Skip to main content

Neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio in evaluation of inflammation in non-dialysis patients with end-stage renal disease (ESRD)

Abstract

Background

Neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) have been reported to be associated with inflammation in end-stage renal disease (ESRD) receiving dialysis. However, the value of NLR and PLR in non-dialysis patients with ESRD remains unclear.

Methods

Among 611 non-dialysis patients with ESRD in The First Affiliated Hospital of University of South China (2012–2018), we compared NLR and PLR in patients with high-sensitivity C-reactive protein (hs-CRP) levels of ≤3 mg/L vs. > 3 mg/L. Correlation of NLR and PLR to hs-CRP, PCT, ferritin were analyzed. Receiver operating characteristics (ROC) analysis was used for estimating sensitivity and specificity of NLR and PLR.

Results

NLR was higher in the patients with high hs-CRP levels (> 3 mg/L), compared to patients with low hs-CRP levels (≤ 3 mg/L) [5.74 (3.54–9.01) vs. 3.96 (2.86–5.85), p < 0.0001]. Additionally, PLR was higher in high hs-CRP group than in low group [175.28 (116.67–252.26) vs. 140.65 (110.51–235.17), p = 0.022]. In the current study, NLR and PLR were both positively correlated with hs-CRP (rs = 0.377, p = 0.000 for NLR; rs = 0.161, p = 0.001 for PLR), PCT, leukocytes, neutrophils, platelets, and age. NLR or PLR with a cut-off value of 5.07 or 163.80 indicated sensitivity and specificity were 65.67 and 66.37% (AUC = 0.69) or 57.21 and 57.52% (AUC = 0.55), respectively.

Conclusions

NLR or PLR was positively correlated with hs-CRP in non-dialysis patients with ESRD. NLR might be better for identifying inflammation than PLR in this population.

Peer Review reports

Background

Inflammation is involved in the process of end-stage renal disease (ESRD) mainly caused by diabetic nephropathy and chronic glomerulonephritis [1,2,3]. Our previous study and others showed that inflammatory marker is a significant predictor of intima-media thickness (IMT) progression and increased IMT had poor survival in ESRD patients [4,5,6]. It has been reported that increased IMT, as a strong predictor of cardiovascular disease and mortality, was associated with inflammation even in non-dialysis patients [5, 7]. Thus, it is important to pay attention to inflammation in ESRD as well as non-dialysis patients.

Inflammatory markers such as C-reactive protein (CRP), procalcitonin (PCT), and ferritin are widely used in ESRD [8,9,10]. However, those traditional biomarkers have their limitations. The predictive value of CRP is rather nonspecific in dissecting a cause because multiple factors contribute to the inflammation of uremia [10]. PCT, a calcitonin precursor peptide, is a sensitive and specific indicator for infection, but its measurement is costly or inaccessible [11]. Ferritin has relative low accuracy in evaluating inflammation in ESRD since ESRD patients who had received intravenous iron also show higher ferritin level [9]. Therefore, a simpler, more convenient and useful marker is desired for use in clinical practice.

Recently, neutrophil-to-lymphocyte ratio (NLR) was reported to be associated with inflammation in ESRD including both hemodialysis (HD) and peritoneal dialysis (PD) patients [11,12,13], and estimate survival in HD patients [14, 15]. Studies suggested that platelet-to-lymphocyte ratio (PLR) was linked to inflammation and could predict mortality among HD patients [11, 14]. Both NLR and PLR are inexpensive, convenient, and have been widely served as prognostic indicators in several cancers such as esophageal or prostate cancer [16, 17]. Their application for evaluating inflammation in ESRD dialysis patients has been addressed. However, the value of NLR and PLR in non-dialysis patients with ESRD (those patients are in a special transition period that ESRD patients have to live through before dialysis or a kidney transplantation) remains unclear.

Therefore, in the current study, we studied a 7-year cohort of non-dialysis ESRD patients and sought to determine the relationship of NLR and PLR with inflammation in those patients.

