| Abstract|| |
It has been verified that the red blood cell distribution width (RDW) is related to renal function. This study aimed to investigate the association of RDW with the residual renal function in peritoneal dialysis (PD) patients. The patients were categorized into three groups according to the quartiles of their baseline RDWs. The correlations between RDW and clinical parameters, dialysis adequacy, and residual renal function were analyzed. The clinical data, PD prescription and dialysis adequacy of 54 uremic patients on continuous ambulatory PD were collected. All the statistical analyses were performed using the Statistical Package for the Social Sciences program version 17.0. The baseline RDW of the patients was 13.56% ± 1.36%. No significant differences in the other indexes [hemoglobin, albumin, alkaline phosphatase, intact parathyroid hormone (iPTH), urea and creatinine] among the three groups were found. One month after beginning PD, the correlation between the RDW and the residual renal function has not been found in the multivariate regression model adjusted for the hemoglobin, albumin, and leukocyte. Three months after beginning the PD, a significant difference between Group 2 and Group 3 in iPTH was found. Multivariate regression analysis showed that the elevated RDW is associated with the declined residual glomerular filtration rate (heart rate = -0.587, 95% confidence interval -1.080 ~ -0.093) for the corresponding period after PD, adjusted for the hemoglobin, albumin, and leukocyte. This study showed that the RDW reflected the residual renal function in the corresponding period after PD in the PD patients.
|How to cite this article:|
Zhang Q, Cao X, Zhou J, Ding R, Huang J, Cai G, Chen X. Red cell distribution width reflects the early stage residual renal function in peritoneal dialysis patients. Saudi J Kidney Dis Transpl 2018;29:1082-91
|How to cite this URL:|
Zhang Q, Cao X, Zhou J, Ding R, Huang J, Cai G, Chen X. Red cell distribution width reflects the early stage residual renal function in peritoneal dialysis patients. Saudi J Kidney Dis Transpl [serial online] 2018 [cited 2019 May 19];29:1082-91. Available from: http://www.sjkdt.org/text.asp?2018/29/5/1082/243950
| Introduction|| |
The primary evaluation standards of the adequacy of dialysis in peritoneal dialysis (PD) patients are the urea clearance index (Kt/V) and the creatinine clearance (CrCl), including the peritoneal clearances and residual renal clearances. Although the total clearance of creatinine or urea is an important determinant of survival in PD patients, it is the residual renal function, not the peritoneal clearance, that is significantly and independently associated with PD patients’ survival time. In PD patients, protecting the residual renal function is of great importance to an improved prognosis. In clinical practice, we hope to find a convenient, accessible, and inexpensive indicator to predict the residual renal function of patients undergoing PD.
The red blood cell distribution width (RDW), which reflects the variability in the sizes of the circulating erythrocytes, is a widely reported parameter of the complete blood count and is used to evaluate anemia and thrombocytopenia.,, The RDW has also been proved to be an independent predictor of mortality in patients on chronic hemodialysis (HD)., Among the patients undergoing PD, an increase in the RDW is associated with the risk of cardiovascular mortality and all-cause mortality. Recently, a study by Lippi et al confirmed that the estimated glomerular filtration rate (GFR) progressively decreased across quartiles of the RDW in unselected adult outpatients. The research of Ujszaszi et al studied kidney transplant recipients and showed the similar result that a lower estimated GFR is related to a higher RDW. In addition, a previous study has shown that the RDW values significantly increase with poorer kidney function among chronic kidney disease (CKD) patients and have a negative relationship with the estimated GFR. Nevertheless, whether a negative correlation between the RDW and the renal function exists in PD patients has not been studied before. We hypothesized that the RDW may have a relationship with the residual renal function and the adequacy of the dialysis in patients on PD and investigated this possibility in our study.
| Subjects and Methods|| |
This retrospective study enrolled 54 stable continuous ambulatory PD (CAPD) patients from our PD center. These patients received PD catheterization and were followed up in our PD center. The exclusion criteria were as follows: (1) patients whose clinical indexes (including routine complete blood counts, biochemical parameters, intact parathyroid hormone (iPTH), and PD adequacy) lacked integrity and whose follow-up period was <3 months, (2) patients on automated PD, day ambulatory, or intermittent PD, (3) patients who had any malignant diseases or were pregnant, (4) and patients whose primary disease had active lesions, such as systemic lupus erythematosus, systemic vasculitis, and so forth. According to the above standard, a total of 54 patients (24 males, 30 females) were eligible for the study.
