INTRODUCTION:

Chronic kidney disease (CKD) refers to the progressive and irreversible loss of kidney function¹. It is a global health problem, with an increasing prevalence and incidence rates². It leads to end-stage renal disease (ESRD), the last stage of CKD, where there is a need for dialysis or renal transplantation to maintain life².

CKD patients have higher rates of mortality and morbidity compared to general population³. Cardiovascular disease (CVD) is considered the main cause of death in patients with CKD⁴, with approximately 50% of all-cause mortality in patients with ESRD⁵. There are traditional risk factors such as diabetes mellitus (DM), hypertension (HT), dyslipidemia, and obesity⁶. However, they cannot explain this high rate of cardiovascular mortality in CKD patients. Therefore, many trials have proposed that non-traditional risk factors such as chronic inflammation, anemia, endothelial dysfunction, and coronary artery calcification (CAC) may be more important for the development of atherosclerosis in these patients⁷. Among these, it seems that inﬂammatory processes play a crucial role in development and progression of CKD and its cardiovascular complications^8,9. It is predicted that early and specific detection of inflammation might improve the quality of life of these patients and decrease mortality and morbidity rates¹⁰. Many patients with CKD have elevated serum levels of various inflammatory mediators including C-reactive protein (CRP), interleukin-6 (IL-6) and tumor necrosis factor-α (TNF-α)¹¹. Various markers have been recognized to measure and monitor systemic inflammation, such as CRP, IL-1, IL-6, erythrocyte sedimentation rate (ESR), ferritin and TNF-a. However, in the current global socioeconomic status, it is important to find out cost-eﬀective biological markers¹². High sensitivity C-reactive protein (hs-CRP) is a biomarker of subclinical inflammation and an independent predictor for cardiovascular risk evaluation^13,14. Recently, white blood cell (WBC) counts and their subtypes are considered as sensitive indicator of inflammation, which can be done easily in laboratory¹⁵. In this respect, neutrophil to lymphocyte ratio (NLR) and platelet to lymphocyte ratio (PLR) have been proposed as novel inexpensive, convenient and readily available markers of systemic inflammation¹⁰. These ratios have been studied in cancers^16,18, heart diseases^19,20 and diabetes^21,22. Additionally, previous study shown that the NLR predicts the progression rate of stage 4 chronic kidney disease to dialysis²³. Other studies reported that PLR was related to inﬂammation and could predict mortality among hemodialysis (HD) patients^24,25. There are few studies about NLR or PLR and their relationship with inflammation in CKD. The present study aimed to evaluate the association of NLR and PLR with hs-CRP levels, as a gold-standard marker for the detection of inﬂammation, in a group of Syrian CKD patients. Thus, the possibility to use NLR or PLR as an inflammatory indicator instead of hs-CRP.

MATERIALS AND METHODS:

This study is a cross sectional study that included 100 CKD patients, 50.4±15 (mean±SD) years of age; 54 males; seen at the department of kidney disease at Tishreen University Hospital in Lattakia from July 2020 to July 2021. These patients were classified into three groups according to estimated glomerular filtration rate (eGFR), CKD stage 3 (eGFR: 30-59ml/min/1.73m², n=24), CKD stage 4 (eGFR: 15-29ml/min/1.73m², n=26) and CKD stage 5 (eGFR: <15ml/min/1.73m² and on hemodialysis (HD), n=50)²⁶. Twenty-two subjects, 45.1±20 years of age; among them 10 males, without a medical history of kidney disease, and with eGFR> 60 ml/min/1.73m² and normal serum creatinine (<1.3mg/dl for male and 1.1mg/dl for female), served as control group. We categorized CKD patients according to the presence of subclinical inﬂammation based on the hs-CRP cut off point of 3mg/l, patients with no inﬂammation were those who obtained a result ≤ 3 mg/l^25,27.

