Hypophosphatemia: nutritional status, body composition, and mortality in hemodialysis patients

  • Cristina Garagarza
  • Ana Valente
  • Cristina Caetano
  • Telma Oliveira
  • Pedro Ponce
  • Ana Paula Silva
Nephrology - Original Paper

DOI: 10.1007/s11255-017-1558-2

Cite this article as:
Garagarza, C., Valente, A., Caetano, C. et al. Int Urol Nephrol (2017). doi:10.1007/s11255-017-1558-2
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Abstract

Purpose

The aim of the present study was to investigate the relationship between serum phosphate levels, clinical parameters, body composition, and mortality.

Methods

Multicenter longitudinal observational study of a cohort of 3552 patients in hemodialysis (HD) from 34 Nephrocare dialysis units in Portugal with 24 months of follow-up. Patients were divided into three groups depending on their serum phosphorus (<3.5; 3.5–5.5; >5.5 mg/dL). Statistical tests were performed with SPSS, version 20.0. A p < 0.05 was considered significant.

Results

On the one hand, hypophosphatemia was significantly associated with better dialysis adequacy, higher age and overhydration. On the other hand, it was associated with lower albumin, protein intake, creatinine, hemoglobin, calcium, potassium, magnesium, body mass index (BMI), body cell mass index, fat tissue index and lean tissue index. These patients had lower survival rates compared with those with normo- and hyperphosphatemia. Hypophosphatemia was a predictor of death when adjusted for age, diabetes, HD vintage, gender, and Kt/V. Comparing the mortality predictors in hypo- and hyperphosphatemia, we found that low albumin, BMI, and high overhydration increased the mortality risk in the hypophosphatemic group, whereas in hyperphosphatemic patients data were not statistically significant.

Conclusion

Currently, a high prevalence of hypophosphatemia exists in Portuguese HD patients. This condition is associated with worst nutritional and body composition parameters. In the context of additional indices of malnutrition (low albumin, low BMI or severe overhydration), hypophosphatemic patients presented higher mortality risk.

Keywords

Body composition Hemodialysis Hypophosphatemia Mortality Phosphorus Nutrition 

Introduction

Derangements in phosphorus levels are common among maintenance hemodialysis (HD) patients. These derangements are frequently present as hyperphosphatemia; however, hypophosphatemia is increasing and has emerged as a new challenge in the field of renal nutrition. Serum phosphorus has been reported to be an important risk factor for all-cause and cardiovascular mortality in these patients with a “U”-shaped correlation [1, 2, 3, 4, 5, 6].

There are several reasons that can lead to hypophosphatemia such as decreased phosphorus intake, decreased phosphorus intestinal absorption, increased gastrointestinal losses, use of some drugs (phosphate binders, antacids), diabetic ketoacidosis, and respiratory alkalosis [7]. The recommended phosphorus target in HD patients is 3.5–5.5 mg/dL [8].

By convention, hypophosphatemia is often graded as mild (<3.5 mg/dL), moderate (<2.5 mg/dL) and severe (<1.0 mg/dL) [7]. Although there is little evidence regarding hypophosphatemia and its significant clinical consequences in humans, severe hypophosphatemia should be treated [9].

In HD patients, the recommended intake of phosphorus is 800–1000 mg/day [8, 10]. However, this restriction should be adjusted to the protein needs of the patient in order to avoid protein energy wasting. Between 50 and 86% of dietary phosphorus is absorbed by the gastrointestinal tract, in all intestinal segments. Phosphorus presented in animal products (organic phosphate) is more readily available for intestinal absorption than inorganic phosphate of vegetal products [11]. Moreover, phosphorus used as a preservative in processed foods is completely absorbed [11]. Phosphorus absorption is dependent on both passive transport related to the concentration in the intestinal lumen (i.e., increased after a meal) and active transport stimulated by calcitriol. Medications or foods that bind phosphorus (antacids, phosphate binders, calcium) can decrease the net amount of phosphorus absorbed by decreasing the free phosphate for absorption [7]. Approximately two-thirds of the ingested phosphorus is excreted in the urine, and the remaining one-third in stool, and this phosphorus excretion is highly dependent on kidney function [7].

