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Clinical and Translational Research

Hypervolemia and Blood Pressure in Prevalent Kidney Transplant Recipients

Chan, Winnie1,2,3; Bosch, Jos A.2; Jones, David4; McTernan, Philip G.5; Inston, Nicholas1; Moore, Sue1; Kaur, Okdeep1; Phillips, Anna C.2; Borrows, Richard1,6,7

Author Information
doi: 10.1097/TP.0000000000000066

Abstract

Hypervolemia (or volume expansion) represents isotonic expansion of the extracellular fluid compartment caused by abnormal retention of water and sodium, manifesting as fluid accumulation and swelling in the extremities or lung tissues. It is common among patients with end-stage renal disease requiring maintenance dialysis (1–4), and is associated with increased morbidity and mortality (1–3, 5). For many of these patients, kidney transplantation is a preferred option of renal replacement therapy to correct metabolic abnormalities. It is assumed that hypervolemia no longer represents a major problem after transplantation, but no study to date confirms or refutes this.

In addition, hypervolemia is associated with hypertension in patients on hemodialysis (2) and peritoneal dialysis (3), but this relationship has not been studied in kidney transplant recipients (KTRs) despite this complication arising in 75% to 90% of these patients (6).

B-Type natriuretic peptide (BNP) is a cardiac hormone that is synthesized as an amino acid precursor protein and undergoes intracellular modification to a prohormone BNP (pro-BNP) (7). It is secreted predominately from the ventricles in response to increased stretch of the ventricular wall (7). Upon release into the circulation, pro-BNP is cleaved into the biologically active 32-amino-acid C-terminal fragment BNP and the biologically inactive 76-amino-acid N-terminal fragment (NT-proBNP) (7). NT-proBNP possesses a longer half-life time than the biologically active counterpart, hence delivering a superior reflection of pathophysiological situation leading to raised BNP levels (8). Because of renal metabolism of NT-proBNP, concentrations also rise with the progression of chronic kidney disease (CKD) (9). Recent studies have confirmed that it is a marker of extracellular volume overload rather than cardiac dysfunction per se in maintenance dialysis patients (10–13). However, little research has examined this relationship after transplantation, with the two studies conducted to date highlighting the inverse relationship between NT-proBNP and allograft function (14, 15).

The primary objectives of this study were to determine the prevalence and predictors for hypervolemia in a stable kidney transplant cohort, and to assess its association with posttransplant hypertension. Secondly, we sought to explore the utility of serum NT-proBNP as a correlate of hypervolemia and renal dysfunction in this cohort.

RESULTS

Population Characteristics

The characteristics of the studied population are shown in Table 1. The mean percentage volume expansion (%VE)±standard deviation (SD) for the cohort was 2.6±7.7%, ranging from −17.0% to +25.0%. Based on denoted criteria (described in Materials and Methods), the prevalence of hypovolemia in KTRs was 11% (13 patients), normovolemia was 59% (73 patients), mild hypervolemia was 25% (31 patients displaying %VE between 7.1% and 15.0%), and 5% suffered from severe hypervolemia (6 patients displaying %VE >15.0%).

T1-16
TABLE 1:
Population characteristics

Factors Predicting Extracellular Volume Status

On univariate analysis, increasing values for %VE were associated with the following: higher sodium intake (relationship is shown in Fig. 1), higher fluid intake, older age, pre-existing diabetes, male gender, the use of an angiotensin-converting-enzyme inhibitor (ACEI) or angiotensin receptor blocker (ARB) (grouped as a single category), and the number of antihypertensive medications. The effect sizes for the univariate analyses are shown in SDC, Table 1,https://links.lww.com/TP/A952. In the multivariate analysis, only increased sodium intake (beta coefficient, β=1.7; 95% confidence interval, CI=1.2, 2.4; P<0.001) and advancing age (β=1.8; 95% CI=1.0, 2.6; P<0.001) retained statistical significance. In addition, an association emerged in the multivariate analysis between increased %VE and reduced fat tissue index (FTI) (β=−1.4; 95% CI=−2.2, −0.5; P=0.002). A 51% of the variation in extracellular volume status (%VE) was explained by these variables (R2: 51%; Table S1, SDC,https://links.lww.com/TP/A952).

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FIGURE 1:
Association between sodium intake and extracellular volume status (percentage volume expansion, %VE).