Exclusion Criteria included fever or acute infectious diseases, a history of surgeries within the 3 months prior to the beginning of data collection, pregnant women, autoimmune diseases, chronic liver disease and lung diseases, malignancies, patients with amputations, with only one kidney, patients using immunosuppressive treatment, steroid hormones (all types), heart failure. After analysis, patients with hs-CRP>10mg/l, white blood cell (WBC) count> 10x10³μ/l were also excluded.

Participants’ data (age, sex), body mass index (BMI) (kg/m²), comorbidities diseases were obtained. BMI was calculated using the equation: BMI= weight/(height)². The estimated GFR (eGFR) was calculated using Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) formula²⁸. Our study was reviewed by Tishreen University Board, a written consent was obtained from all subjects.

Blood sampling and laboratory measurements:

A peripheral venous blood sample was drawn from each participant in the morning. Blood samples were collected on ethylenediaminetetraacetic acid (EDTA) tubes for complete blood count (CBC) test, and on lithium heparin tubes for chemical assays. Blood was drawn before sessions of hemodialysis for CKD stage 5 patients. All laboratory measurements were performed in the central laboratory at Tishreen University Hospital in Lattakia. Heparinized plasma creatinine and urea concentrations were measured using automated biochemical analyzer (Mindray BS-380) with the commercially available kits. CBC analysis was done using Sysmex XT-1800i analyzer. NLR and PLR were calculated by dividing absolute neutrophil to absolute lymphocyte count, and absolute platelet to absolute lymphocyte count, respectively. Both were obtained from the same blood sample. The serum levels of hs-CRP were measured by an immunoturbidimetry assay kit (Biosystem®).

Statistical analysis:

Statistical analyses were performed using SPSS statistical software (version 25). All results were described as mean±standard deviation (SD) for continuous variables and percentages for categorical variables. Chi-square and ANOVA tests were used to assess the relationship between variables. Pearson’s correlation coefficient (r) was used for continuous data. Receiver operating characteristic (ROC) curve analysis was performed to determine the optimum cutoﬀ points of NLR and PLR to predict inflammation. The area under the curve (AUC) was used to denote markers’ performance and comparison. P value <0.05 was considered statistically significant.

Demographic and laboratory characteristics of the participants are shown in Table 1. There were no significant differences between CKD groups and controls with respect to age, BMI and gender. Among CKD subjects, 60(49%) patients had diabetic mellitus and 57(47%) patients had hypertension, without significant difference in percentages of those patients among the 3 stages of CKD (p>0.05) for both variables. The mean creatinine and urea concentration were higher in all CKD groups compared to the control subjects respectively with a significant difference among groups (p<0.001, for both). There were significant differences in WBC, neutrophils and lymphocytes count among groups (p<0.05). No significant difference was found in platelets count between groups. NLR as well as PLR and hs-CRP levels were significantly higher in all CKD groups compared to control subjects (Table 1, p<0.05, for all). Although hs-CRP levels were higher in patients with stage 4 compared to other CKD groups, the difference fell out of statistical significance. Similarly, there were no differences regarding NLR and PLR levels among CKD groups (Table 1) (for all, p>0.05).

Study parameters with respect to hs-CRP groups:

CKD patients were categorized into two groups according to the presence of subclinical chronic inﬂammation (63%) or absence of inﬂammation (37%), depending on the hs-CRP cut off point of 3 mg/l. We considered that hs-CRP>3mg/l indicates the presence of subclinical inflammatory state, despite absence of any symptoms of inflammation, and hs-CRP≤3 mg/l indicates the absence of inflammation (Table 2). The mean values of hs-CRP were 1.66mg/l for the group without inﬂammation and 6.4mg/l for the group with subclinical inﬂammation (p<0.001). WBC and neutrophils count showed signiﬁcant diﬀerences between the groups (p<0.05), while lymphocytes and platelets count did not (p>0.05). NLR and PLR showed mean levels of 3.09 (1.24–5.1) and 153.88 (104.34–283.33) in CKD patients, respectively, with a statistically signiﬁcant diﬀerence between groups (p<0.001, for both). Table 2 shows the results of the laboratory tests and their statistical analysis. Moreover, a statistically significant positive correlation was found between both NLR and PLR with hs-CRP (p<0.001, r=0.50 for NLR and p<0.001, r= 0.43 for PLR), as shown in Figure 1.