On the one hand, evidence has shown an association between hypophosphatemia and poor clinical outcomes suggesting that hypophosphatemia is an adverse prognostic marker [2, 5, 6]. On the other hand, serum phosphorus >6.5 md/dL has also been associated with mortality. [12, 13] Therefore, the aim of this study was to investigate the relationship between serum phosphate levels, clinical parameters, body composition, and mortality.

Methods

Study design

This was a longitudinal multicenter study with 24 months of follow-up (from November 2013 until November 2015) which included 3552 maintenance HD patients.

Data analysis

This study included patients from 34 dialysis units in Portugal.

Inclusion criteria were: age ≥18 years and three times weekly (4 h/session) in-center HD for ≥3 months (with an online hemodiafiltration technique). All patients were dialyzed with high-flux (Helixone®, Fresenius Medical Care, Deutschland GmbH, Germany®) membranes and ultrapure water in accordance with the criteria of ISO regulation 13,959:2009—water for hemodialysis and related therapies. The magnesium concentration of dialysate was 0.5 mmol/L, and calcium concentration was either 1.25 or 1.5 mmol/L, at nephrologist discretion.

Patients were divided into three groups depending on their baseline serum phosphorus (one single measurement): G1 < 3.5 mg/dL; G2 between 3.5 and 5.5 mg/dL and G3 > 5.5 mg/dL. These ranges were chosen because at the start of the study the target value in our dialysis units for normophosphatemia was between 3.5 and 5.5 mg/dL.

One single measurement was obtained at baseline regarding: dry weight (DW), presence of diabetes, albumin, creatinine, normalized protein catabolic rate (nPCR), magnesium, potassium, hemoglobin, calcium*phosphorus product (Ca/P), vitamin D [25(OH)D], parathyroid hormone (PTH), Kt/V (dialysis adequacy), body mass index (BMI), lean tissue index (LTI), fat tissue index (FTI), body cell mass index (BCMI), and relative overhydration (overhydration/extracellular water pré dialysis—OH/ECW). During the follow-up period (24 months), deaths (mortality) and the number of hospitalizations (morbidity) were registered.

In the laboratory methods, the following Roche (Roche Diagnostics®, USA) tests were used: (Cobas 701/702) complexometry (ammonium phosphomolybdate) for the determination of serum phosphorus, (Cobas 701/702) complexometry (NM-BAPTA) for calcium determination and (Cobas 401/702) colorimetry (xilidilo blue) for magnesium. Intact PTH was determined with (Elecsys 2010) ECLIA (electrochemiluminescence) and CV intra-assay 0.119% and CV inter-assay 0.169% were used.

Analysis of body composition

Body composition analysis was performed through bioimpedance spectroscopy with the Body Composition Monitor® (BCM), Fresenius Medical Care, Deutschland GmbH, Germany®.

The BCM takes measurements at 50 frequencies in a range of 5–1000 kHz. The measurement was performed approximately 30 min before the midweek HD session, with four conventional electrodes being placed on the patient, who was lying in the supine position: two in the hand and two in the foot contralateral to the vascular access. Regarding the quality of measurements, all exceeded 95%. Severe overhydration was considered if OH/ECW > 15%. For the analysis of the mortality risk predictors in hypo- and hyperphosphatemic patients, low LTI and FTI was considered if it was below the median value, to exclude possible outliers.

Statistical methods

Categorical variables were presented as frequencies. Percentages and continuous variables were presented as mean ± standard deviation (SD) or as median and interquartile ranges (IQR), as appropriate. Data distribution was tested with the Kolmogorov–Smirnov test. Comparison between variables was carried out through one-way ANOVA, and the post hoc analysis was performed by Bonferroni.

The prognostic differences of risk stratification in the study population were evaluated using Kaplan–Meier curves and log-rank test.

The Cox proportional hazard model was used to measure all potential variables and determine the significance of variables for prediction of 24-month mortality. The hazard ratio (HR) of death and 95% confidence interval (CI) were obtained by the Cox proportional hazard model. Primarily, a univariate Cox model was used to identify the association of hypo- and hyperphosphatemia with mortality; and secondly the multivariable Cox regression models were conducted using covariates that have been described as significant predictors of mortality or covariates of clinical concern including age, HD vintage, gender, diabetes, and Kt/V. Cox regression univariate and multivariate analysis were also performed by groups: hypophosphatemic versus hyperphosphatemic patients. Possible confounders were included in multivariate analysis to analyze death predictors in both groups.