Extracellular Volume Status and Blood Pressure

Increasing volume status (higher %VE) was associated with progressive increases in all measures of blood pressure (BP) (systolic blood pressure, SBP, r=0.83, P<0.001; diastolic blood pressure, DBP, r=0.60, P<0.001; mean arterial pressure, MAP, r=0.78, P<0.001; Fig. 2A). A significant difference across categories of volume status (“hypovolemia”; “normovolemia”; “mild hypervolemia”; “severe hypervolemia”) was seen, with increased BP at higher degrees of extracellular volume status (Fig. 2B).

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FIGURE 2:
A, relationship between extracellular volume status (percentage volume expansion, %VE) and blood pressure. B, comparisons of blood pressure among kidney transplant recipients with different extracellular volume status.

The univariate and adjusted analyses describing the predictors of MAP, SBP, and DBP are shown in Tables S2–S4, SDC,https://links.lww.com/TP/A952. The following predictor variables displayed univariate, unadjusted associations with higher values for all measures of BP (MAP, SBP, and DBP): increasing %VE, increased sodium intake (associations shown in Fig. 3), older age, diabetes (pre-existing diabetes, pre-DM; or new onset diabetes after transplantation, NODAT), the use of an ACEI or ARB, hypoalbuminemia, male gender, and number of antihypertensive medications. In addition, higher fluid intake was associated with higher MAP and SBP readings, but not DBP. However, in the adjusted model, the only independent predictor of BP was a higher %VE, with this effect seen for MAP (β=6.6; 95% CI=5.6, 7.6; P<0.001), SBP (β=9.8; 95% CI=8.5, 11.0; P<0.001), and DBP (β=4.9; 95% CI=3.7, 6.2; P<0.001). Of note, a substantial proportion of BP variation could be explained by this single predictor variable (62%, 69%, and 35% for MAP, SBP, and DBP as shown in Tables S2–S4, SDC,https://links.lww.com/TP/A952).

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FIGURE 3:
Association between sodium intake and blood pressure.

NT-proBNP as a Marker of Volume Status and Allograft Function

Median serum NT-proBNP level in this cohort of KTRs was 291.0 (interquartile range, IQR: 65.0–700.4) pmol/L. NT-proBNP levels demonstrated a positively skewed distribution and underwent logarithmic transformation before parametric analysis. On univariate analysis, higher %VE, lower estimated glomerular filtration rate (eGFR), and reduced hemoglobin (Hb) level were associated with higher values for NT-proBNP (Table S5, SDC,https://links.lww.com/TP/A952). In the multivariate analysis, increasing %VE (ratio, R=1.16; 95% CI=1.03, 1.29; P=0.01), decreasing eGFR (R=0.95; 95% CI=0.90, 0.99; P=0.03), and lower Hb level (R=0.74; 95% CI=0.58, 0.96; P=0.02) retained significant associations with NT-proBNP. In addition, the absence of a dihydropyridine calcium channel blocker (CCB) prescription (R=0.63; 95% CI=0.45, 0.89; P<0.01) and current or previous smoking history (R=1.46; 95% CI=1.04, 2.05; P=0.03) were significant predictors of raised NT-proBNP levels in the multivariate model. The relationships of NT-proBNP with %VE and renal allograft function are demonstrated in Figure 4(A) and (B), respectively. A 21% of the variation in NT-proBNP was explained by the variables in the final multivariate model.

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FIGURE 4:
A, association between extracellular volume status (percentage volume expansion, %VE) and level of NT-proBNP. B, association between renal function and level of NT-proBNP.

DISCUSSION

This is the first study to address in detail the prevalence, predictors, and consequences of hypervolemia in KTRs. Based on the previously established definition of hypervolemia, 30% of KTRs were hypervolemic, of whom 5% suffered from severe hypervolemia. Despite a lower incidence when compared to continuous ambulatory peritoneal dialysis (3) or hemodialysis (16) populations, this degree of hypervolemia was unexpected, and is noteworthy in light of the specific selection of a clinically and biochemically stable kidney transplant cohort for this study. Hypervolemia was associated with increasing sodium intake, highlighting an important target for intervention. Dietary sodium restriction has not been formally examined in KTRs, but has gained attention in other contexts (17). The daily sodium intake in the current cohort of KTRs was 2,725 mg (118 mmol), lower than previously reported (3,588 mg/156 mmol per day) (18) but well above the recommendation of Dietary Approach to Stop Hypertension (DASH) guideline (1,500–2,300 mg/65–100 mmol per day) (19). Collectively, these findings suggest that reducing sodium intake in line with the DASH diet should be recommended for KTRs presented with hypervolemia.

