Advances in Peritoneal Dialysis, Vol. 31, 2015 Kei Yokota, 1,2 Tsutomu Sakurada, 1 Kenichiro Koitabashi, 1 Yugo Shibagaki, 1 Kazuomi Kario, 2 Kenjiro Kimura 3 Association Between Residual Kidney Function and Visit-to-Visit Blood Pressure Variability in Peritoneal Dialysis Patients Visit-to-visit blood pressure (BP) variability has recently been recognized as an important risk factor for decline of residual kidney function (RKF) in patients with chronic kidney disease. However, little is known about the impact of visit-to-visit BP variability on RKF in peritoneal dialysis (PD) patients. We retrospectively studied the association between RKF and visit-to-visit BP variability in 42 patients who started on PD between February 2006 and March 2012. Residual kidney function was defined as the mean of the urea and creatinine clearances in the patients. Visit-to-visit BP variability was defined as the average real variability of BP measurements taken during 12 consecutive visits after the start of PD. A significant association between the slope of RKF after the start of PD and the visit-to-visit variability of systolic BP was evident (r = 0.353, p = 0.022). On multiple regression analysis, the association was significant (p = 0.024) after adjustments for possible confounders (proteinuria, estimated glomerular filtration rate, and mean systolic BP). Decline in RKF was significantly associated with visit-to-visit BP variability in PD patients. The results suggest that RKF can be better maintained by reducing visit-to-visit BP variability. Key words Blood pressure variability, residual kidney function From: 1 Division of Nephrology and Hypertension, Department of Internal Medicine, St. Marianna University School of Medicine, Kanagawa; 2 Division of Cardiovascular Medicine, Department of Medicine, School of Medicine, Jichi Medical University, Tochigi; and 3 JCHO Tokyo Takanawa Hospital, Tokyo, Japan. Introduction Residual kidney function (RKF) is important for better prognosis in peritoneal dialysis (PD) patients. Because a rapid decline in RKF is reported to be associated with increased long-term mortality (1), it is of paramount importance to assess the risk for decline of RKF in PD patients. Proteinuria, baseline residual glomerular filtration rate (2), and high diastolic blood pressure (BP) (3) are reported to be predictors of RKF decline. Recently, an increasing body of evidence has suggested that visit-to-visit BP variability is a major risk factor for cardiovascular events and all-cause mortality in the general population (4 6), in patients with chronic kidney disease (7), and in patients on hemodialysis (8,9). Furthermore, visit-to-visit BP variability in chronic kidney disease patients has been reported to affect RKF (10). However, little is known about the effect of visit-to-visit BP variability in PD patients. To explore such variability, we retrospectively studied the association between the slope of RKF decline and visit-to-visit BP variability. Methods Patients Between February 2006 and March 2012, 51 outpatients started PD at our hospital. The present analysis excludes 5 patients whose records lacked the data necessary to calculate RKF at the time of PD start and at 1 year after PD start; 2 patients who did not continue PD for more than 1 year (1 because of dementia, 1 because of transplantation); 1 anuric patient who was on hemodialysis at the start of PD; and 1 patient who died from a stroke 3 months after starting PD. The remaining 42 PD patients were included in this retrospective observational study, which was approved
50 Blood Pressure Variability in PD by the institutional review board of the St. Marianna University School of Medicine. At the start of PD, all patients were hospitalized for 1 3 weeks and were treated by experienced nephrologists specialized in PD. After discharge from the hospital, patients made routine clinic visits about every 4 weeks. Definition of BP variability Visit-to-visit BP variability has been defined (11) as the average real BP variability (ARV): n 1 ARV = 1 / (n 1), Σ BPk + 1 BPk k=1 where n is the number of visits. After discharge from the hospital, office BP was measured by automated sphygmomanometer at each visit. Visit-to-visit BP variability was therefore defined as the ARV of the BP measurements for the first 12 consecutive visits after the start of PD. Measurement of RKF At each monthly visit, urine chemistry, blood urea nitrogen, and serum creatinine were measured [Bio- Majesty JCA-BM6070 (after 2012) or BioMajesty JCA-BM2250 (before 2012): Jeol, Tokyo, Japan]. Estimated residual glomerular