Predictors of serum creatinine in haemodialysis patients: a cross-sectional analysis

Luigi Vernaglione1, Anna Lisa Marangi, Claudio Cristofano1, Rosa Giordano, Stefano Chimienti1 and Carlo Basile

Divisions of Nephrology, Hospitals of Martina Franca and 1 Manduria, Italy

Abstract

Background. C-reactive protein (CRP) levels, an acute phase response index, predict cardiovascular outcome and are inversely related to visceral proteins, including albuminaemia in haemodialysis patients. Less definite is the relationship between inflammation and markers of somatic proteins such as serum creatinine in such patients. To explore these questions, a cross-sectional analysis of potential predictors of serum creatinine was performed.

Methods. One hundred and seventy-nine prevalent haemodialysis patients as of June 2001 were included in the cohort. Midweek pre-dialysis blood samples were collected during the months of June, September through to December 2001 inclusive, and determinations of serum urea (urease method), creatinine (alkaline picrate method) and CRP levels by means of a high sensitivity immunonephelometric method were performed. Furthermore, pre- and post-dialysis body weights were recorded and 2 min post-dialysis serum urea levels were determined three times. They were utilized for the calculation of single pool Kt/V and of normalized protein catabolic rate (nPCR). Each of the data represents the mean of three determinations made every 3 months in the study period.

Results. The analysis of multivariate linear regression was able to validate our model characterized by a dependent variable, serum creatinine and four independent variables (age, CRP, Kt/V and nPCR) (R2=0.60; F=24.10; P<0.00001; SE=1.94). Age (-0.08 mg/dl decrease in serum creatinine per 1-year increase in age), Kt/V (-0.25 mg/dl decrease in serum creatinine per 0.1 increase in Kt/V) and nPCR (0.10 mg/dl increase in serum creatinine per 0.1 g protein/kg/day increase in nPCR) were independently predictive of serum creatinine (P<0.00001). CRP and dialysis vintage did not predict serum creatinine. Stratifying the patients for the effects of CRP, only CRP values <=4 mg/l were directly predictive of serum creatinine (P<0.00001), whereas CRP values >4 mg/l were not. A further insight was given by the stratification of the patients for the effects of the interquartile ranges of CRP: it showed a progressive and statistically significant reduction of ß-coefficient inversely related to the increasing CRP values (P=0.003). Thus, the nature of the correlation between CRP and serum creatinine changes with increasing CRP values: from being a direct one, it shows a trend towards a transformation into an indirect one with ß=0 at a CRP value of ~9 mg/l. However, this indirect relationship does not reach statistical significance.

Conclusions. The present cross-sectional study suggests that the activation of acute phase response does not influence creatinine metabolism in haemodialysis patients; in contrast, age, Kt/V and nPCR predict serum creatinine levels. Larger prospective trials are needed to achieve a definitive answer about the relationship between somatic proteins, acute phase response activation and nutrition in dialysis patients.

Keywords: C-reactive protein; haemodialysis; Kt/V; nPCR; serum creatinine; somatic proteins

Introduction

The presence and intensity of the inflammatory response have been classified by levels of proteins of the acute phase response, such as C-reactive protein (CRP) or serum amyloid A or the cytokines that regulate them [1]. Large cross-sectional studies have identified these markers of inflammation as powerful predictors of coronary and cerebrovascular disease in the general population [2,3]. Serum CRP concentrations have also been found to be significantly elevated in haemodialysis patients [4,5], in whom the prevalence of cardiovascular disease is increased ~20–100-fold compared with the general population [6]. In prospective cohort studies of dialysis patients, some investigators recently reported that CRP is one of the most powerful predictors of mortality [79]. We now also have a good understanding of the relationship between inflammation and proxies of visceral proteins such as albuminaemia in dialysis patients [1013]. Less definite is the relationship between inflammation and markers of somatic proteins such as serum creatinine in such patients [1]. In fact, several critical questions do remain: what are the effects of inflammation on serum creatinine? What type of relationship exists between aging, gender, dietary protein intake, dialysis efficiency and serum creatinine? To explore these questions, we conducted a cross-sectional analysis of some potential predictors of serum creatinine in a relatively large cohort of haemodialysis patients.