A recent study demonstrated a relationship between increased sodium intake and higher BP, although the contribution of extracellular volume status was not evaluated therein (18). Although the results of the current study confirmed a univariate association between sodium intake and BP, this relationship did not hold when the effect of extra cellular volume status was taken into account. Indeed, hypervolemia was identified as the only independent risk factor for elevated BP, which has a recognized impact upon long-term patient and graft outcomes (20–22). Although this relationship between hypervolemia and elevated BP resonates with findings in dialysis patients (2, 3, 23), this has not been previously demonstrated in KTRs.

Pertinently, the American Society of Hypertension (24) acknowledges the possible role of volume expansion and potential therapeutic role of diuretics in posttransplant hypertension. Other expert review articles also recognize volume expansion as a potential risk factor, although remain guarded over the use of diuretic therapies (25, 26). In the current study, the prevalence of diuretic usage was only 15%, with furosemide being the only diuretic prescription. No association between furosemide usage and volume status was observed, but this may be a reflection of “confounding by indication”. Furthermore, the median dosage of furosemide in this study cohort was 40 mg, a dosage which may be insufficient to target hypervolemia in KTRs with a mean eGFR of 44 mL/min (27). Such confounding may also be responsible for the association between renin-angiotensin system blockers (ACEI and ARB), and volume overload, MAP, SBP, and DBP, although these associations did not persist in the adjusted analysis.

In regard to other determinants of extracellular volume status, an inverse association between fat mass and volume status was observed in the current study. This phenomenon has been demonstrated in a non-transplanted population (28), which now extends to the kidney transplant population. Interestingly, renal dysfunction was not identified as one of the predictors of volume status and blood pressure in this study. However, based on the statistical point estimates, eGFR displayed inverse associations with volume overload, MAP, SBP, and DBP, and the absence of statistical significance may reflect the study size and the range of renal function encountered in this study, and certainly the current results do not exclude the importance of renal function in this setting.

Based on the findings from this study, a multimodality approach involving the DASH diet and increased diuretic usage may be beneficial in the treatment of volume overload and hypertension in KTRs. Previous studies have shown that synergistic hypotensive effects were achieved when sodium restriction and diuretics were used in combination (29, 30). In particular, the DASH diet, comprising high fruits, vegetables, whole grains, and low-fat dairy products; and low fat, refined carbohydrates, and sodium, has been shown to substantially lower blood pressure in large, randomized controlled trials (19, 31, 32). It has also been proven to potentiate the benefits of antihypertensive medication treatment (31). Diuretic therapy should be titrated in accordance with volume status and blood pressure. Crucially, meticulous monitoring of both volume status and blood pressure should be in place to ensure optimal management of hypertension in KTRs. In particular, increasing fluid intake is often promoted particularly in the early period posttransplantation, yet also displayed univariate association with volume overload, MAP, and SBP, thereby highlighting the importance of judicious assessment of extracellular volume in these patients. Indeed, the findings from this study suggest that more widespread and accurate evaluation of extracellular volume status may facilitate the clinical management of KTRs, and sets the scene for interventional measures which have shown benefit in a recent hemodialysis-based trial (33). It is hoped that the findings of this study will highlight the importance of extracellular volume status assessment in the management of hypertension, a tool yet to be incorporated into international guidelines from Kidney Disease: Improving Global Outcomes (34), European Renal Best Practice Work Group (35), and United Kingdom Renal Association (36).