Methods

Study population

A total of 611 non-dialysis patients (Age: 56.91 ± 14.62 y, 61.20% for males) with ESRD, admitted to The First Affiliated Hospital of University of South China from February 2012 to June 2018, were enrolled in this cross-sectional study. They were diagnosed as ESRD for the first time and these patients were evaluated by two nephrologists before starting dialysis. Patients were excluded if they had one of the following diseases: 1) a history of major surgery and inflammatory disease within the preceding 3 month; 2) end stage liver disease; 3) metastatic malignancies; 4) malabsorption syndromes. Their data was collected before the first dialysis.

Study parameters

Data on patient demographics (age, gender), etiology of ESRD, blood biochemistry and inflammatory markers including high-sensitivity C-reactive protein (hs-CRP) (mg/L), PCT (ng/ml), and ferritin (ng/ml), complete blood count, NLR, and PLR were recorded in all patients. GFR (ml/min per 1.73 m2) = 186 × Scr-1.154 × age-0.203 × 0.742 (if female) × 1.233 (if Chinese), as described [18, 19]. Hs-CRP was set for low risk (< 1.0 mg/L), average risk (1.0–3.0 mg/L), and high risk (> 3.0 mg/L) as described before [11, 13]. In this regard, recorded data was also compared in patients with hs-CRP levels of ≤3 mg/L vs. > 3 mg/L in the present study. Correlation of NLR and PLR to age (years), serum levels of albumin (g/L), hs-CRP (mg/L), ferritin (ng/ml), PCT (ng/ml), leukocytes (109/L), neutrophils (109/L), lymphocytes (109/L), and platelets (109/L) were also studied.

Laboratory analysis

Blood samples were drawn from all the individuals using uniform techniques after an overnight fasting period. Complete blood count and all biochemical analyses including serum creatinine, serum albumin, calcium, phosphorus, parathormone and ferritin were performed by automated procedures. The serum level of hs-CRP was measured by nephelemetric method (Roche, Hitachi Cobas C system, Mannheim, Germany). NLR was calculated as ratio of neutrophil to-lymphocyte counts and similarly PLR was calculated as the ratio of the platelet-to-lymphocyte count. Both were obtained from the same blood sample. All laboratory values were measured in the laboratory of The First Affiliated Hospital of University of South China by standardized methods.

Statistical analysis

Numerical variables were tested for normal distribution with the Kolmogorov–Smirnov test. Normally distributed variables were summarized as mean (± SD) and compared using Student’s t-test. Non-normally distributed variables were summarized as medians with interquartile ranges (IQRs) and Mann–Whitney U test was conducted. Frequencies were provided for all nominal values and Fisher’s exact test was used for comparison of qualitative data. Spearman tests were used for correlation analysis. The use of NLR and PLR to accurately diagnose inflammation in ESRD patients without dialysis was evaluated by receiver operating characteristics (ROC) analysis. A sensitivity and specificity calculation for NLR and PLR was derived from the hs-CRP cut offs. P-value < 0.05 was considered as significant. All statistical analyses were carried out using SPSS 20.0 software (SPSS Inc., Chicago, IL, USA).

Results

Baseline characteristics of patients

The average age of the patients was 56.91, and 61.20% of them were males. Diabetic nephropathy (32.08%), chronic glomerulonephritis (29.30%), and hypertensive nephropathy (16.53%) were the leading etiological factors during the development of ESRD. Data on laboratory findings and inflammatory markers are presented in Table 1.

Table 1 Demographic and clinic characteristics and laboratory findings in non-dialysis ESRD patients

Study parameters with respect to hs-CRP groups

Of 611 patients, 218 patients had low hs-CRP levels (≤ 3 mg/L), while 393 patients had high hs-CRP levels (> 3 mg/L). When compared to patients with lower (≤ 3 mg/L) hs-CRP levels, patients with high hs-CRP levels were determined to have significantly higher values for NLR [5.74 (3.54–9.01) vs. 3.96 (2.86–5.85), p < 0.0001], PLR [175.28 (116.67–252.26) vs. 140.65 (110.51–235.17), p = 0.022], ferritin [344.30 (192.70–586.88) vs. 217.60 (100.75–376.80) ng/ml, p < 0.0001], and PCT [0.69(0.33–2.03) vs. 0.42 (0.19–0.80), p = 0.034] (Table 2).

