|Year : 2017 | Volume
| Issue : 3 | Page : 679-686
The correlation between residual renal function and inflammation in chronic hemodialysis patients
Said S Ahmed Khamis1, Yassin S Yassin2, Ashraf A Dawood3, Khaled M Amin El Zorkany3, Elsayed G Mahros MSc 3
1 Department of Biochemistry, Internal Medicine and Nephrology, Faculty of Medicine, Menoufia University, Menoufia, Egypt
2 Department of Nephrology, Faculty of Medicine, Menoufia University, Menoufia, Egypt
3 Department of Internal Medicine and Nephrology, Faculty of Medicine, Menoufia University, Menoufia, Egypt
|Date of Submission||19-Jul-2016|
|Date of Acceptance||02-Oct-2016|
|Date of Web Publication||15-Nov-2017|
Elsayed G Mahros
Zagazig, Sharqia, 44661
Source of Support: None, Conflict of Interest: None
The aim of the study was to study any possible correlation between inflammation and residual renal function (RRF) in chronic hemodialysis (HD) patients.
RRF plays an important role in maintaining fluid balance, phosphorus control, nutrition, and removal of middle molecular uremic toxins. Decline of RRF also contributes significantly to anemia, inflammation, and malnutrition in patients on dialysis. Inflammation and activation of acute-phase responses are common in chronic kidney disease patients. The causes of inflammation in HD patients are multifactorial. Inflammatory reaction may originate from several sources, including graft or fistula infections, bioincompatible dialysis membrane, dialysate, endotoxin exposure, back filtration, chronic infections, and malnutrition. High-sensitivity C-reactive protein (hsCRP) assay is useful for sensitive detection of the inflammatory state.
Patients and methods
Fifty patients on regular HD were divided into two groups: group 1 comprising 25 patients with RRF and group 2 comprising 25 patients without RRF. Estimation of hsCRP and serum albumin and calculation of RRF were carried out.
The mean and SD of hsCRP in HD patients without RRF was 14.90 ± 11.58 mg/l and that in HD patients with RRF was 5.71 ± 3.56 mg/l (P = 0.000). There was significant negative correlation between hsCRP and residual kidney function (r = −0.574) in group 1. There was no statistically significant difference between groups regarding serum albumin.
The levels of hsCRP were found to be elevated in chronic kidney disease on dialysis patients. There was a significant relationship between reduced glomerular filtration rate and hsCRP levels.
Keywords: high-sensitivity C-reactive protein, inflammation, residual renal function
|How to cite this article:|
Ahmed Khamis SS, Yassin YS, Dawood AA, Amin El Zorkany KM, Mahros EG. The correlation between residual renal function and inflammation in chronic hemodialysis patients. Menoufia Med J 2017;30:679-86
|How to cite this URL:|
Ahmed Khamis SS, Yassin YS, Dawood AA, Amin El Zorkany KM, Mahros EG. The correlation between residual renal function and inflammation in chronic hemodialysis patients. Menoufia Med J [serial online] 2017 [cited 2020 Apr 5];30:679-86. Available from: http://www.mmj.eg.net/text.asp?2017/30/3/679/218266
| Introduction|| |
Residual renal function (RRF) in patients with end-stage renal disease (ESRD) receiving renal replacement therapy is defined as the ability of native kidneys to eliminate water and uremic toxins. In clinical practice, it is considered synonymous with such parameters as daily diuresis and/or glomerular filtration rate (GFR). The optimal method to measure RRF has not been established . RRF remains important even after beginning of dialysis. RRF contributes significantly to the overall health and well-being of patients on dialysis . It plays an important role in maintaining fluid balance, phosphorus control, nutrition, and removal of middle molecular uremic toxins and shows inverse relationships with valvular calcification and cardiac hypertrophy in patients on dialysis. Decline in RRF also contributes significantly to anemia, inflammation, and malnutrition in patients on dialysis . RRF may allow for a reduction in the duration of hemodialysis (HD) sessions and the need for dietary and fluid restrictions in both patients on peritoneal dialysis (PD) and patients on HD. More importantly, the loss of RRF is a powerful predictor of mortality . Much of RRF is lost during the first 18 months of HD, and appears to depend on the primary cause(s) of kidney failure as well as on other patient-related and treatment-related factors .