Peritoneal dialysis prescription and dialysis adequacy
The study evaluated the PD adequacy in three primary aspects as follows: the calcium and phosphorus metabolism, nutritional status, and solute clearance. By measuring the total weekly Kt/V for the urea and total weekly CrCl, the adequacy of the dialysis was estimated. The PD and residual renal function were calculated separately. The residual GFR was computed using the average of the 24-h urinary urea and CrCl. The creatinine concentration in the dialysate was corrected for interference by glucose. The total body water was estimated using the formula of Watson et al.
In this study, we defined the conditions of the enrolled patients before PD as the baseline. The patients were categorized into three groups according to the quartiles of their baseline RDWs: Group 1, RDW ≤12.5% (n = 11); Group 2, 12.5% ≤RDW <14.2% (n = 29); Group 3, RDW >14.2% (n = 14). General clinical data were collected at the baseline and at one month and three months after PD. Routine complete blood counts, biochemical parameters, and iPTH studies were conducted in the enrolled patients. Based on CKD-Epidemiology Collaboration equation, the serum creatinine before PD was converted to estimated GFR. The indexes of the PD adequacy at one month and three months after PD were calculated and recorded. The body mass index (BMI) was computed from the patients’ weight in kilograms divided by the square of their height in meters [BMI = weight (kg)/height (m2)].
| Statistical Analysis|| |
All the statistical analyses were performed using the Statistical Package for the Social Sciences program (SPSS) version 17.0 (SPSS Inc., Chicago, IL, USA). The continuous variables were expressed as the means ± standard deviation or medians and range. The differences in features between the groups were assessed using a one-way analysis of variance or the Kruskal–Wallis H test. The linear correlation between the RDW and the clinical parameters, dialysis adequacy and residual renal function, were first analyzed using Pearson’s correlation or Spearman’s correlation analyses. To investigate the contribution of the RDW to the residual renal function and dialysis adequacy, the multivariate linear regression analysis was used to determine the statistically significant factors associated with residual renal function, as well as dialysis adequacy. As a dependent variable, each variable of residual renal function and dialysis adequacy was separately introduced into the multivariate regression model, adjusted for hemoglobin, albumin, and leukocyte. A two-sided P <0.05 was considered statistically significant.
| Results|| |
The baseline characteristics of the 54 PD patients are shown in [Table 1]. The RDW ranged from 11.7% to 18.6% (13.6% ± 1.4%). The characteristics of the patients at the baseline were not significantly different among the three groups [Table 1]. Forty-seven of the patients were clinically diagnosed with primary glomerulonephritis, three patients with nephropathy, three patients with hypertensive nephropathy, and one patient with Henoch-Schönlein purpura nephritis.
|Table 1: The baseline characteristics of the 54 enrolled peritoneal dialysis patients.|
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One month after peritoneal dialysis
During this study, although no significant differences in the serum albumin and hemoglobin were found among the groups, the serum albumin and serum hemoglobin declined as the baseline RDW increased (P >0.05) [Table 2]. Other clinical variables, including the serum levels of alkaline phosphatase (ALP), iPTH, urea, and creatinine, showed no statistically significant differences among the groups (P >0.05) [Table 2]. The correlations of the baseline RDW, clinical variables, and dialysis adequacy were analyzed. The RDW at one month after PD was negatively correlated with the residual renal Kt/V (r = −0.265, P = 0.053) and the residual renal CrCl (r = −0.255, P = 0.063) for the corresponding period [Table 3]. However, those correlations were not found in the multivariate regression model adjusted for the hemoglobin, albumin, and leukocyte [Table 4].