Table 2 Demographic and clinical characteristics and laboratory findings according to hs-CRP groups in non-dialysis ESRD patients

Correlation analysis

Bivariate correlation analysis revealed that both NLR and PLR were positively correlated with hs-CRP (rs = 0.377, p < 0.0001 for NLR and rs = 0.161, p < 0.0001 for PLR) and PCT (rs = 0.285, p < 0.0001 for NLR; rs = 0.158, p = 0.037 for PLR). NLR was statistically positively correlated with ferritin (rs = 0.140, p = 0.003), while PLR has no relationship with ferritin (rs = − 0.039, p = 0.413) (Table 3). The relationships of NLR and PLR to hs-CRP are displayed Fig. 1 and Table 4. The optimal cut-off value of NLR was 5.07 and the cut-off value of PLR was 163.80. The sensitivity and specificity were 65.67 and 66.37% for NLR, while were 57.21, 57.52% for PLR, respectively. Positive and negative likelihood ratios were 1.95 and 0.52 for NLR, while 1.35 and 0.74 for PLR, respectively.

Table 3 Bivariate correlation analysis of NLR and PLR to other parameters in non-dialysis ESRD patients
Fig. 1
figure1

Correlation of (a) NLR and (b) PLR to hs-CRP in non-dialysis ESRD patients. NLR = Neutrophil-to-lymphocyte ratio; PLR = platelet-to-lymphocyte ratio; hs-CRP = high sensitivity C-reactive protein; ESRD = end-stage renal disease

Table 4 The relationships of NLR and PLR to hs-CRP in non-dialysis ESRD patients

ROC analysis of the relationship between NLR, PLR, and hs-CRP

Figure 2 illustrates ROC curve which indicated poor sensitivity and specificity of PLR (Fig. 2). However, ROC curve of NLR (AUC = 0.69) showed significantly (p < 0.0001) larger area than PLR (AUC = 0.55) (Table 4).

Fig. 2
figure2

ROC analysis of the relationship among NLR, PLR and hs-CRP in non-dialysis ESRD patients. NLR = Neutrophil-to-lymphocyte ratio; PLR = platelet-to-lymphocyte ratio; hs-CRP = high sensitivity C-reactive protein; ESRD = end-stage renal disease

Discussion

Our findings in a cohort of non-dialysis patients with ESRD first revealed that higher (> 3 mg/L) hs-CRP levels were carrying with higher values for NLR and PLR in patients. Moreover, patients with higher hs-CRP levels tended to have significantly higher values for PCT, ferritin, leukocytes and neutrophils. Importantly, we explored that both NLR and PLR were positively correlated with hs-CRP and PCT.

Our analysis showed that higher values for NLR and PLR in high (> 3 mg/L) hs-CRP level group than those in low (≤ 3 mg/L) level group in non-dialysis ESRD patients, is consistent with the result in HD patients [11]. Similar to hs-CRP, PCT and ferritin are also inflammatory markers [8, 9]. Thus, it is reasonable to have the result that high hs-CRP level group has significantly higher values of PCT and ferritin compared to low hs-CRP level group in our current study. Additionally, we found that high hs-CRP level group had significantly higher values of leukocytes and neutrophils when compared to low hs-CRP level group. Our previous reports that CKD patient had increased level of activated leukocytes and neutrophils may partly explain this since inflammation can lead to activation and up-regulation of those cells [20,21,22].