Inflammation and activation of acute-phase responses are common in chronic renal disease (CKD) and are observed in the early stages of CKD as well . The prevalence of inflammation increases with deterioration of renal function . The causes of inflammation in HD patients are multifactorial. Although inflammation may directly result in cardiovascular injuries, the underlying cardiovascular complications in these patients may be also associated with inflammatory response . Inflammatory reaction may originate from several sources such as graft or fistula infections, bioincompatible dialysis membrane, dialysate, endotoxin exposure, back filtration, chronic infections, and malnutrition . Poor oral, dental, and periodontal health in HD patients can be a source of inflammatory reactions . In addition to C-reactive protein (CRP), which seems to be the most important marker for the identification and control of inflammation in clinical practice, many other markers are also available for the evaluation of inflammatory state. Serum levels of high-sensitivity C-reactive protein (hsCRP), tumor necrosis factor α (TNFα), albumin, and adiponectin also increase in patients with chronic renal failure (CRF). In addition, high levels of other related parameters of inflammation, such as erythrocyte sedimentation rate, hepcidin, and ferritin, may be seen in patients with ESRD, whereas, by contrast, serum albumin, low-density lipoprotein, and high-density lipoprotein cholesterol levels decrease with inflammation .
| Patients and Methods|| |
The present study was carried out on 50 patients (aged 37–76 years) on regular HD in the Hemodialysis Unit of Nasr City Hospital of Insurance, Egypt. All patients gave informed consent and the study was approved by the local medical committee of the hospital.
The patients were divided into two groups:
Group 1: This group comprised 25 patients on regular HD who have preserved RRF.
Group 2: This group comprised 25 patients on regular HD who do not have preserved RRF.
Patients on regular HD for more than 3 months and older than 18 years were eligible for inclusion in this study.
Patient on diuretics, those who were pregnant, and those with malignancy or infection were excluded.
All participants were subjected to the following: detailed medical history, renal function tests (creatinine urea before and after HD), determination of serum CRP (high sensitive) as an inflammatory marker, and determination of serum albumin levels.
The RRF was calculated for all patients by the following formula :
RRF = ID urine volume × urine urea concentration/ID period/mean BUN.
Where mean BUN=(U1 + U2)/2, U1 is the BUN just after the first dialysis of the week, U2 is the BUN just before the second dialysis of the week, and ID stands for interdialytic period.
Data were analyzed using the statistical program for the social sciences (SPSS, version 20.0; IBM, Armonk, New York, USA). Quantitative data were expressed as mean ± SD and qualitative data were expressed as frequency and percentage.
The following tests were conducted: independent-sample t-test of significance was used when comparing between two means; the c2-test of significance was used to compare proportions between two qualitative parameters; and Pearson's correlation coefficient (r) test was used for correlating data. P values were interpreted as follows: P value less than or equal to 0.05 was considered significant, P value less than or equal to 0.001 was considered highly significant, and P value more than 0.05 was considered nonsignificant.
| Results|| |
There was a statistically significant difference between groups on the basis of demographic data [Table 1].
|Table 1: Comparison between group 1 and group 2 on the basis of demographic data|
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There was a highly statistically significant difference between groups on the basis of the duration of dialysis (years), on using the independent-sample t-test [Table 2].
|Table 2: Comparison between group 1 and group 2 according duration of dialysis (years)|
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There was no statistically significant difference between groups on the basis of the cause of RF, on using the c2-test [Table 3].
|Table 3: Comparison between group 1 and group 2 on the basis of the cause of renal failure|
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There was no statistically significant difference between groups on the basis of urea reduction test (URT) and creatinine, on using the independent-sample t-test [Table 4].