Subjects and methods

Patient cohort
Two hundred and two patients (stable on haemodialysis for at least 6 months) were being treated in two dialysis units at the hospitals of Martina Franca and Manduria as of June 2001. One hundred and seventy-nine prevalent patients were included in the cohort considered eligible for the present study. Exclusion criteria at the entry of the study were use of a percutaneous haemodialysis catheter, co-morbidity (malignancy, auto-immune disease and/or acute infections), medications (NSAIDs, steroids), and/or recent major traumatisms and surgical interventions that might interfere with the immune system. They were being treated thrice weekly with standard bicarbonate dialysis (with semisynthetic or synthetic membranes, n=154) (138 mmol/l Na, 35 mmol/l HCO3, 2.0 mmol/l K, 1.75 mmol/l Ca, 0.75 mmol/l Mg) or with high-flux haemodiafiltration (n=25) (with either polysulfone or AN69S). Data on age, gender, primary renal disease (diabetes mellitus), dialysis vintage (time since initiation of dialysis) were recorded.

Methods
Midweek pre-dialysis blood samples were collected during the months of June, September through to December 2001 inclusive, and determinations of serum urea (urease method) and creatinine (alkaline picrate method) levels by means of automated machines (Cobas Mira S, Roche, Italy) and of serum CRP levels by means of N high sensitivity assay (Dade Behring Marburg GmbH, Germany) were made. This assay is based on particle-enhanced immunonephelometry: expected values for healthy individuals are typically <=3 mg/l [14].

Furthermore, pre- and post-dialysis body weights were recorded and 2 min post-dialysis serum urea levels were determined three times (June, September and December 2001). They were utilized for the calculation of single pool Kt/V [15] and of normalized protein catabolic rate (nPCR) [16].

Each of the data of this work represents the mean of three determinations made every 3 months in the study period.

Statistical analysis
Results are expressed as mean±SD for continuous parametric data, median (interquartile range) for continuous non-parametric data. Statistical inference of data was performed in two steps: (i) verification of linearity of bivariate correlations between variables and of normality of distribution of residuals; (ii) after obtaining the respect of the criteria of linearity and of normality of distribution of residuals, analysis of multivariate linear regression was performed with serum creatinine as dependent variable; {alpha} values of 1% (P=0.01) were considered for the aims of statistical significance of inferences. All analyses were conducted using Statistica software package (StatSoft Inc., Tulsa, USA).

Results

Table 1Go shows the characteristics of the patients enrolled into the study. Bivariate linear regressions were performed among some variables: age (r=-0.51, P<0.00001), CRP (r=-0.21, P=0.005), Kt/V (r=-0.27, P=0.0003) and nPCR values (r=0.22, P=0.003) were related in a linear manner with serum creatinine with normal distribution of residuals (normal probability plot of residuals versus serum creatinine: r=0.86 for age; r=0.98 for CRP values; r=0.96 for Kt/V values; r=0.97 for nPCR values). On the contrary, dialysis vintage (r=0.08, P=0.27) was not linearly related with serum creatinine. Therefore, the vintage was considered a stratification parameter together with sex and diabetes in our model of multivariate linear regression.