All statistical tests were performed using the Statistical Package for the Social Sciences (SPSS) 20.0 software (SPSS, Inc., Chicago, IL, USA). Statistical significance was defined as p < 0.05.

Results

This study included 3552 maintenance HD patients of whom 644 (17.4%) died during the 2 years of the follow-up. The mean age and the mean HD vintage were, respectively, 70.1 ± 14.5 years and 74 ± 54.5 months; 43% were female and 31% diabetics. Hypophosphatemia (G1) presented a prevalence of 28.6% (n = 1017) (mean = 2.7 ± 0.58 mg/dL), normophosphatemia (G2) of 56% (n = 1988) (mean = 4.4 ± 0.57 mg/dL), and hyperphosphatemia (G3) of 15.4% (n = 547) (mean = 6.4 ± 0.85 mg/dL).

Hypophosphatemia was significantly associated with better dialysis adequacy (Kt/V), higher age, overhydration and lower albumin, nPCR, creatinine, hemoglobin, calcium, Ca/P, potassium, magnesium, parathyroid hormone (PTH), BMI, BCMI, FTI, and LTI. Clinical and body composition parameters of the different groups of patients are presented in Tables 1 and 2.
Table 1

Patient’s clinical parameters differences between groups

 

G1

P: <3.5 mg/dL

G2

P: 3.5–5.5 mg/dL

G3

P: >5.5 mg/dL

p

N

1017

1988

547

Age (years)b

75.3 ± 13.2

69.5 ± 13.8

62.4 ± 15.4

<0.001

HD vintage (months)a

62.0 (34–101)

58 (34–95)

59 (33–101)

0.545

nPCR (kg/g/day)b

0.99 ± 0.24

1.15 ± 0.25

1.28 ± 0.27

<0.001

Creatinine (mg/dL)a

6.6 (5.1–7.8)

7.7 (6.5–9.1)

9.0 (7.6–10.6)

<0.001

Albumin (g/dL)a

3.7 (3.4–4.0)

3.9 (3.6–4.1)

4.0 (3.7–4.2)

<0.001

CRP (mg/L)a

5.8 (2.2–18.3)

5.1 (2–12.4)

4.4 (1.7–9.8)

0.012*

Magnesium (mg/dL)a

2.0 (1.9–2.2)

2.2 (2.0–2.4)

2.4 (2.1–2.6)

<0.001

Vitamin D (ng/dL)a

9.7 (7.0–14.2)

10.0 (7.0–15.0)

9.2 (7.0–16.6)

0.750

Potassium (mEq/L)a

5.1 (4.7–5.6)

5.5 (5.0–5.9)

5.7 (5.4–6.6)

<0.001

Hemoglobin (mg/dL)a

11.4 (10.6–12.1)

11.5 (10.7–12.3)

11.7 (10.9–12.6)

<0.001

Calcium (mg/dL)a

8.7 (8.3–9.1)

8.8 (8.4–9.2)

8.9 (8.4–9.3)

<0.001

Ca*P (mg/dL)a

24.8 (20.5–28.0)

38.3 (33.9–43.2)

54.9 (50.7–61.4)

<0.001

PTH (ng/L)a

195 (102–323)

304 (178–497)

402 (201–684)

<0.001

Kt/Va

1.7 (1.5–1.9)

1.6 (1.4–1.8)

1.5 (1.4–1.8)

<0.001

Dry weight (kg)a

62.6 (54.0–71.0)

67.5 (59.0–76.0)

69.5 (59.5–79.3)

<0.001

Hospitalizations (n)b

0.54 ± 0.45

0.49 ± 0.92

0.45 ± 0.94

0.116

P phosphorus, HD hemodialysis, nPCR normalized protein catabolic rate, CRP C-reactive protein, Ca*P product phosphorus-calcium, Kt/V dialysis adequacy

p = 0.013 between G1 and G3 by one-way ANOVA with post hoc Bonferroni correction for multiple comparisons

aResults are expressed as median (interquartile range)

bResults are expressed as mean ± SD

Table 2

Patient’s body composition differences between groups

 

G1

P: <3.5 mg/dL

G2

P: 3.5–5.5 mg/dL

G3

P: >5.5 mg/dL

p

N

1017

1988

547

BMI (kg/m2)

25.22 ± 4.82

26.70 ± 5.00

27.0 ± 5.27

<0.001

LTI (kg/m2)

