The week before the ABPM study each patient’s BP was measured by a mercury sphygmomanometer whose cuff was adapted to the circumference of the arm controlateral to the AVF, with subjects resting for at least 15 min before the measurement. Systolic BP (SBP) was recorded at Korotkoff phase I and diastolic BP (DBP) was recorded at Korotkoff phase V. The average of three BP measurements performed on three different days was taken as office BP.
ABPM measurements were recorded every 15 min between 7:00 a.m. and 10:00 p.m. and every 30 min from 10 p.m. to 7 a.m. The ABPM study was considered invalid and was repeated on a different day if data were missing for more than 2 consecutive hours. BP during sleep was analyzed based on the data derived from each patient’s event diaries. We derived the average 24-hr SBP and DBP, the awake SBP and DBP, and the asleep SBP and DBP from the ABPM data. Pulse pressure (PP) was calculated as SBP−DBP for each set of BP measurement, office or ABPM. Dipping was defined as more than or equal to 10% reduction in nighttime ambulatory BP compared with daytime ambulatory BP, whereas reverse dipping was defined as no reduction or even an increase in nighttime ABPM BP compared with daytime values (15). AH was defined as an average BP more than or equal to 130/80 mm Hg according to the criteria issued by the NKF-Kidney Disease Outcomes Quality Initiative Clinical Practice Guidelines on Hypertension and Antihypertensive agents in chronic kidney disease (16). On the basis of ABPM records, patients were classified as normotensives, dippers, nondippers, or reverse dippers.
Serum creatinine, hemoglobin (Hgb) concentration, serum cholesterol, triglycerides, uric acid levels, and 24-hr urinary protein excretion rate were measured for each patient. Body mass index (BMI) was calculated as weight/height2. Estimated glomerular filtration rate was calculated according to the four-variable modification of diet in renal disease (MDRD) equation (17). The presence of diabetes before transplantation and new-onset diabetes after transplantation, the duration of dialysis before transplantation, the number and the class of antihypertensive medications at the time of the ABPM study, and the various immunosuppressive regimens were also taken into consideration for each subject.
Furthermore, data related to transplantation [namely, transplantation from living or deceased donor, prior kidney transplant, donor age, both human leukocyte antigen and DR mismatches, recipients’ % panel reactivity antibodies, cold ischemia time, the occurrence of delayed graft function and of acute rejection episodes in the first posttransplant year, and serum creatinine values at discharge from our Renal Unit after renal transplantation] were also retrieved for each patient.
Data are presented as mean±SD. Comparisons between groups were made by the t test for unpaired data or by analysis of variance (ANOVA) for continuous variables, when appropriate. Newman-Keuls post hoc analysis was performed to assess intergroup differences if the ANOVA test was significant. Fisher’s exact test or chi-square test, when appropriate, was used for between-group comparisons of categorical variables. The significance of association between each set of measured BP values and continuous variables (age, duration of dialysis before transplantation, BMI, serum creatinine, Hgb, total cholesterol, triglycerides and uric acid levels, number of antihypertensives, and daily urinary protein excretion) was determined by calculating Pearson’s correlation coefficient (r). Forward stepwise multiple regression analysis was performed to identify the strongest predictors of both serum creatinine and daily urinary protein excretion at the time of ABPM, both of which were included in the model as dependent variables because they are assumed to be reliable indexes of allograft outcome. The following continuous independent variables were included in the multiple regression model: both office and ABPM BP values, patient’s age, time spent on dialysis, BMI, Hgb, serum lipids, serum uric acid, the number of antihypertensive agents, donor age, both human leukocyte antigen and DR mismatches, % panel reactivity antibodies, cold ischemia time, and creatinine value at discharge from hospital after transplantation. A general linear model was used to analyze the simultaneous effects of categorical variables such as gender, the presence of diabetes, and the occurrence of delayed graft function or acute rejection in the first posttransplant year.
Demographic, clinical, and laboratory data of the 94 RTRs are reported in Table 1, whereas Table 2 shows both office and ABPM BP values of the study population. Office BP values showed that only 5 (5%) patients had BP values lower than 130/80 mm Hg.