Surprisingly, we found that non-dialysis ESRD patients had relatively lower median levels of hs-CRP (6.87 mg/L) than those (16.8 mg/L) in HD patients, but higher median levels of NLR (4.48) and PLR (154.80) in comparison to those (NLR = 3.4; PLR = 139) in HD patients respectively [11]. The trends of NLR, PLR, and hs-CRP are not parallel in ESRD patients without dialysis and HD patients. Uremia, endogenous factors as well as the dialysis procedure itself may be responsible for the high prevalence of inflammation and high level of hs-CRP in HD patients [23, 24]. It has been reported that NLR was found negatively correlated with glomerular filtration rate (GFR) and positively correlated CKD stage [25,26,27]. Therefore, non-dialysis ESRD patients from rural district with kidney disease in more advanced stage may account for the high level of NLR and PLR in our result [28].

NLR and PLR have previously been reported as inflammatory markers for patients with ESRD. One study demonstrated that NLR was positively correlated with tumor necrosis factor-α (TNF-α) in 61 ESRD patients receiving PD or HD for ≥6 months [12]. The study showed that the NLR was significantly higher in PD patients than HD patients. Another study compared NLR and PLR in 62 ESRD patients also receiving PD or HD for ≥6 months [13]. The study showed that ESRD patients with PLR ≥ 140 had significantly higher NLR, IL-6, and TNF-α levels when compared to patients with PLR < 139. The study also showed that PLR was found to be superior to NLR in terms of inflammation in ESRD patients. A recent study enrolled 100 ESRD patients on maintenance HD for ≥3 months [11]. The study revealed that the correlation relationships between the NLR or PLR and hs-CRP were statistically robust. In the present study, we recruited 611 non-dialysis patients with ESRD in a cross-sectional study. NLR and PLR were positively correlated with hs-CRP in non-dialysis ESRD patients, in line with other studies in PD or HD patients [11,12,13]. As to our knowledge, this is the first report about NLR and PLR in evaluation of inflammation in non-dialysis patients with ESRD. In addition, a strength of our study is that we included a wider range of patients.

We found that high hs-CRP level group was determined to have significantly higher values for ferritin positively correlated with NLR in non-dialysis ESRD patients, while the published papers suggested that there is no difference of ferritin value between high and low hs-CRP groups and no relationship between NLR and ferritin in HD patients [11]. Our data was different from previous reports. This may be attributed to commonly receiving intravenous iron to treat anemia in HD patients, while non-dialysis ESRD patients mostly receive oral iron poorly absorbed in advanced CKD, especially non-dialysis ESRD, leading to high levels of ferritin in HD patients and making the effect on the analysis in the population [11, 29,30,31,32]. Although PCT and TNF-α have both been shown to play a central role in the vicious circle of inflammation, PCT instead of TNF-α was analyzed statistically positively correlated with NLR or PLR in ESRD patients (11). One explanation is that PCT could serve as a better inflammatory marker than TNF-α in ESRD patients. This is supported by the reports that PCT level is more valuable indicator than TNF-α for predicting severity of acute pancreatitis, bacterial infection after bronchoscopy or in neutropenic febrile children with acute lymphoblastic leukemia [33,34,35].

NLR has proved to be a better marker than PLR or WBC as a predictor of survival in HD patients [14, 15]. Retrospectively, Catabay et al. compared the mortality predictability of NLR and PLR among 108,548 incident HD patients [14]. The authors found high NLR, but not PLR, in incident HD patients predicted mortality, especially in the short-term period. In another study, Ouellet et al. evaluated NLR as a predictor of survival in 5782 incident HD patients [15]. NLR is superior to total WBC count for prediction of all-cause mortality in incident and prevalent HD patients and was identifies as a novel and robust predictor of all-cause mortality in those patients. Moreover, NLR was demonstrated deterioration in renal function and assessed as a predictor of worsening renal function in CKD patients [25,26,27]. In the current study, our results elucidated that NLR or PLR was statistically correlated with hs-CRP in non-dialysis ESRD patients. However, it should also be noted that, the AUC for the ROC relationships was not enough to draw a conclusion that NLR or PLR was good substitute for hs-CRP. Taken together, NLR or PLR may be potential mixed markers of inflammation, renal function and mortality in CKD patients. In this regard, further study should be needed to validate the mixed role in CKD patients.