filtration rate (egfr) was calculated using the four-variable Modification of Diet in Renal Disease equation (12), with a Japanese coefficient of 0.808: egfr (ml/min/1.73 m 2 ) = 0.808 175 serum creatinine 1.154 age 0.203 ( 0.742 if female). Residual kidney function was defined as the mean of each patient s urea and creatinine clearances in accordance with the Japanese guideline (13) and was adjusted for body surface area. It was measured just after the start of PD and at 1 year after PD start. The primary outcome was the slope of RKF decline, calculated as the difference in the RKF from PD start to 1 year after PD start. Statistical analyses Unless otherwise specified, all data are expressed as means with standard deviations or as percentages. The slope of RKF decline and the BP parameters were both normally distributed (Shapiro Wilk test, p > 0.05). Univariate correlations between the BP parameters and the slope of the RKF were assessed using Pearson correlations. After adjustments for possible confounding factors [proteinuria, baseline egfr, and mean office systolic BP (sbp)], multivariate linear regression analyses of the slope of RKF decline were performed. Significance was defined as a two-tailed p value less than 0.05. All statistical analyses were performed using the IBM SPSS Statistics software application (version 19: IBM, Armonk, NY, U.S.A.). Results Patient characteristics Table I shows the characteristics of the study patients. Overall mean age was 56.3 years. At baseline, mean serum creatinine was 8.5 mg/dl, and mean egfr was 5.1 ml/min/1.73 m 2. For the first 12 visits after the start of PD, the mean office sbp was 133.0 ± 12.4 mmhg, and the mean office diastolic BP (dbp) was 77.1 ± 8.7 mmhg. The ARV of the office sbp was 13.7 ± 5.6 mmhg, and the ARV of the office dbp was 8.7 ± 3.2 mmhg. Just after the start of PD, the mean RKF was 37.3 ± 21.5 L/ week/1.73 m 2 ; 1 year after the start of PD, it was 29.9 ± 21.5 L/week/1.73 m 2. Overall, the annualized slope of RKF decline was 7.6 ± 17.4 L/week/1.73 m 2. Univariate correlations between BP parameters and the slope of RKF decline Figure 1 shows the univariate correlations between BP parameters and the slope of the RKF. The ARV of the office sbp, the mean office sbp, and the mean office dbp were significantly correlated with the slope of RKF decline. In contrast, the ARV of the office dbp was not significantly correlated with the slope of RKF decline. Multivariate regression analysis between BP parameters and the slope of RKF decline Table II shows the results of the multivariate linear regression analysis. After adjustments for proteinuria, baseline egfr, and mean office sbp, the ARV of the office sbp was independently associated with the slope of RKF decline. No multicollinearity was evident in any model; all variance inflation factors were less than
Yokota et al. 51 table i Characteristics of the study patients at the time of peritoneal dialysis start Characteristic Value Patients (n) 42 Mean age (years) 56.3±12.5 Sex (% men) 64 Mean BMI (kg/m 2 ) 23.5±4.2 Cause of ESRD (%) Diabetic nephropathy 38 Chronic glomerulonephritis 26 Nephrosclerosis 10 Polycystic kidney disease 5 Others 11 Unknown 10 Hypertension (%) 79 Diabetes mellitus (%) 55 Dyslipidemia (%) 61 Coronary artery disease (%) 12 Stroke (%) 10 Antihypertensive agents (%) ACE inhibitor 20 ARB 60 Dihydropyridine CCB 79 Non-dihydropyridine CCB 14 Diuretic 62 Beta blocker 19 Alpha blocker 12 Statin (%) 46 Serum creatinine (mg/dl) 8.5±2.3 egfr (ml/min/1.73 m 2 ) 5.1±1.5 Blood urea nitrogen (mg/dl) 78.4±21.0 Serum albumin (g/dl) 4.0±0.5 Serum uric acid (mg/dl) 8.5±2.3 Hemoglobin concentration (g/dl) 9.5±1.7 Urinary protein (g)/creatinine (g) ratio 2.6±1.7 BMI = body mass index; ESRD = end-stage renal disease; ACE = angiotensin converting enzyme; ARB = angiotensin II receptor blocker; CCB = calcium channel blocker; egfr = estimated glomerular filtration rate. 3.0. After adjustments for confounders, the correlation between the ARV of the office sbp and the slope of the RKF was significant. Discussion Hypertension is a key issue in the management of PD patients. In the present study, hypertension was seen in 79% of the PD patients, which is consistent with the previously reported prevalence of 29% 80% (14). Cardiovascular disease is the most common figure 1 Simple correlations between the slope of the residual kidney function (RKF) and the average real variability (ARV) of (A) the office systolic blood pressure (SBP), (B) the mean office SBP, and (C) the mean office diastolic blood pressure (DBP) in 42 peritoneal dialysis patients.