|Table 2: A comparison of the clinical data among the three groups of peritoneal dialysis patients at 1 month after beginning peritoneal dialysis.|
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|Table 3: The correlation between the RDW and the residual renal function, as well as the relationship among the inflammatory variables in the peritoneal dialysis patients.|
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|Table 4: The correlation between the RDW and the residual renal function, dialysis adequacy.|
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The differences in the inflammatory indicators among the groups, including the number of leukocytes, neutrophils, mononuclear cells, and C-reactive protein (CRP), were not obvious [Table 2]. A negative relationship between the residual renal function and inflammatory indicators was found. The RDW at one month after beginning the PD was positively correlated with the number of mono-nuclear cells (r = 0.287, P = 0.003).
Three months after peritoneal dialysis
No significant differences were found in a comparison of the clinical parameters (albumin, hemoglobin, ALP, iPTH) and the indexes of the adequacy of the PD and residual renal function among the groups [Table 5]. The correlation between the RDW at three months after PD and the residual renal CrCl during this period was statistically significant (r = −0.267, P = 0.051) [Figure 1] and [Table 3]. A negative relationship between the RDW and residual GFR was also observed (r = −0.405, P = 0.003) [Figure 2]. Multivariate regression analysis showed that the declined residual GFR [heart rate (HR) = −0.587, 95% confidence interval (CI) −1.080 ~ −0.093] is associated with the elevated RDW adjusted for the hemoglobin, albumin, leukocyte [Table 4]. The correlation between the elevated RDW and the decreased residual renal CrCl (HR = −4.922, 95% CI −9.206 ~ −0.639) was observed in multivariate regression analysis adjusted the hemoglobin, albumin, leukocyte [Table 4]. Similarly, the relationship between the elevated RDW and the decreased total CrCl (HR = −4.069, 95% CI −7.776 ~ −0.361) has also been found [Table 4].
|Table 5: A comparison of the clinical data among the three groups of patients 3 months after beginning peritoneal dialysis.|
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|Figure 1: The relationship between the residual renal CrCl and the concurrent RDW at 1 month after peritoneal dialysis.|
CrCl: Creatinine clearance, RDW: Red blood cell distribution width.
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|Figure 2: The relationship between the residual GFR and the RDW at 3 months after peritoneal dialysis.|
GFR: Glomerular filtration rate, RDW: Red blood cell distribution width.
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Changes of inflammatory indicators, including the number of leukocytes, neutrophils, mononuclear cells, and CRP, were not observed [Table 5]. The RDW at three months after the PD was positively correlated with the number of mononuclear cells (r = 0.307, P = 0.024).
| Discussion|| |
The objective of this study was to determine the prognostic value of the RDW in CAPD patients for evaluating the residual renal function. The differences among the groups were analyzed by categorizing the patients according to the quartiles of their baseline RDW values. The correlations between the RDW and the residual renal function and clinical variables were also studied. The primary result of our study indicates that a higher RDW is associated with a lower residual renal function and residual CrCl at three months after PD. To the best of our knowledge, this study is the first one to show the relationship between the RDW and the residual renal function in patients undergoing PD.