11.2 ± 2.78

12.18 ± 2.89

13.13 ± 3.4

<0.001

FTI (kg/m2)

13.14 ± 5.63

13.79 ± 5.72

13.34 ± 6.36

0.042*

BCMI (kg/m2)

5.82 ± 1.99

6.52 ± 2.06

7.21 ± 2.41

<0.001

OH/ECW pre (%)

8.74 ± 8.80

7.24 ± 8.38

6.43 ± 8.78

<0.001

P phosphorus, BMI body mass index LTI lean tissue index, FTI fat tissue index, BCMI body cell mass index, OH/ECW pre overhydration/extracellular water

p = 0.047 between G1 and G2 by one-way ANOVA with post hoc Bonferroni correction for multiple comparisons

In our sample, we had 181 patients with data regarding serum vitamin D (mean = 11.75 ± 6.29) of which, only three patients presented vitamin D ≥30 ng/dL. Patients were separated into tertiles of serum vitamin D, but the differences between these three groups and serum phosphorus status (hypophosphatemia, normophosphatemia and hyperphosphatemia) were not statistically significant (40.0; 30.5 and 34.6%, respectively; p = 0.805). Regarding vitamin D therapy in each group, we observed the following prevalence: normophosphatemia = 57.6% (n = 1279), hypophosphatemia = 27.1% (n = 602) and hyperphosphatemia = 15.2% (n = 338); (p = 0.02). Native and active vitamin D therapy included: alfacalcidol (29.8%), calcitriol (14%), cholecalciferol (17.4%), or paricalcitol (10.7%).

From the patients taking calcimimetics 17.1% had calcium <8.4 mg/dL and in 9.4% had hypophosphatemia.

Within hypophosphatemic patients, 26.5% (n = 269) had phosphate binders prescribed, whereas in the normophosphatemic group, this value was 51.5% (n = 1023) and 79.2% (n = 433) in the group of patients with phosphorus >5.5 mg/dL (p < 0.001).

Regarding hypophosphatemic patients with and without phosphate binders prescription, no statistically significance difference was observed in survival (p = 0.138).

During the 24 months of the follow-up period, the overall mortality was 17.2% (612 deaths occurred). 15.5% of the normophophatemic patients died whereas in the hyperphosphatemic group this percentage was lower (12.2%). Among hypophosphatemic patients, 23.3% of deaths were registered.

Patients with phosphorus <3.5 mg/dL had lower survival rates compared with those with normo- and hyperphosphatemia (p < 0.001) (Fig. 1). At 24 months, the survival rate was 77% for hypophosphatemic patients, 84% for normophosphatemic, and 88% for hyperphosphatemic.
Fig. 1

Survival curve for the three groups of patients (n = 3552; Log-rank χ2 = 41.84; p < 0.001)

In the Cox regression analysis, hypophosphatemia was a mortality risk factor independent of age, HD vintage, gender, diabetes, and Kt/V (HR: 1.29; 95% CI 1.07–1.55; p = 0.007) (Table 3). However, the statistical significance was lost when the model was adjusted for albumin. Data regarding mortality risk predictors in hypo- and hyperphosphatemic patients separately are presented in the Fig. 2. In this analysis, “Low LTI” refers to LTI < 11.7 kg/m2 and “Low FTI” refers to FTI < 12.9 kg/m2 (both median values). On the one hand, through the univariate model, we found several mortality predictors for the hypophosphatemic group including low protein intake, low albumin, severe overhydration and low LTI. On the other hand, in hyperphosphatemic patients, only severe overhydration and low LTI appear to be significant regarding mortality risk. However, in the models adjusted for age, gender, DM, HD vintage and dialysis adequacy, the mortality risk predictors which showed statistical significance were hypoalbuminemia, low BMI and severe overhydration but only for the hypophosphatemic patients.
Table 3

Cox proportional hazard univariate and multivariate model for all-cause mortality

 

Univariate analysis

Multivariate analysisa

HR (95% CI)

p

HR (95% CI)

p

Hypophosphatemiab

1.59 (1.34–1.88)

<0.001

1.29 (1.07–1.55)

0.007

Hyperphosphatemiab

0.78 (0.60–1.00)

0.059

1.00 (0.74–1.35)