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Table 1.  Characteristics of 179 prevalent haemodialysis patients (males 50.3%, diabetics 13.9%)

 
The analysis of multivariate linear regression was able to validate our model characterized by a dependent variable, serum creatinine, and four independent variables (age, CRP, Kt/V and nPCR) (R2=0.60; F=24.10; P<0.00001; SE=1.94). Age (-0.08 mg/dl decrease in serum creatinine per 1-year increase in age), Kt/V (-0.25 mg/dl decrease in serum creatinine per 0.1 increase in Kt/V) and nPCR (0.10 mg/dl increase in serum creatinine per 0.1 g protein/kg/day increase in nPCR) were independently predictive of serum creatinine (P<0.00001), whereas CRP levels were not (Table 2Go). Table 3Go shows the outputs of multivariate linear regression of the patients stratified for the effects of dialysis vintage (median 44 months; stratification of the patients in two groups, the first with a vintage <=44 months, the latter with a vintage >44 months) and CRP values (median 4 mg/l; stratification of the patients in two groups, the first with CRP values <=4 mg/l, the latter with CRP values >4 mg/l). The stratification of the patients for the effects of vintage did not change the statistical outputs obtained in the analysis of the totality of the patient cohort, whereas the stratification of the patients for the effects of CRP gave the following results: they did not differ from those obtained in the totality of the patient cohort in the group with CRP values >4 mg/l, whereas CRP was directly predictive of serum creatinine in the group stratified for the effects of CRP values <=4 mg/l (Table 3Go). A further insight into the relationship between CRP and serum creatinine was given by the stratification of the patients for the effects of the interquartile ranges of CRP: it showed a progressive and statistically significant reduction of ß-coefficient inversely related to the increasing CRP values (second quartile=0.24; third quartile=0.046; fourth quartile=-0.08; P=0.003) (Figure 1Go). Thus, the nature of the correlation between CRP and serum creatinine changes with increasing CRP values: from being a direct one, it shows a trend towards a transformation into an indirect one with ß=0 at a CRP value of ~9 mg/l. However, this indirect relationship does not reach statistical significance. The direct prediction power of serum creatinine was again statistically significant only in patients with CRP <=4 mg/l and the cut-off of this prediction power was for CRP values of 4 mg/l.


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Table 2.  ß-coefficients and estimates obtained in multivariate linear regression analysis with serum creatinine as dependent variable in 179 prevalent haemodialysis patients

 

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Table 3.  Outputs of multiple linear regression analysis in 179 prevalent haemodialysis patients, stratified for the effects of the vintage (V) (median 44 months) and of CRP values (median 4 mg/l)

 


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Fig. 1.  Trend of ß-coefficient of CRP in multivariate linear regression analysis in 179 prevalent haemodialysis patients stratified for the interquartiles ranges of CRP values.

 
The multivariate linear regression performed stratifying the patients for the effects of gender and diabetes confirmed the statistical outputs reported above: age, Kt/V and nPCR predicted serum creatinine in males and in non-diabetics as already reported for the totality of the patient cohort; CRP was not predictive of serum creatinine in any of the strata (Table 4Go). Only age was predictive of serum creatinine in females (Table 4Go). It must be underlined that serum creatinine was significantly higher in males than in females: it was 9.7±2.8 in males and 8.7±1.8 mg/dl in females (P=0.004). The model lacked any predictive power in diabetics, probably because of their small number in the patient cohort (n=25) (Table 4Go).


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Table 4.  Outputs of multivariate linear regression analysis in 179 prevalent haemodialysis patients, stratified for the effects of the gender and of the presence of diabetes mellitus

 