The present study has some limitations. First, our study is a single-center research. Second, the analyses were based on a single measurement of laboratory parameters that may not reflect the relation over time. Third, multivariable adjustment was not conducted (such as diabetes control) due to insufficient data. Finally, we mainly focused on hs-CRP, and its comparison to other inflammatory markers including albumin, IL-6, and TNF-α was limited. Thus, multi-center well-designed study is required to further clear relationship between inflammation and NLR or PLR, and whether the use of these ratios contributes clinically in non-dialysis ESRD patients.

Conclusion

We first reported that NLR or PLR was positively correlated with hs-CRP in non-dialysis patients with ESRD and NLR might be better in identifying inflammation than PLR in this population.

Availability of data and materials

The datasets used and/or analyzed during the current study available from the corresponding author on reasonable request.

Abbreviations

ESRD:

End-stage renal disease

CKD:

Chronic kidney disease

HD :

Hemodialysis

CRP:

C-reactive protein

PCT:

Procalcitonin

NLR:

Neutrophil-to-lymphocyte ratio

PD:

Peritoneal dialysis

PLR:

Platelet-to-lymphocyte ratio

hs-CRP:

High-sensitivity C-reactive protein

WBCs:

White blood cells

ROC:

Receiver operating characteristics

GN:

Glomerulonephritis

GFR:

Glomerular filtration rate

TNF-α:

Tumor necrosis factor-α

References

  1. 1.

    Cobo G, Lindholm B, Stenvinkel P. Chronic inflammation in end-stage renal disease and dialysis. Nephrol Dial Transplant. 2018;33:iii35–40. https://doi.org/10.1093/ndt/gfy175.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  2. 2.

    Wada J, Makino H. Inflammation and the pathogenesis of diabetic nephropathy. Clin Sci (Lond). 2013;124:139–52. https://doi.org/10.1042/CS20120198.

    CAS  Article  Google Scholar 

  3. 3.

    Gao JR, Qin XJ, Jiang H, Wang T, Song JM, Xu SZ. Screening and functional analysis of differentially expressed genes in chronic glomerulonephritis by whole genome microarray. Gene. 2016;589:72–80. https://doi.org/10.1016/j.gene.2016.05.031.

    CAS  Article  PubMed  Google Scholar 

  4. 4.

    Boaz M, Chernin G, Schwartz I, Katzir Z, Schwartz D, Agbaria A, Gal-Oz A, Weinstein T. C-reactive protein and carotid and femoral intima media thickness: predicting inflammation. Clin Nephrol. 2013;80:449–55. https://doi.org/10.5414/CN108067.

    CAS  Article  PubMed  Google Scholar 

  5. 5.

    Lestariningsih L, Hardisaputro S, Nurani A, Santosa D, Santoso G. High sensitivity C-reactive protein as a predictive of intima-media thickness in patients with end-stage renal disease on regular hemodialysis. Int J Gen Med. 2019;12:219–24. https://doi.org/10.2147/IJGM.S205506.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  6. 6.

    He Z, Cui L, Ma C, Yan H, Ma T, Hao L. Effects of lowering dialysate calcium concentration on carotid intima-media thickness and aortic stiffness in patients undergoing maintenance hemodialysis: a prospective study. Blood Purif. 2016;42:337–46.

    CAS  Article  Google Scholar 

  7. 7.

    Lemos MM, Jancikic AD, Sanches FM, Christofalo DM, Ajzen SA, Carvalho AB, Draibe SA, Canziani ME. Intima-media thickness is associated with inflammation and traditional cardiovascular risk factors in non-dialysis-dependent patients with chronic kidney disease. Nephron Clin Pract. 2010;115:c189–94. https://doi.org/10.1159/000313033.

    CAS  Article  PubMed  Google Scholar 

  8. 8.