The independent association between an objective measure of hypervolemia and raised NT-proBNP level is a novel and noteworthy finding of this study, confirming and extending findings from the non-transplanted populations, predominantly patients undergoing dialysis (10–13). Additionally, reduced allograft function was independently associated with raised NT-proBNP levels, in keeping with findings from previous studies among KTRs (14, 15), because of a reduced renal clearance of NT-proBNP. Although previous studies have suggested NT-proBNP as a marker of cardiac dysfunction in dialysis patients (37, 38), interpretation of these studies is limited by a lack of concomitant and objective measurement of volume status, and by the variation in NT-proBNP levels depending on the timing of blood sampling relative to dialysis treatment. In fact, the most detailed study in dialysis, which employed standardized sampling times, simultaneous echocardiography, and bioimpedance-based extracellular fluid volume measurements, showed that NT-proBNP was dependent on volume overload per se, rather than the echocardiographic parameters of cardiac dysfunction (10, 11). The single study in KTRs addressing the relationship between echocardiography and NT-proBNP level likewise found no relationship between the two parameters (14). Although cardiac function was not assessed in the current study, the findings from this study certainly support the concept that NT-proBNP levels reflect volume status. However, an important caveat is the high variability in the relationship between NT-proBNP levels and both %VE and eGFR. This suggests that although NT-proBNP may be a marker of volume expansion and renal dysfunction, it cannot yet be considered as an accurate surrogate for either. The utility of serial NT-proBNP measurements cannot be discerned by the current study.

Other factors independently associated with elevated NT-proBNP levels included smoking (current or ex-smoker, or both), reduced level of Hb, and the absence of CCB prescription as an antihypertensive agent. Although the mechanisms behind these findings are not fully understood and were not the focus of the present study, these results are in keeping with previous observations in non-transplant cohorts (39–45), and reflects the “face validity” of the current findings.

This study has limitations that should be acknowledged. It represents a single-center experience, and validations of the findings are needed in other cohorts. Also, transplant renal artery stenosis is a potential cause for posttransplant hypertension and volume expansion. However, it was not systematically sought in this study because of an estimated prevalence of only 5% to 10% (46), and the lack of detection is unlikely to have confounded the results. The cross-sectional nature of this study is unable to establish the causal relationship between predictor and outcome variables. Long-term longitudinal follow-up and experimental interventions are now required to robustly evaluate the impact of extracellular volume status on relevant end points in kidney transplantation.

In summary, this is the first study to investigate the prevalence, predictors, consequences, and biochemical markers of hypervolemia in KTRs. It points at potential targets for intervention, thereby expanding future avenues for basic and clinical research.

MATERIALS AND METHODS

Participants and Study Design

KTRs beyond 1 year posttransplantation, with stable graft function (<10% increase in serum creatinine over preceding 6 months), were recruited to this cross-sectional study between April 2010 and April 2013. Exclusion criteria included episodes of acute rejection within the last 6 months, evidence of sepsis in the last 6 weeks, known active malignancy or chronic infection, history of thyroid disease or adrenal insufficiency, and contraindications for use of bioimpedance-based body composition assessment (implanted or external electronic devices, metallic implants, amputations, pregnancy, and lactation). Of 133 patients approached, 10 did not participate (mainly because of work commitment). The study was approved by the local research ethics committee and was conducted in accordance with the principles of the Declaration of Helsinki.

Data Collection

Demographics and Clinical Parameters

Age, gender, ethnicity, and time posttransplantation were collected from patients’ medical records. Smoking status (never smoked, current and ex-smoker) was collected by questionnaire. The following clinical parameters were retrieved from patients’ medical records: (1) presence of diabetes, pretransplantation (pre-DM), or NODAT; (2) previous acute rejection episodes; (3) immunosuppressive medication usage, either prednisolone, calcineurin inhibitor, or adjunctive antiproliferative agent; (4) use of antihypertensive medications, either ACEI, ARB, beta-adrenergic blocker (BAB), dihydropyridine CCB, or alpha-adrenergic blocker (AAB); and (5) use of diuretic.

SBP and DBP were measured semi-recumbent with a fully automatic upper-arm digital blood-pressure monitor (Spot Vital Signs LXi; Welch Allyn). Six readings over an 8- to 10-min period were taken, with the first reading ignored, and the mean of the remaining five used for analysis. This protocol for BP monitoring has been shown to produce measurements comparable to that derived from the 24-hr ambulatory blood pressure monitor, the “gold standard” for the diagnosis of hypertension (47). MAP was subsequently calculated using the formula (2DBP+SBP)/3 (18).

Laboratory Parameters

Blood samples were collected for measurement of high-sensitivity C-reactive protein (hsCRP), albumin (Alb), Hb, and eGFR derived using the four-variable modification of diet in renal disease equation (48). Morning urine was collected for assessment of albumin-to-creatinine ratio (ACR). Analyses were undertaken in accredited hospital hematology and biochemistry laboratories.

