, systolic BP; 95% CI, 95% confidence interval.
NDT includes nondipper and reverse dipper. Results for dipping status were obtained by controlling for daytime ambulatory BP monitoring SBP in the model.
Joint Effects of Clinic and Ambulatory BP
Because ABPM and clinic BP measurements were each predictive of renal and cardiovascular endpoints, we tested whether ABPM provides additional information beyond that of clinic BP measurements in models that included all patients and in separate models for patients with controlled (<130 mmHg) and uncontrolled (>130 mmHg) clinic SBP (Table 4). Our results suggest that there may be a different risk relationship between ABPM and renal and cardiovascular outcomes that is dependent on degree of office BP control.
Table 4.
HRs relating renal and cardiovascular outcomes to 24-hour, daytime, and night-time ambulatory BP, overall and in models stratified by clinic SBP control at baseline
| Overall (n=617) | Controlled Clinic BP, Clinic SBP <130 mmHg (n=267) | Uncontrolled Clinic BP, Clinic SBP ≥130 mmHg (n=350) | P for Interaction | ||
|---|---|---|---|---|---|
| HR (95% CI) | P Value | HR (95% CI) | HR (95% CI) | ||
| ESRD, death or doubling of SCr | |||||
| Events (event rate)a | 200 (0.079) | 65 (0.055) | 135 (0.099) | ||
| Model 1 | |||||
| 24-h SBP | 1.11 (1.01, 1.23) | 0.03 | 1.45 (1.17, 1.79) | 1.03 (0.91, 1.17) | 0.01 |
| Night-time SBP | 1.07 (0.99, 1.16) | 0.07 | 1.33 (1.12, 1.57) | 1.01 (0.92, 1.12) | 0.01 |
| Daytime SBP | 1.12 (1.01, 1.25) | 0.03 | 1.42 (1.11, 1.8) | 1.05 (0.92, 1.20) | 0.08 |
| Model 2 | |||||
| 24-h SBP | 1.01 (0.91, 1.12) | 0.87 | 1.33 (1.04, 1.70) | 0.96 (0.84, 1.10) | 0.02 |
| Night-time SBP | 1.01 (0.93, 1.10) | 0.78 | 1.25 (1.03, 1.51) | 0.97 (0.88, 1.08) | 0.02 |
| Daytime SBP | 1.00 (0.88, 1.13) | 0.95 | 1.26 (0.96, 1.66) | 0.97 (0.84, 1.12) | 0.02 |
| Cardiovascular events | |||||
| Events (event rate)a | 99 (0.040) | 38 (0.033) | 61 (0.045) | ||
| Model 1 | |||||
| 24-h SBP | 1.23 (1.07, 1.42) | 0.003 | 1.30 (0.98, 1.72) | 1.25 (1.05, 1.47) | 0.75 |
| Night-time SBP | 1.16 (1.04, 1.29) | 0.01 | 1.13 (0.91, 1.41) | 1.19 (1.05, 1.36) | 0.87 |
| Daytime SBP | 1.24 (1.06, 1.45) | 0.01 | 1.45 (1.07, 1.97) | 1.20 (1.00, 1.45) | 0.38 |
| Model 2 | |||||
| 24-h SBP | 1.26 (1.12, 1.41) | <0.001 | 1.27 (0.97, 1.67) | 1.31 (1.13, 1.53) | 0.98 |
| Night-time SBP | 1.19 (1.08, 1.31) | <0.001 | 1.12 (0.90, 1.39) | 1.23 (1.09, 1.39) | 0.64 |
| Daytime SBP | 1.26 (1.12, 1.43) | <0.001 | 1.43 (1.07, 1.92) | 1.29 (1.09, 1.53) | 0.57 |
HR is expressed as per 10-mmHg increment in SBP. The models were stratified by randomization group (BP and drug) and controlled for age, sex, smoking status, LDL cholesterol, diabetes mellitus (model 1), and proteinuria (model 2). For renal outcomes, the models control for clinic SBP. HR, hazard ratio; SBP, systolic BP; 95% CI, 95% confidence interval; SCr, serum creatinine.
Number of events (event rate per patient-year).
As shown in Table 4, for renal outcomes, there was an interaction such that the effect of the ABPM variables differed based on whether clinic SBP was controlled. In participants with controlled clinic BP, all ABPM time periods were significantly associated with renal outcomes (model 1). However, daytime BP was no longer predictive after controlling for proteinuria (model 2). In contrast, ABPM was not predictive of renal outcomes among participants who had uncontrolled clinic SBP. With respect to cardiovascular events, ABPM was consistently associated with outcomes based on a similar point estimate of hazard ratios and nonstatistically significant P values for interaction. When the analysis was confined exclusively to patients with masked hypertension, there was no significant relationship between level of ambulatory BP (after controlling for clinic BP) and either renal or cardiovascular outcomes (data not shown).
Discussion
In the AASK-CS that enrolled African Americans with CKD attributed to hypertension, we demonstrated that ABPM adds prognostic information beyond that of well characterized and standardized clinic BP. Importantly, ABPM adds prognostic information in patients with controlled clinic BP in terms of renal outcomes, and is also informative of cardiovascular outcomes in patients with uncontrolled clinic BP.