Table 2. Demographic and laboratory findings according to hs-CRP groups in CKD patients (n=100)

Parameters	hs-CRP ≤ 3 mg/l (n=37)	hs-CRP>3mg/l (n=63)	P -value
Age (years)	46.81 ± 16.1	52.44 ± 13.85	0.07
BMI (kg/m²)	23.1 ± 3.6	23.6 ± 3.3	0.54
NLR	2.62 ± 0.66	3.36 ± 0.73	<0.001
PLR	135.75 ± 24	164.53 ± 46.26	<0.001
WBC count (10⁹/l)	6.11 ± 1.5	6.9 ± 1.97	0.04
Neutrophils count (10⁹/l(	4.1 ± 1.1	4.9 ± 1.6	0.01
Lymphocytes count (10⁹/l)	1.64 ± 0.46	1.5 ± 0.44	0.14
Platelets count (10⁹/l)	218.65 ± 56.1	233.94 ± 48.54	0.16

Figure 1. Correlation of NLR (A) and PLR (B) with hs-CRP in CKD patients.

The relationship between NLR or PLR and other variables in CKD patients :

We did not detect any association between NLR levels and age or BMI. Similarly, PLR levels did not correlate with age or BMI. In addition, we found that both NLR and PLR levels were not influenced by sex. Using independent t-student test, there was no significant difference in NLR means between males and females (p>0.05). Similarly, no significant difference was found in PLR levels between males and females (p>0.05). Furthermore, there were no statistically significant differences in the mean levels of NLR neither between diabetic and non-diabetic CKD patients (p>0.05), nor between hypertensive and non-hypertensive CKD patients (p>0.05). Similar results were obtained for PLR (Table 3).

Table 3. Relationship between NLR or PLR and some variables in CKD patients (n=100)

Characteristics	NLR		PLR
	r	P -value	r	P -value
Age (years)	0.1	0.31	0.13	0.21
BMI (kg/m²)	-0.04	0.67	0.06	0.56
	Mean ± SD	P -value	Mean ± SD	P -value
Males Females	2.9±0.81 3.2±0.78	0.2	157±43 150±40.3	0.42
Diabetic patients Non-diabetic patients	3±0.8 3.1±0.64	0.71	157.8±41.6 147.9±41.8	0.25
Hypertensive patients Non-hypertensive patients	2.99±0.8 3.15±0.6	0.37	158.8±42.6 147.3±40	0.17

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

The analysis of the ROC curve showed that the best cut oﬀ point for NLR to detect subclinical inflammation in CKD patients was greater than or equal to 3.06, with a sensitivity of 70% and a speciﬁcity of 81.1%, positive predictive value (PPV) was 86.3% and negative predictive value (NPV) was 61.2%. The best cutoﬀ point for PLR was greater than or equal to 144.78, with 59% sensitivity and 73% speciﬁcity, PPV was 78.7% and NPV was 50.9%. The diﬀerence in the AUC between NLR and PLR was not statistically signiﬁcant (AUC: 0.77 vs. AUC: 0.70, respectively; p= 0.19) (Figure 2).

Figure 2. Analysis of the ROC curve for different cutoﬀ points for NLR and PLR in patients with CKD using the ROC curve and AUC test.

DISCUSSION:

NLR provides information on both adaptive immune response (mediated by lymphocytes) and innate immune response (mediated by neutrophils). It is more stable for measurement than total and differential white blood cell (WBC) counts and less affected by physiological and pathological status²⁹. For PLR, high platelet counts are associated with increased inflammation, where platelets release proinflammatory cytokines, thromboxane and other mediators^30,31. NLR and PLR are considered as a novel biomarker for assessing inflammation. They have been getting widely used in patients with various diseases¹⁰ and can be calculated routinely without additional cost from the complete blood count (CBC)²⁹. However, there are a few studies concerning these parameters for CKD. The main purpose of this study was to investigate the possibility to use NLR and PLR as markers of inflammation compared to hs-CRP in CKD patients. Our results elucidated that NLR and PLR levels had a statistically significant positive correlation with hs-CRP.These findings provide that a simple calculation of NLR and PLR might be a surrogate marker for evaluation of inflammation in CKD patients.