    Demir NA, Sumer S, Celik G, Afsar RE, Demir LS, Ural O. How should procalcitonin and C-reactive protein levels be interpreted in haemodialysis patients? Intern Med J. 2018;48:1222–8. https://doi.org/10.1111/imj.13952.

    CAS  Article  PubMed  Google Scholar 

  9. 9.

    Jairam A, Das R, Aggarwal PK, Kohli HS, Gupta KL, Sakhuja V, Jha V. Iron status, inflammation and hepcidin in ESRD patients: the confounding role of intravenous iron therapy. Indian J Nephrol. 2010;20:125–31. https://doi.org/10.4103/0971-4065.70840.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  10. 10.

    Wanner C, Drechsler C, Krane V. C-reactive protein and uremia. Semin Dial. 2009;22:438–41. https://doi.org/10.1111/j.1525-139X.2009.00596.x.

    Article  PubMed  Google Scholar 

  11. 11.

    Ahbap E, Sakaci T, Kara E, Sahutoglu T, Koc Y, Basturk T, Sevinc M, Akgol C, Kayalar AO, Ucar ZA, et al. Neutrophil-to-lymphocyte ratio and platelet-tolymphocyte ratioin evaluation of inflammation in end-stage renal disease. Clin Nephrol. 2016;85:199–208. https://doi.org/10.5414/CN108584.

    CAS  Article  PubMed  Google Scholar 

  12. 12.

    Turkmen K, Guney I, Yerlikaya FH, Tonbul HZ. The relationship between neutrophil-to-lymphocyte ratio and inflammation in end-stage renal disease patients. Ren Fail. 2012;34:155–9. https://doi.org/10.3109/0886022X.2011.641514.

    CAS  Article  PubMed  Google Scholar 

  13. 13.

    Turkmen K, Erdur FM, Ozcicek F, Ozcicek A, Akbas EM, Ozbicer A, Demirtas L, Turk S, Tonbul HZ. Platelet-to-lymphocyte ratio better predicts inflammation than neutrophil-to-lymphocyte ratio in end-stage renal disease patients. Hemodial Int. 2013;17:391–6. https://doi.org/10.1111/hdi.12040.

    Article  PubMed  Google Scholar 

  14. 14.

    Catabay C, Obi Y, Streja E, Park C, Rhee CM, Kovesdy CP, Hamano T, Kalantar-Zadeh K. Lymphocyte cell ratios and mortality among incident hemodialysis patients. Am J Nephrol. 2017;46:408–16. https://doi.org/10.1159/000484177.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  15. 15.

    Ouellet G, Malhotra R, Penne EL, Usvya L, Levin NW, Kotanko P. Neutrophil-lymphocyte ratio as a novel predictor of survival in chronic hemodialysis patients. Clin Nephrol. 2016;85:191–8. https://doi.org/10.5414/CN108745.

    CAS  Article  PubMed  Google Scholar 

  16. 16.

    Yodying H, Matsuda A, Miyashita M, Matsumoto S, Sakurazawa N, Yamada M, Uchida E. Prognostic significance of neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio in oncologic outcomes of esophageal Cancer: a systematic review and meta-analysis. Ann Surg Oncol. 2016;23:646–54. https://doi.org/10.1245/s10434-015-4869-5.

    Article  PubMed  Google Scholar 

  17. 17.

    Guo J, Fang J, Huang X, Liu Y, Yuan Y, Zhang X, Zou C, Xiao K, Wang J. Prognostic role of neutrophil to lymphocyte ratio and platelet to lymphocyte ratio in prostate cancer: a meta-analysis of results from multivariate analysis. Int J Surg. 2018;60:216–23. https://doi.org/10.1016/j.ijsu.2018.11.020.

    Article  PubMed  Google Scholar 

  18. 18.

    Ma YC, Zuo L, Chen JH, Luo Q, Yu XQ, Li Y, Xu JS, Huang SM, Wang LN, Huang W, et al. Modified glomerular filtration rate estimating equation for Chinese patients with chronic kidney disease. J Am Soc Nephrol. 2006;17:2937–44.

