Hypertension is an important risk factor for cardiovascular events and progression of chronic kidney disease (CKD) (1–2). Its prevalence is 79% in patients with CKD stage 1 and 96% in stages 4 and 5 (3). Transplantation is the best treatment for end-stage renal failure (4), allowing partial recovery of renal function. However, approximately 70% of stable transplants have an estimated glomerular filtration rate (e-GFR) less than 60 mL/min/1.73 m2 (5). After transplantation, the prevalence of hypertension is as high as 90% (6). Apart from classical risk factors, immunosuppressive drugs such as steroids or calcineurin inhibitors also contribute to hypertension (7). Corticosteroids favor sodium retention and anti-calcineuric drugs activate the sympathetic nervous system, stimulate endothelin release, and inhibit inducible nitric oxide (8, 9). These observations suggest that hypertension could be more prevalent or more severe, or both, in transplants than in CKD patients with a similar renal function.
In renal transplant patients, hypertension is associated with decreased allograft survival, major adverse cardiac events, and poorer patient survival (10–12). The association between hypertension and outcome is independent from renal function (12, 13). Despite no specific clinical trials that have been done to evaluate the effect of blood pressure (BP) control in kidney transplants, epidemiologic data suggest that BP control improves graft and patient survival (11). Accurate diagnosis and precise monitoring of BP is a necessary condition for an efficient treatment. However, office blood pressure has important limitations to diagnose and to treat hypertension because of its intra- and inter-individual variability. On the contrary, ambulatory blood pressure monitoring (ABPM) allows a more reproducible BP estimate. In patients with CKD, ABPM better detects patients at risk of cardiovascular events and at risk for progression of CKD than office BP (2), and in patients with a functioning graft, ABPM but not office BP was associated with 1-year serum creatinine (14).
The combination of the information obtained by office BP and ABPM shows that office BP misclassifies a proportion of patients with regards to hypertension, the so-called white coat and masked hypertension (15, 16). ABPM also provides information about the circadian pattern of BP. Classification of hypertensive patients according to nocturnal BP dip from day to night into dipper and non-dipper further contributes to define cardiovascular risk (17) and the risk of CKD progression (2). In renal transplants, ABPM pattern is associated with an increased probability of cardiovascular events and graft failure (18).
Thus, the aim of the present study is to evaluate office BP and ABPM in two cohorts of transplant and CKD patients with an e-GFR less than 60 mL/min/1.73 m2 to better characterize how transplantation contributes to prevalence, severity, and circadian pattern of hypertension.
Demographic Characteristics of Patients
During the study period, a total of 3,125 patients were visited at our outpatient clinic to recruit 100 transplants and 100 patients with CKD that accomplished the inclusion criteria. Reasons for exclusion were age equal to or greater than 70 years (n=1,986), e-GFR greater than 60 mL/min/1.73 m2 (n=582), previous history of cardiovascular disease (n=104), hemodialysis treatment (n=124), more than one kidney transplant (n=41), patients with other transplanted organs (n=35), CKD patients receiving any immunosuppressive regimen for glomerulonephritis (n=23), active neoplasia (n=16), and declined participation (n=14). In eight transplants and three patients with CKD, 24-hr BP monitoring was not adequately obtained. Thus, 92 transplants and 97 patients with chronic kidney disease were included.
Demographic characteristics of patients are summarized in Table 1. The proportion of patients with diabetic nephropathy was lower and the time since the diagnosis of renal disease was higher in transplants. On the other hand, proteinuria-to-creatinine ratio was higher in patients with CKD.
Eighteen transplants were receiving a ciclosporin, 69 a tacrolimus, and five an inhibitor of the mammalian target of rapamycin (i-mTOR)-based regimen. At the time of study, 64 transplants were receiving steroids and 82 were receiving mycophenolate mofetil.