|Table 4: Comparison between group 1 and group 2 on the basis of the urea reduction test, serum creatinine, and residual kidney function|
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There was no statistically significant difference between groups on the basis of serum albumin, on using the independent-sample t-test [Table 5].
|Table 5: Comparison between group 1 and group 2 on the basis of serum albumin|
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There was a highly statistically significant difference between groups on the basis of hsCRP, on using the independent-sample t-test [Table 6].
|Table 6: Comparison between group 1 and group 2 according to high-sensitivity C-reactive protein (mg/l|
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There was a significant positive correlation between hsCRP and age and a significant negative correlation between hsCRP URT (%) and residual kidney function (RKF) [Table 7] and [Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5], [Figure 6], [Figure 7].
|Table 7: Correlation between high-sensitivity C-reactive protein and other parameters using Pearson's correlation coefficient in group 1|
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|Figure 1: Comparison between group 1 and group 2 on the basis of urea reduction test and creatinine.|
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|Figure 2: Comparison between group 1 and group 2 on the basis of albumin.|
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|Figure 3: Comparison between group 1 and group 2 on the basis of high-sensitivity C-reactive protein (hsCRP) (mg/l).|
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|Figure 4: Significant positive correlation between high-sensitivity C-reactive protein. (hsCRP) and age in group 1.|
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|Figure 5: Significant negative correlation between high-sensitivity C-reactive protein. (hsCRP) and urea reduction test. (%) in group 1.|
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|Figure 6: Significant negative correlation between high-sensitivity C-reactive protein. (hsCRP) and residual kidney function in group 1.|
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|Figure 7: Significant positive correlation between high-sensitivity C-reactive protein. (hsCRP) and age in group 2.|
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| Discussion|| |
Recurrent or chronic inflammatory processes are common in individuals with CKD, including those with CRF and especially ESRD .
Multiple factors can contribute to immune dysregulation and inflammatory activation in CKD. Some of them may be related to the primary disease rather than to uremia per se. Other modifiers originate from the genetic background, as well as from the diet, lifestyle, and environment, representing epigenetic influences. Decreased renal clearance clearly accounts for higher levels of circulating cytokines, although increased production has also been described .
An inverse correlation between GFR and inflammation has now been clearly proven. In the Chronic Renal Insufficiency Cohort (CRIC) study, biomarkers of inflammation [interleukin (IL)-1β, IL-1 receptor antagonist, IL-6, TNFα, CRP, and fibrinogen) were inversely associated with the measures of kidney function and positively with albuminuria . Inflammation is present not only in adults but also in pediatric patients with CKD/ESRD . Interestingly, the erythrocyte sedimentation rate in adolescents has been shown to be predictive of ESRD in middle-aged men .
Children with CRF show increase in serum hepcidin level; its level increases with increase in the years of HD, CRP levels, and serum ferritin .
Different biomarkers of inflammation appear to have a different predictive value in CKD/ESRD. In a large multicentral international database of HD patients, CRP predicted mortality with a precision comparable to that of albumin and exceeding that of ferritin and white blood cell count .
Cytokines along with CRP and serum albumin can also be considered for prognosis of long-term mortality in ESRD .
RRF represents the function of the native kidneys or the in-situ kidney allograft in ESRD . RKF is of significant prognostic importance for patients on HD . It has many clinical advantages including improved nutrition, anemia, and phosphate control. Even small amounts of RKF can provide significant benefit .
RRF confers a survival benefit among dialysis patients that is thought to be related to greater volume removal and solute clearance. The maintenance of urine volume in PD patients may allow for reduced dextrose exposure, hyperglycemia, hypercholesterolemia (particularly hypertriglyceridemia), weight gain, and perhaps greater preservation of peritoneal membrane function; among HD patients, lower ultrafiltration volume, less intradialytic hypotension, and myocardial stunning may result. It is hypothesized that the removal of middle molecules, improved volume control, and less inflammation may mediate this survival benefit .