    Article  Google Scholar 

  19. 19.

    Huang S, Wu X. Clinical application of full age spectrum formula based on serum creatinine in patients with chronic kidney disease. Zhonghua Wei Zhong Bing Ji Jiu Yi Xue. 2018;30:877–81. https://doi.org/10.3760/cma.j.issn.2095-4352.2018.09.011.

    Article  PubMed  Google Scholar 

  20. 20.

    He Z, Zhang Y, Cao M, Ma R, Meng H, Yao Z, Zhao L, Liu Y, Wu X, Deng R, et al. Increased phosphatidylserine-exposing microparticles and their originating cells are associated with the coagulation process in patients with IgA nephropathy. Nephrol Dial Transplant. 2016;31:747–59. https://doi.org/10.1093/ndt/gfv403.

    CAS  Article  PubMed  Google Scholar 

  21. 21.

    Zhang Y, Meng H, Ma R, He Z, Wu X, Cao M, Yao Z, Zhao L, Li T, Deng R, et al. Circulating microparticles, blood cells, and endothelium induce procoagulant activity in sepsis through phosphatidylsering exposure. Shock. 2016;45:299–307. https://doi.org/10.1097/SHK.0000000000000509.

    CAS  Article  PubMed  Google Scholar 

  22. 22.

    Johnson BL 3rd, Midura EF, Prakash PS, Rice TC, Kunz N, Kalies K, Caldwell CC. Neutrophil derived microparticles increase mortality and the counter-inflammatory response in a murine model of sepsis. Biochim Biophys Acta Mol basis Dis. 1863;2017:2554–63. https://doi.org/10.1016/j.bbadis.2017.01.012.

    CAS  Article  Google Scholar 

  23. 23.

    Hsu HJ, Yen CH, Wu IW, Hsu KH, Chen CK, Sun CY, Chou CC, Chen CY, Tsai CJ, Wu MS, et al. The association of uremic toxins and inflammation in hemodialysis patients. PLoS One. 2014;9:e102691. https://doi.org/10.1371/journal.pone.0102691.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  24. 24.

    Li G, Ma H, Yin Y, Wang J. RP, IL-2 and TNF-α level in patients with uremia receiving hemodialysis. Mol Med Rep. 2018;17:3350–5. https://doi.org/10.3892/mmr.2017.8197.

    CAS  Article  PubMed  Google Scholar 

  25. 25.

    Tonyali S, Ceylan C, Yahsi S, Karakan MS. Does neutrophil to lymphocyte ratio demonstrate deterioration in renal function? Ren Fail. 2018;40:209–12. https://doi.org/10.1080/0886022X.2018.1455590.

    Article  PubMed  PubMed Central  Google Scholar 

  26. 26.

    Azab B, Daoud J, Naeem FB, Nasr R, Ross J, Ghimire P, Siddiqui A, Azzi N, Rihana N, Abdallah M, et al. Neutrophil-to-lymphocyte ratio as a predictor of worsening renal function in diabetic patients (3-year follow-up study). Ren Fail. 2012;34:571–6. https://doi.org/10.3109/0886022X.2012.668741.

    CAS  Article  PubMed  Google Scholar 

  27. 27.

    Tsai SF, Wu MJ, Wen MC, Chen CH. Serologic and Histologic Predictors of Long-Term Renal Outcome in Biopsy-Confirmed IgA Nephropathy (Haas Classification): An Observational Study. J Clin Med. 2019;8:E848. https://doi.org/10.3390/jcm8060848.

    CAS  Article  PubMed  Google Scholar 

  28. 28.

    Zhang W, Gong Z, Peng X, Tang S, Bi M, Huang W. Clinical characteristics and outcomes of rural patients with ESRD in Guangxi, China: one dialysis center experience. Int Urol Nephrol. 2010;42:195–204. https://doi.org/10.1007/s11255-009-9609-y.