Office and Ambulatory Blood Pressure Monitoring
Office systolic and diastolic BP was not different between groups. On the contrary, ABPM showed significantly higher BP values in renal transplants, especially for sleep SBP. When office BP and ABPM values were used to classify hypertension, the proportion of normotensive, white coat, masked hypertension, and hypertension was similar between groups. Additionally, the circadian pattern of BP and the number of antihypertensive drugs was not different (Table 2).
When patients were classified according to BP patterns associated with highest cardiovascular risk, that is, non-dipper pattern (2, 17), and nocturnal hypertension (19, 20), renal transplants more frequently showed the combination of these two patterns as shown in Figure 1.
Blood Pressure and Immunosuppression in Kidney Transplants
In patients receiving ciclosporin (n=18), 24-hr SBP was 136.6±15.2 mm Hg and in patients with tacrolimus (n=69) was 133.7±14.4 mm Hg (P=0.45). The mean 24-hr DBP was 80.9±7.6 mm Hg and 79.5±11.3 mm Hg for patients with ciclosporin and tacrolimus regimes, respectively (P=0.62). We did not find any differences in awake and sleep BP (data not shown).
In patients receiving steroids (n=64), 24-hr SBP was 133.9±14.8 mm Hg and in patients without steroids (n= 28) was 133.8±13.4 mm Hg (P=0.95), and 24-hr DBP was 79.8±10.8 mm Hg in patients with steroids and 79.6±9.6 mm Hg in patients not receiving steroids (P=0.93). We did not find any differences in awake and sleep BP (data not shown).
Transplantation as a Predictive Variable for 24-hr, Awake, and Sleep SBP
Univariate and multivariate analysis were performed to evaluate the contribution of transplantation to the prediction of 24-hr systolic BP. For this purpose, all patients were included and transplantation was considered a predictive variable. The following variables were independent predictors of 24-hr SBP: proteinuria-to-creatinine ratio (R=0.284), transplantation (R= 0.426), diabetes (R=0.471), and smoking (R=0.495). Independent predictors of awake SBP were proteinuria-to-creatinine ratio (R=0.257), transplantation (R= 0.380), and diabetes (R=0.427). Similarly, transplantation (R=0.285), proteinuria-to-creatinine ratio (R=0.467), and diabetes (R=0.505) were also predictors of sleep SBP. Despite time of renal disease was different between transplants and patients with CKD, this variable was not associated with SBP and, accordingly, was not considered in the multivariate analysis.
In Figure 2, differences between renal transplants and CKD patients for non-adjusted and adjusted 24-hr, awake, and sleep SBP are shown. The major difference between renal transplants and CKD patients was observed in sleep SBP.
Hypertension in renal transplants in comparison with patients with CKD and similar renal function has not been well characterized. In this study, we did not observe any difference in office BP between transplants and CKD patients with an e-GFR less than 60 mL/min/1.73 m2. However, hypertension was more severe in kidney transplants when measured with ABPM, mainly caused by increased systolic 24-hr BP, and especially sleep SBP. Thus, office blood pressure underestimates the severity of hypertension in transplant patients. This observation may have important clinical consequences because hypertension in kidney transplants is an independent risk factor for graft failure (10) and cardiovascular mortality (11). Despite the significant difference in ABPM, the mean number of antihypertensive drugs was not different. The difference in systolic 24-hr BP between kidney transplants and CKD patients was 7.7 mm Hg. The difference in sleep SBP between groups was even higher, reaching 11 mm Hg. This result is remarkable if we take into consideration that despite patients were selected according to e-GFR at entry, transplant patients had better renal function and less severe proteinuria, factors that are strongly associated with hypertension (21–23). To further evaluate the contribution of transplantation to hypertension, different multivariate analysis were done considering 24-hr, awake, and sleep SBP as the dependent variable, and transplantation was always an independent predictor of SBP. Other independent risk factors were proteinuria-to-creatinine ratio and diabetes as it has been previously described (24, 25). Of note, when 24-hr, awake, and sleep BP were compared between transplants and CKD patients after correcting for all confounding variables, the differences between both cohorts were even higher, 12 mm Hg for 24-hr BP, 10 mm Hg for awake BP, and 15 mm Hg for sleep BP. These differences may have important consequences on long-term patient survival (11). It should be taken into consideration