On the basis of ABPM measurements, 5 patients (5%) were found to have normal BP values, 15 (16%) were classified as dippers, 47 (50%) as nondippers, and 27 (29%) as reverse dippers. Comparisons of office BP levels among dippers, nondippers, and reverse dippers revealed that both SBP and PP were lower in reverse dippers compared with nondippers (Table 3). No differences in biochemical parameters were observed in the three groups (Table 3). No differences were observed among the three groups regarding both the number and the different classes of antihypertensive medications (Table 3).
Of the 94 patients, 12 had been on peritoneal dialysis before transplant, eight had thrombosed vascular access, and 74 had a still functioning AVF at the time of ABPM. No differences in office or ABPM BP values were observed in these three groups.
Patients were then further subgrouped solely on the basis of the number of antihypertensive medications being administered at the time of ABPM: six patients were receiving no therapy (group 0), 25 patients were taking one medication (group 1), 30 patients were on two medications (group 2), and 33 patients were receiving three or more (group 3). No differences in BP values, office or ABPM, were observed among these four subgroups. By contrast, serum creatinine levels were higher in group 3 (2.4±0.8 mg/dL when compared with 2.0±0.6 in group 2, 1.8±0.6 in group 1, and 2.2±1.0 in group 0, P=0.022, ANOVA). However, no differences were shown regarding gender, age, dialytic age, serum lipids and uric acid, Hgb concentration, daily proteinuria, and sodium excretion among the four groups.
Eighty-one RTRs receiving calcineurin inhibitors were further subdivided on the basis of the medication, cyclosporine or tacrolimus, that was administered. Although no differences were observed in office BP levels, ABPM analysis of patients receiving tacrolimus revealed lower PP values, both awake and asleep. Tacrolimus-treated patients also had higher estimated glomerular filtration rate and lower cholesterol levels compared with patients receiving cyclosporine (Table 4).
Table 5 shows significant associations of ABPM BP values with continuous variables. Interestingly, the tight, direct association between awake SBP and proteinuria persisted when we carried out separate analyses of the 59 patients with detectable albuminuria (r=0.52; P<0.0001; Fig. 1) and the 47 patients with macroalbuminuria (r=0.51; P=0.0003). Figure 2 shows the strong association of asleep DBP with serum creatinine.
Forward stepwise multiple regression analysis showed that awake SBP (β coefficient 0.301; standardized β coefficient 0.409; P=0.002) was the only significant predictor of daily proteinuria, according to a model that accounted for 39% of the total variance of daily urinary protein excretion (F=2.428; P=0.005). Furthermore, serum creatinine at discharge from hospital after transplantation (β coefficient 0.419; standardized β coefficient 0.397; P<0.0001) and asleep DBP (β coefficient 0.150; standardized β coefficient 0.215; P=0.03) were the only significant predictors of serum creatinine at the time of ABPM according to a model that accounted for 49% of total creatinine variance (F=7.761; P<0.0001).
Office BP values were immediately discharged by the forward stepwise multiple regression model, thus confirming the results of correlation analysis that showed only a slight and not significant association between office SBP and proteinuria (P=0.06) and no significant associations between 1-year serum creatinine and each set of measured office BPs.
Our study shows that 1 year after transplantation only 5% of patients reached what are considered optimal target BP levels for RTRs (16). This figure is consistent with reports by Mange et al. (2) and highlights how difficult it is to achieve adequate BP control in RTRs, and how nephrologists involved in clinical renal transplant management settle for higher-than-recommended BP target levels, even though AH, among nonimmunologic factors (18, 19), plays a major role in renal transplant outcome (1, 2).
The most important and new finding of our study, in fact, is that BP proved to be an even stronger factor associated with renal graft damage than traditional immunologic factors.
The second most important finding is that ABPM both improved our awareness of AH in RTRs and disclosed the relationship between BP load and graft dysfunction. In our cohort, ABPM identified almost 30% of subjects with nocturnal increases in BP levels whose office pressure was significantly lower than the office BP of the other hypertensive patients, which is why we misunderstood their true BP load. Moreover, ABPM highlighted the existence of a direct association between BP and both serum creatinine and proteinuria.