Our results demonstrate that in a large cohort of participants with CKD followed for 5 years, 24-hour SBP predicts both renal and cardiovascular outcomes. Further analyses based on daytime and night-time SBP levels reveal that both parameters were predictive of renal and cardiovascular outcomes. These results contrast with recent publications stressing the role of night-time BP as a better predictor of renal and cardiovascular complications than daytime SBP (19–24). Minutolo et al. recently demonstrated in a multicenter prospective cohort study in CKD patients that night-time BP measurement was a more accurate predictor of renal and cardiovascular risk than daytime values (24). Similarly, Redon et al. found that night-time SBP >130 mmHg was associated with an increased risk of reaching the primary outcome of the composite of death and ESRD in a cohort of 79 patients with nondiabetic CKD stages 3 and 4 managed using usual care and followed for an average of 44 months (19). In a meta-analysis of four prospective cohort studies in the general population in Europe by Fagard et al., night-time BP predicted all-cause and cardiovascular mortality, coronary heart disease, and stroke, whereas daytime BP did not add prognostic precision to night-time pressure (20). Similar findings were observed by the International Database on Ambulatory Blood Pressure Monitoring in relation to Cardiovascular Outcomes investigators in which night-time BP predicted mortality outcomes, whereas daytime BP predicted only noncardiovascular mortality after adjustment for night-time BP (21–23).
An important finding of our study is the minimal difference between daytime (137 mmHg) and night-time (134 mmHg) SBP; the 3.3 mmHg difference in our participants contrasts with a 13.7-mmHg mean difference and a 9-mmHg mean difference in the meta-analysis by Fagard et al. (20) and the recent study by Minutolo et al. (24). The similarity between daytime and night-time SBP highlights the presence of night-time hypertension in our patients with CKD. Daytime SBP values achieved in the AASK-CS were very close to the upper limit of normal (135 mmHg), whereas night-time SBP of 134 mmHg was much higher than normal values (25). The elevation in night-time SBP was observed in spite of the two to four daily antihypertensive agents taken by our participants.
As previously described by Pogue et al., a large proportion of our participants had abnormal dipping pattern (80%), with 40% of them being reverse dippers (11). Absence of a normal dipping pattern has been proposed as a risk factor for progression of renal disease and cardiovascular morbidity and mortality (1–5,8–15,20–24). Studies in CKD populations have demonstrated that loss of the dipping pattern is associated with increased proteinuria and accelerated progression of renal disease and poor allograft function when transplant participants were evaluated 1 year after transplantation (15). In one small study, restoring a normal dipping pattern with night-time administration of antihypertensive medication reduced proteinuria, stressing the potential role of a normal circadian rhythm in the progression of CKD (26).
Dipping status did not predict progression of renal disease or cardiovascular events in our participants, after controlling for daytime BP. One possibility is that the study was underpowered to detect this signal because of the limited number of participants with a normal dipping pattern. Another possibility is that absolute levels of night-time BP, rather than classification of dipper/nondipper status, may be more important from a prognostic standpoint.
Our study also demonstrates that standardized clinic BP measurements were predictive of both incident renal outcomes and cardiovascular events. These results differ from previous reports that have stressed the benefits of ABPM over clinic BP in predicting both renal and cardiovascular outcomes. Previous studies in participants with CKD recruited from a renal and/or general medicine clinic reported that ABPM and home BP measurements are better predictors of proteinuria and target organ damage than routine clinic BP values (24,27). ABPM was also shown to be a better predictor of target organ damage in CKD patients where ABPM had a stronger correlation with left ventricular hypertrophy than clinic measurements (25). One possible explanation is the large number and high quality of standardized clinic BP measurements that we obtained in AASK-CS.
The role of masked hypertension as a predictor of progression of kidney disease in CKD patients was previously demonstrated by Agarwal and Andersen using home BP recordings and comparing these recordings with standardized clinic measurements (28). Our observation that ABPM adds prognostic information for renal outcomes in patients with controlled clinic BP is consistent with this finding.
Our study has both limitations and strengths. Limitations include the relatively small number of cardiovascular events and the focus on one type of CKD patients, specifically, African Americans with CKD attributed to hypertension. Another potential limitation is the fact that participants in the AASK-CS represent a survivorship cohort (i.e., none died or experienced ESRD during the AASK trial). However, as previously documented, the renal event rate was high during the cohort phase of the study and was similar to the event rate of the trial (29). In addition, because our population had existing CKD, we cannot address the role of BP in CKD incidence, but are restricted to evaluating the role of elevated BP in CKD progression. Strengths of our study include the large number of participants, the large number and high quality of clinic BP, the length of the follow-up, and the simultaneous evaluation of renal and cardiovascular outcomes.
In conclusion, results from our study document that ABPM provides additional information beyond that of multiple, high-quality clinic BP in predicting renal and cardiovascular outcomes in African Americans with hypertensive CKD. In contrast to the general population, in which ABPM is used to identify patients with white-coat hypertension, the primary utility of ABPM in African-American CKD patients is to identify high-risk patients with controlled clinic BP.
Disclosures
None.
Supplementary Material
Acknowledgments
This study was supported by grants from the National Institute of Diabetes and Digestive and Kidney Diseases, the National Center for Minority Health and Health Disparities, and King-Monarch Pharmaceutical.
Portions of these data were presented at the annual meetings of the American Society of Nephrology, November 4–9, 2008, in Philadelphia, Pennsylvania, and October 27–November 1, 2009, in San Diego, California.
Footnotes
Published online ahead of print. Publication date available at www.cjasn.org.
This article contains supplemental material online at http://cjasn.asnjournals.org/lookup/suppl/doi:10.2215/CJN.11301111/-/DCSupplemental.
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