This study demonstrated that inﬂammatory markers including NLR, PLR and hs-CRP were signiﬁcantly higher in CKD patients when compared to the control subjects. Increased serum levels of CRP, IL-6, and TNF-a have been reported in several studies in CKD patients¹¹. Chronic inflammation causes activation of the immune system in CKD patients and increases WBC counts and its neutrophil component associated with low levels of lymphocytes^32,33. The assessment of subclinical inflammation in CKD patients revealed that sixty-three (63%) of our patients had high hs-CRP levels (>3 mg/l) indicating the presence of inflammation, despite absence of any signs of inflammation. Our findings showed significantly higher values of NLR and PLR in high (>3mg/L) hs-CRP level group than those in low (≤ 3mg/l) group. Moreover, patients with higher hs-CRP levels tended to have significantly higher values of WBC and neutrophils. Importantly, we explored that both NLR and PLR were positively correlated with hs-CRP, despite the more strength correlation of NLR (higher r).

These results were consistent with other studies, where the study by Li et al, showed that NLR or PLR was positively correlated with hs-CRP in 611 non-dialysis patients with ESRD, and NLR could be better for identifying inflammation than PLR in this population²⁷. Ahbap et al, who worked with 100 ESRD patients on maintenance hemodialysis, found that both NLR and PLR had higher levels in patients with inﬂammation and the correlation of NLR or PLR with hs-CRP were statistically potent²⁵. In contrast, the study of Brito et al, concluded that only PLR showed a signiﬁcant positive correlation with hs-CRP in 85 CKD patients. However, the NLR and PLR values were signiﬁcantly diﬀerent between the groups with and without inﬂammation¹⁰. In their study, they excluded patients with history of dialysis, in addition to the ethnic difference between studies; these factors may influence the correlation significantly. In a similar manner, the study of Chavez Valencia et al, pointed out that PLR is correlated with CRP but no relationship was found between NLR and CRP level. However, their study included only patients on regular HD, this may explain the difference³⁴. Another study compared NLR and PLR in 62 ESRD patients receiving peritoneal dialysis (PD) or HD for more than 6 months, showed that PLR was positively correlated with NLR, IL-6, and TNF-a in this population, and PLR was found to be superior to NLR in terms of inﬂammation in ESRD patients³⁵.

Some studies focused only on NLR advantages compared to other inﬂammatory indicators. The study of Malhotra et al, found that NLR might be a surrogate marker for hs-CPR in HD patients³⁶. In the same context, Okyay et al, approved that the identifying of NLR values is an easy and low-cost laboratory test that can provide signiﬁcant information about the inﬂammatory state in CKD including predialysis and dialysis patients. NLR was positively correlated with IL-6 and hs-CRP in these patients³³. Moreover, Shaarawy et al, concluded the presence of a significant positive correlation between NLR and hs-CRP in patients on regular HD and showed that we can use NLR instead of hs-CRP as a marker of inflammation in these patients³⁷.

These results confirm that NLR and PLR can be used as potential markers of inflammation in CKD patients. These parameters have great advantages compared to other markers in the evaluation of inﬂammation. They are simple, relatively inexpensive, and universally available methods.

In our study, there were no significant difference in NLR or PLR levels between males and females, hypertensive and non-hypertensive, or diabetic and non-diabetic CKD patients. In addition, NLR or PLR levels weren’t correlated with age or BMI. Eventually, these factors did not represent confounding factors that may influence the correlation between NLR or PLR with hs-CRP in CKD patients.

The present study is one of few studies that determined cut off points for NLR and PLR as a predictor of inflammation with calculation of their sensitivity and specificity. We found that ideal cutoff points for NLR and PLR were greater than or equal 3.06 and 144.78, respectively. The diﬀerence of performance between the parameters was not signiﬁcant in our study, the AUC for the ROC relationships was not different enough to make a conclusion that NLR or PLR was better substitute for hs-CRP. Taken together, NLR and PLR may be possible mixed markers of inflammation.