Although the mechanism of the association of the RDW with the residual renal function is not clear, a variety of viewpoints have been proposed. The total clearance of the creatinine or urea is meaningful to the survival of PD patients. It is important to note that the residual renal function has a more beneficial effect on PD patients’ outcomes than the peritoneal clearance., The residual GFR represents an independent predictor of CAPD patient survival, due to its small solute clearance and the endocrine function of the residual renal function. Chronic dialysis patients are characterized by increased inflammation and oxidative stress. Therefore, we speculated that inflammation plays an important role in the relationship between the RDW and the residual renal function. The study analyzed the relationship between the inflammatory parameters and the residual renal function and the correlation between indicators of inflammation and the RDW. The negative relationships between the residual renal function and the leukocytes, neutrophil granulocytes, and C-reactive protein have been found to be apparent in the first month of PD. However, we did not find a similar correlation at the three-month follow-up of the PD patients. The mononuclear leukocytes of the first and third months’ follow-up showed a significant positive relationship with the concurrent RDW. These results do not contradict our above hypothesis. Inflammation is known to be an independent risk factor for the loss of residual renal function. The inflammatory cytokines can enter the circulation, produce nephrotoxic effects and cause a decline in the residual renal nephrons. Meanwhile, inflammation can exert an effect on the RDW and cause it to increase.,,,, Some studies have shown that inflammatory cytokines may have an impact on bone marrow function and inhibit erythropoietin., As maturation and proliferation are suppressed, immature erythrocytes are released into the circulation, leading to changes in the RDW values. Further studies have also found that different markers of inflammatory pathways were significantly related to the RDW values. In addition, an increased RDW may reflect a state of high oxidative stress. Oxidative stress can reduce RBC survival and induce the release of premature RBCs. An analysis has also shown that RDW values are associated with a decrease in serum antioxidants and are elevated in patients who are characterized by oxidative stress conditions, such as in dialysis.,
Another implicated element may be malnutrition. With the decrease in the GFR, the morbidity of protein energy wasting increases. A higher prevalence of nutrient deficiencies has been observed in geriatric patients with a higher RDW, although there was no clear gradient across the RDW quartiles. Moreover, the RDW is a good integrative marker of the complex malnutrition-inflammation syndrome. We believe that an elevated RDW and the residual renal function may be the common presentation of the conditions of inflammation, oxidative stress, and malnutrition. The endothelial dysfunction may also contribute to the association of RDW with residual renal function. A study by Solak et al verified that the RDW is associated with endothelial dysfunction and inflammation, regardless of the level of the anemia in patients with CKD. The study indicates that RDW may be a novel predictor of the residual renal function of patients on PD in the corresponding period. The findings are consistent with those in unselected adult outpatients, kidney transplant recipients and patients with CKD. This conclusion may yield important information on the relationship between a higher RDW and the high rate of PD patients’ cardiovascular mortality.
The second result observed in our study concerned the decreases of albumin and hemoglobin in association with an elevated baseline RDW. As a critical factor in the malnutrition-inflammation-atherosclerosis syndrome, low albumin levels are a strong predictor of mortality in patients new to HD. As renal function worsens, dietary protein intake (DPI) is spontaneously reduced in chronic renal failure patients. Similarly, another study noted an independent effect of the residual renal function on the actual DPI in patients on CAPD. Lower serum albumin can aggravate the conditions of inflammation and malnutrition, damage the residual renal function and lead to an increased RDW.
However, a selection bias may have occurred, since the number of patients in the study is small, and patient heterogeneity may result in a significant selection bias. Therefore, a larger multicenter study and a longer duration of follow-up on the correlation of RDW with the residual renal function in CAPD patients undergoing PD are needed.
| Conclusion|| |
This study showed that RDW elevation may be a novel predictor of residual renal function decrease in CAPD patients in the initial stage of PD. Considering that RDW is routinely tested in blood examinations and therefore poses no added costs, further research is required to verify whether the RDW is a useful predictor in the evaluation of the residual renal function of CAPD patients during the late stages of PD.
| Acknowledgment|| |
This study was supported by the National Key R&D Program of China (2018YFA0108803, 2018YFC0114503, 2016YFC1103004), the Science and Technology Project of Beijing (D181100000118004).
Conflict of interest: None declared.
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Prof. Guangyan Cai
Department of Nephrology, National Clinical Research Center for Kidney Diseases, Chinese PLA General Hospital, Chinese PLA Institute of Nephrology, State Key Laboratory of Kidney Diseases, Beijing 100853
[Figure 1], [Figure 2]
[Table 1], [Table 2], [Table 3], [Table 4], [Table 5]