    Article  PubMed  Google Scholar 

  29. 29.

    Kshirsagar AV, Li X. Long-term risks of intravenous Iron in end-stage renal disease patients. Adv Chronic Kidney Dis. 2019;26:292–7. https://doi.org/10.1053/j.ackd.2019.05.001.

    Article  PubMed  Google Scholar 

  30. 30.

    Rostoker G, Vaziri ND. Iatrogenic iron overload and its potential consequences in patients on hemodialysis. Presse Med. 2017;46:e312–28. https://doi.org/10.1016/j.lpm.2017.10.014.

    Article  PubMed  Google Scholar 

  31. 31.

    Rostoker G, Vaziri ND, Fishbane S. Iatrogenic Iron overload in Dialysis patients at the beginning of the 21st century. Drugs. 2016;76:741–57. https://doi.org/10.1007/s40265-016-0569-0.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  32. 32.

    Macdougall IC. Iron treatment strategies in nondialysis CKD. Semin Nephrol. 2016;36:99–104. https://doi.org/10.1016/j.semnephrol.2016.02.003.

    CAS  Article  PubMed  Google Scholar 

  33. 33.

    Staubli SM, Oertli D, Nebiker CA. Laboratory markers predicting severity of acute pancreatitis. Crit Rev Clin Lab Sci. 2015;52:273–83. https://doi.org/10.3109/10408363.2015.1051659.

    CAS  Article  PubMed  Google Scholar 

  34. 34.

    Farrokhpour M, Kiani A, Mortaz E, Taghavi K, Farahbod AM, Fakharian A, Kazempour-Dizaji M, Abedini A. Procalcitonin and Proinflammatory cytokines in early diagnosis of bacterial infections after bronchoscopy. Open Access Maced J Med Sci. 2019;7:913–9. https://doi.org/10.3889/oamjms.2019.208.

    Article  PubMed  PubMed Central  Google Scholar 

  35. 35.

    Hatzistilianou M, Rekliti A, Athanassiadou F, Catriu D. Procalcitonin as an early marker of bacterial infection in neutropenic febrile children with acute lymphoblastic leukemia. Inflamm Res. 2010;59:339–47. https://doi.org/10.1007/s00011-009-0100-0.

    CAS  Article  PubMed  Google Scholar 

Download references

Acknowledgements

We are grateful to Jianglong Li, Ph. D, M.D. for his constructive comments in improving the language, grammar, and readability of the paper.

Funding

This research was supported by the National Natural Science Foundation of China (81900678) and the Natural Science Foundation of Hunan Province (2019JJ50555). The funding body is used to pay for the labor of reviewing data on patient demographics (age, gender), etiology of ESRD, blood biochemistry and inflammatory markers including high-sensitivity C-reactive protein (hs-CRP), PCT, ferritin, and complete blood count.

Author information

Affiliations

Authors

Contributions

PL1 (Peiyuan Li): Statistics analysis and writing the manuscript. CX: Data collection. PL2 (Peng Liu): Data collection. ZP: Data collection. JW: Data collection. HH: revising the manuscript. ZH: Study design, revising the manuscript and final approval of the versions to be published. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Zhangxiu He.

Ethics declarations

Ethics approval and consent to participate

Ethics approval and consent to participate.

The study was approved by the Ethics Committee of The First Affiliated Hospital of University of South China. As this study was a observational cohort study without any intervention, informed consent was exempted by the Ethics Committee.

Consent for publication

Not applicable.

Competing interests

There is no conflict of interest to report here.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Li, P., Xia, C., Liu, P. et al. Neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio in evaluation of inflammation in non-dialysis patients with end-stage renal disease (ESRD). BMC Nephrol 21, 511 (2020). https://doi.org/10.1186/s12882-020-02174-0

Download citation

Keywords

  • Neutrophil-to-lymphocyte ratio (NLR)
  • Platelet-to-lymphocyte ratio (PLR)
  • Inflammation
  • Non-dialysis patients with end-stage renal disease (ESRD)