Although RRF is important to both HD and PD patients, it is a more prominent consideration in the latter group, where it has been better studied, plays a greater role (dialysis dosing), and persists for a longer period of time. Although the significance of RRF may differ in HD and PD patients and there may be unique causes for its decline in the two groups, its gradual loss may be due to many similar factors .
This study was carried out on 50 patients on regular HD in the Hemodialysis Unit of Nasr City Hospital of Insurance, Egypt, between July 2014 and January 2015. The current study is a cross-sectional work that highlights the relationship between RRF and inflammation in chronic HD patients.
The following factors were included in the analysis: renal function (creatinine, urea before and after HD), serum CRP (high sensitive) as an inflammatory marker, serum albumin, estimated GFR, age, sex, race, history of diabetes and hypertension, duration of dialysis, and cause of ESRD.
In this study, there was no statistically significant correlation between groups regarding age and sex. The mean age of HD patients in group 1 was 59.56 ± 9.29 years, and 80% of them were male; the mean age of HD patients in group 2 was 60.32 ± 15.31 years, and 80% of them were male.
Our study revealed the most common cause of ESRD to be hypertension (44% in group 1 vs. 48% in group 2), diabetes mellitus (32% in group 1 vs. 28% in group 2), obstructive uropathy (12% in group 2 vs. 8% in group 1), glomerulonephritis (8% in group 1 vs. 4% in group 2), analgesic nephropathy (4% in group 1 vs. 4% in group 2), and polycystic kidney disease (4% in group 1 vs. 4% in group 2).
The mean duration of dialysis in group 1 was 1.18 ± 0.66 years and that in group 2 was 5.76 ± 3.78 years. URT (%) was 60.60 ± 4.10% in group 1 and 63.08 ± 5.63% in group 2.
Creatinine was 7.71 ± 1.32 mg/dl in group 1 and 11.32 ± 14.00 mg/dl in group 2.
In our study there was an increase in hsCRP in both groups (5.71 ± 3.56 mg/l in group 1 and 14.90 ± 11.58 mg/l in group 2). This finding is concordant with that of Elmessallamy et al. , who noticed that there was a statistically significant increase in hsCRP in CRF patients in relation to controls. This could be due to immune dysregulation and inflammatory activation in CKD as the uremic milieu produces oxidative stress  and carbonyl stress , which are highly proinflammatory. Decreased renal clearance clearly accounts for higher levels of circulating cytokines, although increased production has also been described . Decreased antioxidants due to the oral intake or the level of some antioxidants is lower than normal in both CRF and ESRD patients. An acute-phase response is also associated with decreased plasma levels of several antioxidants, such as serum vitamin C concentrations . In addition, it was suggested that uremic toxins may contribute to intestinal dysbiosis in CKD and lead to an increased translocation of gut bacteria and bacterial components in the circulation, which can in turn activate systemic inflammation .
Metabolic acidosis is another cause of inflammation in CKD . Vitamin D deficiency is another factor, as vitamin D is a regulator of the immune system. In addition to the inability to form 1,25(OH)2-vitamin D, many patients with CKD also lose the capacity to maintain normal serum 25(OH)-vitamin D levels . The immune dysfunction associated with vitamin D deficiency in patients with CKD and ESRD has been proposed as one of the causes of the misdirected inflammatory response seen in this population . A number of extracorporeal factors have been implicated in inflammatory activation in dialysis patients, including impurities in the dialysis water, microbiological quality of the dialysate, and bioincompatible factors in the extracorporeal dialysis circuit . In addition to the previous causes it was shown that HD treatment acutely upregulates transcription of proinflammatory cytokines . Other modifiers originate from the genetic background, as well as from the diet, lifestyle, and environment, representing epigenetic influences .
Many authors have shown elevated levels of hsCRP after HD sessions. Koulouridis et al.  found an increase of 6.7 mg/l in hsCRP levels after 4 h of HD and Park et al.  reported an increase in hsCRP levels of 4 mg/l after HD. Patients who undergo longer HD treatment might suffer major consequences of inflammatory stimuli and progressively show a decrease in RRF. Therefore, patients who undergo dialysis for a period of months or years will progressively lose their RRF.