that each 10 mm Hg increase of SBP above 140 mm Hg is associated with an increased relative risk of 1.17 for death-censored graft failure and of 1.18 for patient death (12). Furthermore, the proportion of hypertensive patterns associated with higher cardiovascular risk, that is, non-dippers and nocturnal hypertension (20), were higher in renal transplants. In the present study, the prevalence of nocturnal hypertension was as high as 79%. There is scarce information on the prevalence of nocturnal hypertension in adult recipients, but in children the prevalence of nocturnal hypertension varies between 55% and 68% (26, 27). In renal transplants, immunosuppression, especially ciclosporin and steroids, contribute to hypertension (28). In a clinical trial of 3-month conversion from ciclosporin to sirolimus, there was a systolic BP decrease of 6.3 mm Hg at 1 year paralleled by an e-GFR improvement of 6.0 mL/min/1.73 m2 (29). In the BENEFIT study comparing two different belatacept regimens with a ciclosporin-based regimen, systolic blood pressure was 133, 131, and 139 mm Hg and iothalamate measured GFR was 65, 63, and 50 mL/min/1.73 m2, respectively (30). There are few trials evaluating the effect of tacrolimus withdrawal on BP and renal function. A recent trial showed no effect of conversion from tacrolimus to sirolimus at 1 year on hypertension and renal function (31), a result that is in agreement with a neutral effect of tacrolimus when compared to ciclosporin on renal cortical flow (32) and on measured GFR in healthy subjects (33). In the present study, approximately 80% of patients were treated with tacrolimus. Despite BP was slightly higher in ciclosporin-treated patients, this difference did not reach statistical significance. Hence, the contribution of ciclosporin to overall BP increase in renal transplants in our cohort should have been very modest. In the other hand, nearly 80% of patients were receiving prednisone that contributes to hypertension by raising systolic BP between 2 and 4 mm Hg (34); however, we failed to show any difference in BP in patients with and without steroids. Overall, our data suggest that the effect of treatment is not sufficient to explain the difference between transplants and CKD patients.
Limitations of this study are related to the relative small sample size, and its cross-sectional nature does not allow defining the temporal sequence of the associations between variables. Follow-up of this cohort may help to better understand the clinical consequences of this BP increase in renal transplants in comparison with CKD patients with similar renal function. In the present study, home blood pressure monitoring was not done. Despite this measure better correlates with 24-hr ABPM than office BP (35), it does not allow to evaluate nocturnal BP, the major contributor to hypertension in kidney transplants. In summary, we observed that hypertension is more severe in kidney transplants than in patients with CKD with similar renal function whereas office BP does not detect this difference. The major difference between transplants and CKD patients was observed in sleep BP. Thus, ABPM should be the preferred method to assess blood pressure in kidney transplants to assure BP control and avoid hypertension-associated long-term consequences.
MATERIALS AND METHODS
One hundred patients with a first renal transplant and 100 patients with chronic kidney disease were consecutively recruited from our outpatient clinic between June and September 2011 according to the following criteria: (1) age greater than or equal to 18 years and less than or equal to 70 years, (2) patients with eGFR less than 60 mL/min/1.73 m2 not receiving dialysis treatment, (3) no history of cardiovascular events (angina, myocardial infarction, heart failure, stroke, or peripheral vascular disease), (4) stable renal function defined as variability of e-GFR less than 10% between the actual and previous visit, and (5) signed informed consent. All patients were instructed to follow a hyposodic diet consisting of a sodium intake less than 6 g per day. Patients with CKD treated with steroids or immunosuppressants for glomerulonephritis were excluded. This study was approved by the ethical committee of Hospital Universitari Vall d’Hebron.
At entry, the following variables were recorded: age; gender; height and weight; body mass index, calculated as weight divided by squared height; waist perimeter; active smoking (yes or no); time since diagnosis of renal disease; time on dialysis and time since transplantation; number of antihypertensive drugs and use of angiotensin-converting enzyme inhibitors or angiotensin receptor blockers; and immunosuppressive treatment in renal transplants.