0.147

aMultivariate analysis: adjusted for age, HD vintage, gender, diabetes, Kt/V (dialysis adequacy)

bReference: normophosphatemia

Fig. 2

“Forest Plot” with hazard ratios for mortality risk predictors in hypo- and hyperphosphatemic patients. Protein intake (g/kg/day); OH/ECW pre (%): severe overhydration; LTI (kg/m2): lean tissue index; FTI (kg/m2): fat tissue index; BMI (kg/m2): body mass index; albumin (g/dL). Model adjusted for gender, DM, HD vintage, age and dialysis adequacy. *p < 0.05

Discussion

Regarding our data, a higher prevalence of hypophosphatemia exists in this sample when compared to hyperphosphatemia. This condition was associated with higher mortality when compared to hyperphosphatemia (Fig. 1). To our knowledge, this is the first study which includes a comparison between phosphorus levels and body composition parameters. According to our results, patients with hypophosphatemia presented worst nutritional status markers, protein intake and higher levels of overhydration.

The association between hypophosphatemia, low protein intake and malnutrition in HD patients, which are important predictors of mortality, has already been described [14]. Phosphorus decreasing occurs approximately 3–4 days after an inadequate nutrient intake of foods which are rich in phosphorus and a continuous inadequate intake of phosphorus results in an extracellular fluid shift to the cells in order to replace the phosphorus loss [15]. Furthermore, in HD patients, low protein energy intake is commonly observed, mainly in elderly patients [16, 17]. Our findings showed that hypophosphatemic patients had a significantly higher mean age (Table 1). An association between the restriction of dietary phosphorus with reductions in serum albumin, caloric intake and replacement of lean mass with fat, when compared with a more permissive diet regarding phosphorus has been described [18]. Our results are in line with these findings as we found an association between hypophosphatemia and lower protein intake, albumin and creatinine. Regarding body composition, lower levels of LTI, FTI, BCMI, and BMI were also observed in patients with hypophosphatemia indicating a worst nutritional status. However, a significant negative correlation between serum phosphorus and BMI has been described by other authors [19].

In our sample, patients with hyperphosphatemia were younger, had higher albumin levels and also higher protein intake, as well as, better body composition parameters (higher LTI, BMI, and lower overhydration).

Kakiya et al. [20] described that lean mass, serum albumin, and serum creatinine configure a group of markers for protein wasting, whereas fat mass is in a group of indicators for energy wasting. In this study, protein and energy-wasting markers were lower in the hypophosphatemic patients. Rosenberger et al. [21] observed a decline in serum albumin, along with the decline of the phosphorus level which might be a marker of malnutrition inflammation syndrome. Hypophosphatemic patients (G1) presented higher CRP levels which can affect serum creatinine concentrations [22].

It is known that the metabolism of calcium, magnesium, and PTH influences phosphorus levels in these patients. In our study, PTH, magnesium, calcium, and Ca*P product were lower in the hypophosphatemic group (G1). In the study conducted by Lorenzo et al. [14], serum phosphorus and PTH decreased with the advanced age of the patients. Patients in the G1 were those who presented higher age. PTH deficiency or inactivity can lead to hypocalcemia and magnesium secretion can decrease [7, 23]. Kim et al. [24] showed that patients with PTH < 150 pg/mL had significantly lower phosphorus, calcium, and Ca*P product values. It has been suggested that hypoparathyroidism can inhibit intestinal phosphorus absorption [25].

The HD treatment itself can affect serum phosphorus levels. In our study, patients with hypophosphatemia, who also presented lower BMI, had higher Kt/V. On the one hand, dialysis adequacy is inversely proportional to the urea distribution volume, therefore it is expected that patients with lower body surface will present higher Kt/V [26]. On the other hand, it has been described that Kt/V targets are more difficult to reach in patients with higher weight and larger body surface [27]. Higher serum phosphorus levels in HD patients are mostly affected by increased food intake (protein intake) and decreased dialysis adequacy [28].

Tentori et al. [5] found that phosphorus levels ≤2.0 mg/dL were associated with higher all-cause mortality risk in both baseline and time-dependent models. The post hoc analysis of the HEMO study showed that prescribed dietary phosphorus restriction was not associated with greater survival. Moreover, it can have harmful effects [18]. Our results also showed higher mortality rates in patients with hypophosphatemia (Fig. 1). The fact that hyperphosphatemia has shown a protective effect regarding mortality can be related with the fact that those patients have a better nutritional status and an increased protein intake (nPCR), as observed.