Discussion

The main aim of the present cross-sectional study was to determine the effects of acute phase response on somatic proteins synthesis. In other words, this work was designed to verify if CRP, an acute phase response index, predicts serum creatinine, an index of muscle mass. The answer is that CRP is not a statistically significant predictor of serum creatinine in the totality of the patient cohort. In fact, the analysis of the behaviour of ß-coefficient of CRP in relationship to the entire spectrum of CRP clearly shows on the one hand that abnormally high CRP values are not predictive of serum creatinine, on the other hand that CRP values <=4 mg/l are directly correlated with serum creatinine. The reason for this phenomenon could lie in the fact that, in the absence of immune activation, CRP is a non-specific protein that is synthesized by the liver in a continuous way, in response to a well-defined physiologic balance. Similarly to the visceral proteins, CRP and somatic protein synthesis could be modulated by the current nutritional status of the subjects. This could induce, even though the metabolic patterns of CRP and somatic proteins are not physiologically correlated, consensual changes in the rate of their synthesis, which explains the correlation we found between normal values of CRP and serum creatinine. In other words, we do suggest an association due to co-linearity rather than causality between CRP values <=4 mg/l and serum creatinine. In contrast, the activation of acute phase response could lead to the loss of this balance and then to the loss of the relationship between the two variables. The data, taken together, lead to the conclusion that acute phase response does not influence creatinine metabolism. At variance with our data, Kaysen et al. [1] found an inverse relationship between CRP and serum creatinine. In a further study, the same authors found an inverse relationship between CRP and serum creatinine only for CRP levels >13 mg/l [17]. The reasons for this discrepancy are far from being clear. One reason could lie in the fact that their CRP assay was insensitive in the lower range, as the same authors admit [1], whereas our CRP assay was based on a high sensitivity immunonephelometric method. Prospective trials with a larger number of patients are necessary to elucidate this question.

The other aims of the present cross-sectional study were to explore the potential relationship among serum creatinine and aging, gender, dialysis efficiency and dietary protein intake: (i) aging and gender: data obtained in all patients demontrate that age predicts serum creatinine. This inverse correlation, already described by Kaysen et al. [1], is due to the well-known phenomenon of reduction of muscle mass that is present in aging: creatinine is a product of muscle metabolism which decreases in older patients [18]. The importance of aging in predicting serum creatinine was confirmed by adjusting for the effects of gender: this correlation was less strong in females than in males, probably because of the smaller development of muscle mass in females [19], as indirectly shown in our study by a lower mean serum creatinine in females. The influence of aging on serum creatinine was also confirmed by adjusting for the effects of vintage and of the interquartile ranges of CRP values. (ii) Haemodialysis efficiency: as computed by single pool Kt/V, this predicts serum creatinine, as already shown by Kaysen et al. [1]. The inverse correlation between Kt/V and serum creatinine has the clear meaning of a better creatinine clearance when efficiency of the dialysis treatment increases. (iii) Dietary protein intake: an important limitation of this study is that dietary intake was not measured. However, nPCR is considered a valid surrogate for dietary protein intake under steady-state conditions [1]. The direct correlation between serum creatinine and nPCR, already described by Kaysen et al. [1], can be explained by the potential relationship among dialysis efficiency, increased removal of uraemic toxins and correction of metabolic anomalies linked to uraemia that induce protein and amino acid catabolism, like metabolic acidosis [20]. The improvement in dialysis efficiency can also induce a larger daily caloric intake by means of the increase in appetite and reduction of hypercatabolic status. This chain of events can ameliorate the syndrome known as ‘protein energy malnutrition’ of the dialysis patients [1] with an increase of muscle mass and therefore of serum creatinine.

The correlations described between Kt/V, nPCR and serum creatinine were confirmed by adjusting for the effects of vintage, but not for the effects of gender; in fact, these variables were not related in females for the reason that the lower serum creatinine that characterizes these subjects is probably not sufficient to give a statistical significance.

We do not discuss deliberately the data obtained in diabetics because of the small number of the sample.

Finally, it is clear that cross-sectional studies have widely known limitations. The data in this work are the first part of an ongoing longitudinal study, which should be able to address several of the above issues.

In conclusion, the present cross-sectional study suggests that the activation of acute phase response does not influence creatinine metabolism in haemodialysis patients; by contrast, age, Kt/V and nPCR predict serum creatinine levels. We need larger prospective trials in order to achieve a definitive answer about the relationship among somatic proteins, acute phase response activation and nutrition in dialysis patients.

Conflict of interest statement. None declared.

Notes

Correspondence and offprint requests to: Carlo Basile, MD, Via Battisti 192, 74100 Taranto, Italy. Email: nefromartina{at}topvideo.net Back

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Received for publication: 4. 6.02
Accepted in revised form: 23.10.02