The following parameters were determined at entry: hemoglobin (g/dL), ferritin (ng/dL), glycemia (mg/dL), insulinemia (IU/mL), HOMA (homeostatic model assessment) index [(insulinemia×glycemia)/22.5], glycated hemoglobin (%), total cholesterol (mg/dL), triglycerides (mg/dL), HDL (mg/dL) and LDL cholesterol (mg/dL), homocysteine (mmol/L), serum creatinine (mg/dL), proteinuria-to-creatinine ratio (g/g), serum calcium (mg/dL), serum phosphate (mg/dL), 25(OH) vitamin D3 (pg/mL), and serum i-PTH (pg/mL). In patients without previous history of diabetes mellitus, a 2-hr oral glucose tolerance test after administration of 75 g of glucose was done.
Diabetes was defined according to American Diabetes Association 2010 (36) in patients with antidiabetic treatment or fasting glucose greater than or equal to 126 mg/dL, random glucose determination greater than or equal to 200 mg/dL, oral glucose tolerance test greater than or equal to 200 mg/dL, or glycated hemoglobin greater than or equal to 6.5%. Estimated GFR (e-GFR) was calculated by the MDRD-4 formula (37).
Office and Ambulatory Blood Pressure Monitoring (ABPM)
ABPM was measured using an overnight-automated ABPM monitor (Spacelab 90207; Spacelabs Healthcare, USA) with appropriate cuff sizes for each patient. In patients with arteriovenous fistula, BP was measured in the contralateral arm. ABPM was performed for 24 hr and BP was recorded every 20 min during awake hours (8–23 hr) and every 30 min during nocturnal hours (23–8 hr). The patients recorded their sleep and wake times during the BP monitoring, and these times were used to calculate sleep and awake BP averages. We used ABP Report Management System version 188.8.131.52. from Spacelabs Healthcare, and we obtained average 24-hr systolic blood pressure (SBP), 24-hr diastolic blood pressure (DBP), 24-hr pulse pressure, and the awake and sleep SBP and DBP. ABPM hypertension was defined as 24-hr BP greater than or equal to 130/80 mm Hg, awake BP greater than or equal to 135/85 mm Hg, and sleep BP greater than or equal to 120/70 mm Hg (38). On the basis of circadian BP, patients were classified into dippers (ΔSBP≥10%) and non-dippers (0<ΔSBP<10). ABPM with less than 70% of BP measurements were not considered.
Office blood pressure was determined three times at 5-min intervals after 10 min of rest in the contralateral arm of arteriovenous fistula with Omron M3 Digital Automatic Monitor (Healthcare Europe, Netherlands). Office hypertension was defined as SBP greater than or equal to 140 or DBP greater than or equal to 90 mm Hg (38).
Normotension was defined as normal blood pressure by office and ABPM, white coat hypertension was defined as high office BP and controlled ABPM, masked hypertension was defined as normal office BP and uncontrolled ABPM, and hypertension was defined as high blood pressure by both methods.
The difference in BP between transplants and CKD patients has not been previously studied. Accordingly, this is a hypothesis-generating cohort study and no formal power calculation was done to estimate minimum sample size to detect a predefined blood pressure difference. Continuous normally distributed variables are presented as mean±SD. To compare categorical and continuous normally distributed variables, chi-squared and Student t test were employed, respectively. For non-normally distributive variables, Mann-Whitney U test was applied. All tests were two-tailed and a P value less than 0.05 was considered significant. In case of multiple comparisons, Bonferroni correction was applied to calculate the P value.
Univariate and stepwise multivariate regression analysis were employed to evaluate variables associated with 24-hr, awake, and sleep SBP. For multivariate analysis, we considered all variables with P value less than 0.1. To estimate the adjusted difference between 24-hr, awake, and sleep SBP between CKD and transplants, the β coefficient of the stepwise regression was employed.
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