Serum NT-proBNP was measured using a noncompetitive immunoluminometric assay as described by Khan and colleagues (49). This highly specific assay shows no cross-activity with atrial natriuretic peptide, BNP, or C-type natriuretic peptide (49). The inter- and intra-assay coefficients of variation were 2.3% and 4.8%, respectively (49).

Sodium and Fluid Intakes

Sodium and fluid intakes were estimated by a 3-day food diary. A multiple-day food diary provides a good estimate of individual’s sodium intake (50), comparable to that derived from the mean 24-hr urinary sodium excretion (50, 51), and produces a reliable and valid record of fluid intake in free-living humans (52). Participants were given detailed written instructions on completing an accurate dietary record for a 3-day period, which included one weekend day, within 1 week before attending the research visit. These instructions were accompanied by verbal explanation from the researcher, which included training in portion size estimation and documentation for both dining in and eating out. The dietary records were reviewed by the researcher for accuracy and completeness at the research visit. Data was entered into Dietplan6 P3 (Forestfield Software Ltd) nutrition analysis program by the same researcher, avoiding inter-observer variation. Total daily intakes of fluid, energy, and all macro- and micronutrients were calculated by this program. No patients were prescribed sodium-containing oral medication at the time of the study.

Measurement of Body composition and Volume Status; Definition of Volume Status

Body composition and extracellular volume status were assessed by whole-body bioimpedance spectroscopy (“body composition monitor” [BCM]; Fresenius Medical Care, Germany). This device has been used in dialysis patients extensively (5), and has been validated against reference methods for volume status and body composition (53). The BCM utilizes an algorithm based on a three-compartment body model to evaluate extracellular and intracellular fluid volumes (28). Absolute extracellular volume expansion was determined by calculating the difference between the actual amount of extracellular fluid in the body detected by the BCM and the expected amount of extracellular fluid (ECF) predicted by the BCM under normal physiological (i.e., normovolemia) conditions (5, 54). Percentage volume expansion (%VE) is therefore defined as [(absolute extracellular volume expansion×100)/expected ECF volume]. In a normal reference population, the 90th and the 10th percentiles of %VE is ±7% (5, 55). Increased mortality in hemodialysis patients is observed when %VE is greater than 15% (56, 57). Hence, established definitions (and those used in the current study) are based on %VE, less than −7.0% representing “hypovolemia”, within ±7.0% indicating “normovolemia”, between 7.1% and 15.0% denoting “mild hypervolemia”, and greater than 15.0% demonstrating “severe hypervolemia”.

Measurements were carried out in a standard manner while the patient was lying supine in a flat and nonconductive bed. The inbuilt physiological body composition model measures whole-body bioimpedance spectroscopy at 50 frequencies (5–1,000 kHz) through electrodes placed on the wrist (proximal to the transverse) and the ankle (arch on the superior side of the foot) on the same side of the body. Results for %VE, together with lean tissue index (LTI [kg/m2]) and fat tissue index (FTI [kg/m2]), were displayed after each measurement.

Statistical Analysis

Statistical analyses were performed using STATA. Results were presented as mean±standard deviation (SD) for normally distributed data or median (interquartile range, IQR) for non-normally distributed data. Unadjusted univariate relationships were evaluated with Pearson correlation coefficients, and one-way analysis of variance followed by Tukey post hoc test for multiple-group comparisons.

Linear regression analysis was used to determine the associations between predictor variables and the continuously distributed outcome variables, with logarithmic transformation of non-normally distributed data before analysis. The analyses were performed in two stages. Initially, the effect of each variable was examined in a series of univariate regression analyses. Subsequently, the joint effect of variables demonstrating some evidence of association on univariate analysis (P<0.20) was examined in a multivariable regression analysis, using a backwards selection procedure to derive the final model. A type 1 error rate less than or equal to 5% (P≤0.05) was considered significant in the final model.

ACKNOWLEDGMENTS

The research was carried out at the National Institute of Health Research (NIHR)/Wellcome Trust Clinical Research Facility Birmingham. The views expressed are those of the authors and not necessarily those of the NHS, and the NIHR of the Department of Health. The authors would like to acknowledge the staff in the Renal Outpatients Department and the Wellcome Trust Clinical Research Facility who has been involved in facilitating this study. Also, special thanks to Golaleh McGinnell, Theresa Brady, and Helen Houston for leading the nursing support of this research.

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Keywords:

Hypervolemia; Sodium; Blood pressure; NT-proBNP; Kidney transplantation

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