Our study demonstrated a negative correlation between hsCRP levels and RRF. Furthermore, the analysis of our results showed that RRF contributed to the changes in the concentrations of hsCRP. When comparing the two groups, we found that there was a highly statistically significant increase in hsCRP in group 2 (14.90 ± 11.58 mg/l) in comparison with group 1 (5.71 ± 3.56 mg/l) (P = 0.000), and negative significant correlation between hsCRP and RKF in group 1. These data indicate that in patients under HD treatment, RKF probably disappears because of the intensity of the systemic inflammatory state, which in turn is a consequence of the time spent between starting HD treatment and the total loss of RKF.
These results agreed with those of Borges et al.  and Kumar and Shobharani , who found that there was a significant relationship between reduced GFR and hsCRP levels, which suggests that there is inflammatory activity in CKD patients. These results were also consistent with the findings of Pecoits et al.  in predialysis chronic kidney disease patients; they reported a similar inverse relationship between renal function and proinflammatory mediators.
Although the exact mechanism of association remains to be elucidated, the study has indicated that the relationship between RRF and inflammation is largely independent of the cardiovascular status of patients . However, a deteriorating renal function may enhance the overall inflammatory responses because of the decreased renal clearance of factors that are directly or indirectly involved in inflammation. As an example, the serum half-lives of proinflammatory cytokines, TNFα, and IL-1 are greater in animals without renal function than in those with renal function .
Vascular congestion, which increased with deteriorating RRF because of fluid overload in patients with renal insufficiency, may result in altered permeability of the gastrointestinal tract, thereby leading to accumulation of endotoxins such as lipopolysaccharides and bacteria. These processes may in turn stimulate monocytes and increased release of proinflammatory cytokines .
It was suggested that uremic toxins, which accumulate with loss of RRF, may contribute to intestinal dysbiosis in CKD and lead to an increased translocation of gut bacteria and bacterial components in the circulation, which can in turn activate systemic inflammation . Arecent cross-sectional study in stage 3–4 CKD demonstrated that indoxyl sulfate and p-cresyl sulfate (nephrovascular and cardiovascular toxins, produced solely by the gut microbiota) were associated with elevated levels of inflammatory biomarkers as well as with increased arterial stiffness .
Decreased renal clearance clearly accounts for higher levels of circulating cytokines .
Our study shows significant negative correlation between hsCRP and age. This is in concordance with the results of Elmessallamy et al. , who reported that age and hsCRP had a significant correlation with the mean CIMT. It is well known that advancing age is the most powerful cardiovascular risk factor.
This study shows significant negative correlation between hsCRP and URT. This result goes hand in hand with that of Rashid et al. , who found that when the Kt/V was compared with the CRP level, there was a negative correlation between the two parameters (r = −0.212, P = 0.032). Low Kt/V means dialysis inadequacy, which is associated with chronic inflammatory state, resulting in high CRP levels.
Low plasma albumin levels are also associated with inflammation in CKD . However, our results did not show any significant difference between groups regarding serum albumin. This is commensurate with the results of Borges et al. , who found that serum albumin concentrations were not different between groups in a study of 80 patients with CKD undergoing HD. The patients were stratified according to RD into the anuric (residual diuresis−) group (n = 47) and the nonanuric (residual diuresis+) group (n = 33). In addition, this study concurs with that of Gama-Axelsson et al. , who found that serum albumin levels among patients with normal nutritional status did not differ between inflamed and noninflamed patients.
| Conclusion|| |
Increased hsCRP level has a significant negative correlation with RRF, suggesting that, although a great part of the CKD population presents an inflammatory state, RRF has an important role in decreasing the degree of inflammation in HD patients. However, further studies are needed to validate these findings.
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Conflicts of interest
There are no conflicts of interest.
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[Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5], [Figure 6], [Figure 7]
[Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6], [Table 7]