Different cut off points were found in previous studies. Li et al, found the best cutoff points for NLR and PLR to be 5.07 and 163.8, respectively, with sensitivity and specificity of 65.67% and 66.37% for NLR, and 57.21% and 57.52% for PLR in non-dialysis patients with ESRD²⁷. Ahbap et al, who also analyzed HD patients, reported that the ideal cutoﬀ points for NLR was 2.82 with sensitivity of 65.7% and specificity of 63.3%²⁵. Both of the studies determined the presence of inflammation to be at hs-CRP levels >3mg/l. Brito et al, found that the cutoﬀ point for NLR was 1.98, while the cutoff point of PLR was 116.07 in non-dialysis CKD, without signiﬁcant diﬀerence between the area under the NLR and PLR curve for this population¹⁰. However, their study determined inflammation state when hs-CRP >5mg/l. Furthermore, Shaarawy et al, found that the best cutoﬀ point for NLR was ≥1.54 in HD patients with 68.25% sensitivity and 54.05% specificity³⁷. They determined the presence of subclinical inflammation to be at hs-CRP ≥8.2mg/l. Differences in reference ranges of hs-CRP could explain the different cutoff points of NLR and PLR between studies.

CONCLUSION:

Our study has revealed that chronic inflammation is prevalent in CKD subjects in Latakia, Syria (63%), which emphasize the need for routine screening of inflammatory markers levels, where CRP is not routinely tested in the kidney departments. NLR and PLR are easy to calculate in laboratory, simple and done routinely. They are cost-effective tests and can be used by health care professionals as ﬁrst methods for evaluation of inﬂammation in CKD patients before applying other more expensive and invasive procedures.

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Received on 17.04.2022 Modified on 10.05.2022

Research J. Pharm. and Tech 2023; 16(1):187-192.

DOI: 10.52711/0974-360X.2023.00035

Parameters	Control (n=22)	CKD 3 (n=24)	CKD 4 (n=26)	CKD 5 (n=50)	P -value
Male, n (%)	10 (45)	13 (54)	13 (50)	28 (56)	0.86
Age (years)	45 ± 20	51.4 ± 13.4	49.9 ± 15.2	50.08 ± 15.6	0.56
BMI (kg/m²)	24.3 ± 3.15	23.6 ±3.1	24.55 ± 3.17	22.8 ± 3.49	0.12
Hypertension, n (%)	0	15 (62.5)	14 (54)	28 (56)	0.81
Diabetes, n (%)	0	15 (62.5)	14 (54)	31 (62)	0.76
Urea (mg/dl)	21.6 ± 6.56	66.73 ± 28.5	97.2 ± 38.3	114.2 ± 33.6	<0.001
Creatinine (mg/dl)	0.8 ± 0.08	1.78 ± 0.26	2.91 ± 0.37	9.4 ± 2.67	<0.001
hs-CRP (mg/l)	2.2 ± 1.8	4.5 ± 2.9	5.5 ± 2.7	4.3 ± 2.8	0.001
WBC count (10⁹/l)	5.2 ± 1.2	7.3 ±1.7	7.2 ± 2	6 ± 1.6	<0.001
Neutrophils count (10⁹/l(	3.1 ± 0.9	5±1.4	5.1 ± 1.7	4.2 ± 1.3	<0.001
Lymphocytes count (10⁹/l)	1.9 ± 0.4	1.7 ± 0.4	1.5 ± 0.3	1.4 ± 0.4	0.001
Platelets count (10⁹/l)	250 ± 51.9	232 ± 45.6	230 ± 45.6	225.5 ± 57.8	0.32
NLR	1.65 ± 0.5	3 ± 0.6	3.3 ± 0.7	2.97 ± 0.8	<0.001
PLR	133.5 ± 33.8	140.3 ± 24.3	155 ± 40	160 ± 48	0.04