Our study is indeed the first to show that awake SBP is the only significant factor associated with daily urinary protein excretion in kidney transplant recipients. This finding is consistent with a previous report in the chronic kidney disease population showing that elevated daytime SBP was strongly associated with proteinuria (20).
The role proteinuria plays in both graft and RTR survival has recently been emphasized (21, 22). Although proteinuria is a marker of recurrent or de novo glomerular disease and mainly the result of immunologic kidney transplant damage (14), it may worsen if inadequate BP control should result in glomerular hypertension and subsequently in sclerosis (23). Accordingly, a recent study showed that better BP control is associated with a decrease in daily urinary protein excretion in RTRs (21). It is noteworthy that in our sample, awake SBP proved to be the only correlate of daily urinary protein excretion even when both immunologic and nonimmunologic data related to transplantation were taken into account. The significance of this link and its relationship with immunologic mechanisms that are possibly associated with renal graft injury are beyond the scope and the design of a clinical study as ours, and warrant further investigation.
Among our patients, asleep DBP assessed at 1 year from transplantation together with serum creatinine at discharge from hospital after transplantation were the only significant correlates to 1-year graft function, whereas no immunologic parameters were found to be significantly associated with serum creatinine values at the time of ABPM. This finding emphasizes the role of nocturnal hypertension in predicting poor renal transplant outcome (24). However, at variance with the study by Wadei et al. where nondipping systolic behavior predicted reduced glomerular filtration rate, in our population impaired graft function was associated with nocturnal diastolic hypertension. We do not have a reliable explanation for this finding, and we can only speculate that prolonged and undiagnosed nocturnal AH may have induced progressive impairment of graft function in our patients.
What we believe to be relevant is that the close association between awake SBP and daily urinary protein excretion and between asleep DBP and serum creatinine was missed by routine office BP measurement, and could only be disclosed by 24-hr BP monitoring. Accordingly, this result raises the question of whether more aggressive antihypertensive therapy with different 24-hr time schedules should be administered to RTRs with overt proteinuria and to patients with reduced graft function, regardless of their causes and mechanisms.
Another interesting finding of our study is that RTRs receiving tacrolimus have lower PP values. This is consistent with a previous report showing that RTRs on tacrolimus have reduced arterial stiffness, thus possibly explaining their reportedly better cardiovascular outcome (25). Interestingly, this BP pattern was only revealed by ABPM, because no differences were observed between the office PP levels of RTRs on tacrolimus and the office PP levels of patients receiving cyclosporine.
Finally, ABPM showed a direct association between each set of measured BPs and serum triglycerides. Elevated serum triglyceride levels among our patients were likely the result of steroid therapy, and may have been an indirect expression of insulin resistance (26). Indeed, RTRs are more frequently insulin resistant than healthy controls matched for age and BMI, and steroid therapy is reportedly a predominant factor involved in this high prevalence (27). Considering that AH is significantly related to insulin resistance (28), and that all patients in our cohort were on maintenance steroid therapy, we cannot rule out the possibility that the association we found between BP values assessed by ABPM and abnormal triglyceride levels could be the effect of a trend toward insulin resistance, which was not directly assessed in our cohort.
Admittedly, our study has some other limitations. First of all, it is a single-center study with a small sample size. Second, data concerning long-term outcome are missing. Finally, our results only refer to patients whose kidney graft continued to function for more than 1 year.
However, this is the first study to evaluate the relationship between 24-hr BP profile and both creatinine and daily urinary protein excretion in RTRs. According to our findings, ABPM seems to be a truly important tool for both improving the diagnostic accuracy of AH in RTRs and estimating the association between actual BP load and renal target organ damage in this subset of patients. In light of our results, it would seem wise to adopt ABPM in the clinical management of kidney transplant recipients, at least in those with renal graft dysfunction, as expressed by increased serum creatinine and detectable proteinuria.
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Keywords:© 2009 Lippincott Williams & Wilkins, Inc.
Blood pressure; ABPM; Kidney transplant recipients; Outcome; Proteinuria