In the Cox regression analysis, hypophosphatemia was a significant predictor of death, comparing to phosphorus levels between 3.5 and 5.5 mg/dL, even after adjustment for confounding factors such as age, HD vintage, gender, diabetes, and Kt/V (Table 3). Therefore, our data suggest that the hypophosphatemia mortality risk observed in these patients is independent of some predictors of mortality or covariates of clinical concern, such as age, gender, HD vintage, diabetes, and Kt/V. However, with the inclusion of albumin in the model the mortality prediction was lost. This indicates that hypophosphatemia per se was not an independent predictor of death but associated malnutrition, if present, is the real problem. Some other studies have also presented data showing significant results after including phosphorus in adjusted models [4, 29, 30].

As mentioned in the results, no differences between vitamin D levels among the three groups were observed. This reinforces the fact that our findings are associated with hypophosphatemia but not with vitamin D deficiency.

When mortality predictors were analyzed separately for hypophosphatemic and hyperphosphatemic patients, we observed that low albumin (<3.8 g/dL), BMI < 23 kg/m2 and severe overhydration (>15%) were independent mortality predictors only in the hypophosphatemic group (Fig. 2). Therefore, the approach for these patients may also need to be focused on these parameters.

Despite the lack of statistical significance, there was a tendency to an increased mortality risk of the parameters studied also in hyperphosphatemic patients and, with the exception of low LTI, the hazard ratio for all the other parameters was lower in these patients. However, we believe that there might be other mechanisms that attenuate the potential risk when phosphorus levels are above 5.5 mg/dL. As mentioned, the overall nutritional status and body composition parameters are improved in patients with phosphorus levels >5.5 mg/dL, and therefore, this can have benefits that place these patients in an advantage position comparing to hypophosphatemic patients.

As it has been already documented [31, 32], we believe that the majority of hypophosphatemia cases can improve through a nutritional counseling focused on recommending foods high in protein and dairy products as they contain high amounts of phosphorus.

It is worthy of consideration that apart from an insufficient protein energy intake, there are other mechanisms that can contribute to the development of hypophosphatemia such as hypoparathyroidism, paratiroidectomy, phosphate binders, or persistent diarrhea. Therefore, various parameters should be monitored in order to detect the cause and correct it when possible.

One of the limitations of this study is the fact that only a single measurement of serum phosphorus was registered at baseline and sometimes it can show an isolated situation and not the usual patient’s profile. Other limitation is the fact that residual renal function (a well-known predictor of survival and phosphorus levels) was not included in the analysis. Apart from that, our conclusions are based on an observational cohort in spite of a randomized controlled study. However, the total number of patients studied and the large follow-up period are considered strengths of this study. We studied a proportional sample of patients of different dialysis units located in different geographical areas of the country. Moreover, all patients were on online HDF, a fact that we consider important in the context of this study.

Currently, a higher prevalence of hypophosphatemia exists in Portuguese HD patients. This condition is associated with worse nutritional and body composition parameters such as lean and fat tissue index. In the context of additional indices of malnutrition (low albumin, low BMI, or severe overhydration), hypophosphatemic patients presented higher mortality risk. On the contrary, regarding our data, phosphorus level above 5.5 mg/dL is not an independent mortality predictor.

Practical application

We consider that more attention should be given to low phosphorus levels in order to early detect situations of low protein intake or poor nutritional status and prevent or delay unfavorable outcomes. Therefore, in case of phosphorus levels below 3.5 mg/dL, we consider important to check for additional parameters of malnutrition as hypophosphatemia can be an indicator of other altered nutritional parameters.

Compliance with ethical standards

Conflict of interest

There is no conflict of interest or financial interest to be reported by any of the authors.

Informed consent

This study was approved by the local responsible of the ethical board and an informed written consent was previously signed by the patients.

Transparency declarations

All the authors work at Nephrocare dialysis units in Portugal. We certify that the results presented in this paper have not been published previously in whole or part, except in abstract form.

Copyright information

© Springer Science+Business Media Dordrecht 2017

Authors and Affiliations

  • Cristina Garagarza
    • 1
  • Ana Valente
    • 1
  • Cristina Caetano
    • 1
  • Telma Oliveira
    • 1
  • Pedro Ponce
    • 1
  • Ana Paula Silva
    • 2
  1. 1.NephrocareLisbonPortugal
  2. 2.NephrocareFaroPortugal

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