52 Blood Pressure Variability in PD table ii Multivariate regression analysis on the slope of residual kidney function in 42 peritoneal dialysis patients Parameter β p Value Model R 2 ARV of office sbp (mmhg) 0.37 0.024 Mean office sbp (mmhg) 0.31 0.048 Proteinuria a 0.09 0.57 egfr (ml/min/1.73 m 2 ) 0.24 0.14 0.286 a Protein (g)/creatinine (g) ratio. ARV = average real variability; sbp = systolic blood pressure; egfr = estimated glomerular filtration rate. cause of death in PD patients, and hypertension is a major risk factor for cardiovascular mortality. In the management of hypertension in PD patients, control of hypervolemia by restriction of salt intake and optimal prescription of dialysis solutions, and application of antihypertensive medications and diuretics are of paramount importance. All those measures were undertaken in the patients studied here. Even after adjustments for possible confounders, the ARV of the office sbp was significantly associated with the slope of RKF decline. To the best of our knowledge, the present study is the first to explore the relationship between RKF decline and visit-tovisit BP variability. It is noteworthy that, even with relatively well-maintained RKF, visit-to-visit BP variability in the first year after PD start was associated with RKF decline, and thus BP variability (in addition to the traditional mean BP) now has the potential to be a clinical surrogate marker and therapeutic target. Residual kidney function is compromised by dehydration in PD patients (3). Hypotension can be deleterious to the kidneys, and the effect can be larger in patients with chronic hypertension and an impaired myogenic response of the afferent arteriolar wall (15). Visit-to-visit BP variability could be a surrogate marker for the frequency of hypoperfusion in the glomeruli. Because visit-to-visit variability of BP is a known risk factor for all-cause mortality and cardiovascular events, it is reasonable to speculate that high BP variability can also damage the vascular system in the kidneys. In fact, there is some evidence that visit-to-visit BP variability is associated with the incidence and progression of diabetic nephropathy (16), the resistive index of the kidney (17), and decline in the renal function of patients with nondiabetic chronic kidney disease (18). The significant relationship between the slope of RKF decline and visit-tovisit BP variability in the present study is consistent with those earlier reports. The present study has several limitations. One is its small sample size. A further study with a larger sample size is needed. Another limitation is the retrospective nature of the study. A prospective study is required to confirm the effect of BP variability on RKF deterioration in PD patients. Conclusions Even after adjustment for possible confounders, the relationship between the slope of RKF decline and the ARV of office sbp was significant. Increased BP variability is associated with faster decline of RKF in PD patients. Disclosures The authors declare no conflicts of interest with respect to the contents of this article. References 1 van der Wal WM, Noordzij M, Dekker FW, et al. on behalf of the Netherlands Cooperative Study on the Adequacy of Dialysis Study Group. Full loss of residual renal function causes higher mortality in dialysis patients; findings from a marginal structural model. Nephrol Dial Transplant 2011;26:2978 83. 2 Szeto CC, Kwan BC, Chow KM, et al. Predictors of residual renal function decline in patients undergoing continuous ambulatory peritoneal dialysis. Perit Dial Int 2015;35:180 8. 3 Jansen MA, Hart AA, Korevaar JC, Dekker FW, Boeschoten EW, Krediet RT on behalf of the NECOSAD Study Group. Predictors of the rate of decline of residual renal function in incident dialysis patients. Kidney Int 2002;62:1046 53. 4 Hata Y, Muratani H, Kimura Y, et al. Office blood pressure variability as a predictor of acute myocardial infarction in elderly patients receiving antihypertensive therapy. J Hum Hypertens 2002;16:141 6. 5 Rothwell PM, Howard SC, Dolan E, et al. Prognostic significance of visit-to-visit variability, maximum systolic blood pressure, and episodic hypertension. Lancet 2010;375:895 905. 6 Muntner P, Shimbo D, Tonelli M, Reynolds K, Arnett DK, Oparil S. The relationship between visit-to-visit variability in systolic blood pressure and all-cause mortality in the general population: findings from NHANES III, 1988 to 1994. Hypertension 2011;57:160 6.
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