Case Control Study Open Access
Copyright ©The Author(s) 2024. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Clin Cases. May 16, 2024; 12(14): 2308-2315
Published online May 16, 2024. doi: 10.12998/wjcc.v12.i14.2308
Neutrophil-to-lymphocyte ratio associated with renal function in type 2 diabetic patients
Jin-Li Gao, Department of Prevention and Health Care, Community Health Service Center of Miaohang Town, Shanghai 200443, China
Jue Shen, Li-Ping Yang, Department of Prevention and Health Care, Community Health Service Center of Songnan Town, Shanghai 200434, China
Li Liu, Kai Zhao, Xiao-Rong Pan, Ji-Ji Xu, Department of General Practice, Community Health Service Center of Songnan Town, Shanghai 200434, China
Lei Li, Department of Administrative, Community Health Service Center of Songnan Town, Shanghai 200434, China
ORCID number: Lei Li (0009-0003-9775-4625); Ji-Ji Xu (0009-0000-8384-6084).
Co-first authors: Jin-Li Gao and Jue Shen.
Co-corresponding authors: Lei Li and Ji-Ji Xu.
Author contributions: Gao JL conceived, designed, and refined the study protocol; Zhao K, Pan XR, Yang LP, and Liu L were involved in the data collection; Xu JJ and Li L analyzed the data; Gao JL and Shen J drafted the manuscript; Xu JJ and Li L revised the manuscript; all authors were involved in the critical review of the results and have contributed to, read, and approved the final manuscript. Gao JL and Shen J contributed equally to this work as co-first authors; Xu JJ and Li L contributed equally to this work as co-corresponding authors. There are three reasons for designating Xu JJ and Li L as co-corresponding authors. First, this study was a collaborative effort and both Xu JJ and Li L made equally important contributions throughout the course of the study. The designation of co-corresponding authors accurately reflects the distribution of responsibilities and burdens in terms of time and effort required to complete this study and the paper, and also recognizes and respects their equal contributions. Second, Xu JJ and Li L made great efforts to obtain research funding, which was a key factor in making the research possible. Finally, the fact that the whole research team consisted of authors from different fields with different expertise and skills also contributed to the most comprehensive and in-depth exploration of the research topic, which ultimately enriched the readers' understanding by providing different expert perspectives. In conclusion, we believe that the designation of Xu JJ and Li L as co-corresponding authors is highly appropriate, as it accurately reflects the collaborative spirit, equal contribution and diversity of our team.
Supported by Health Commission of Baoshan District, Shanghai, China, No. BSJCPP-A-04 and No. BSZK-2023-T04; and the Science and Technology Commission of Baoshan District, Shanghai, China, No. 20-E-63 and No. 21-E-34.
Institutional review board statement: This study was approved by the Ethics Committee of Community Health Service Center of Songnan Town, Baoshan District, Shanghai, China.
Informed consent statement: All study participants or their legal guardian provided informed written consent about personal and medical data collection prior to study enrolment.
Conflict-of-interest statement: All the Authors have no conflict of interest related to the manuscript.
Data sharing statement: The original anonymous dataset is available on request from the corresponding author at 13916799696@139.com.
STROBE statement: The authors have read the STROBE Statement – checklist of items, and the manuscript was prepared and revised according to the STROBE Statement – checklist of items.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Ji-Ji Xu, MBBS, Deputy Director, Department of General Practice, Community Health Service Center of Songnan Town, No. 301 Songliang Road, Baoshan District, Shanghai 200434, China. 13916799696@139.com
Received: December 28, 2023
Revised: February 14, 2024
Accepted: April 2, 2024
Published online: May 16, 2024
Processing time: 128 Days and 19.9 Hours

Abstract
BACKGROUND

Type 2 diabetes mellitus (T2DM) is a leading risk factor for the development and progression of chronic kidney disease (CKD). However, an accurate and convenient marker for early detection and appropriate management of CKD in individuals with T2DM is limited. Recent studies have demonstrated a strong correlation between the neutrophil-to-lymphocyte ratio (NLR) and CKD. Nonetheless, the predictive value of NLR for renal damage in type 2 diabetic patients remains understudied.

AIM

To investigate the relationship between NLR and renal function in T2DM patients.

METHODS

This study included 1040 adults aged 65 or older with T2DM from Shanghai's Community Health Service Center. The total number of neutrophils and lymphocytes was detected, and NLR levels were calculated. CKD was defined as an estimated glomerular filtration rate ≤ 60 mL/min/1.73 m². Participants were divided into four groups based on NLR levels. The clinical data and biochemical characteristics were compared among groups. A multivariate logistic regression model was used to analyze the association between NLR levels and CKD.

RESULTS

Significant differences were found in terms of sex, serum creatinine, blood urea nitrogen, total cholesterol, and low-density lipoprotein cholesterol among patients with T2DM in different NLR groups (P < 0.0007). T2DM patients in the highest NLR quartile had a higher prevalence of CKD (P for trend = 0.0011). Multivariate logistic regression analysis indicated that a high NLR was an independent risk factor for CKD in T2DM patients even after adjustment for important clinical and pathological parameters (P = 0.0001, odds ratio = 1.41, 95% confidence intervals: 1.18-1.68).

CONCLUSION

An elevated NLR in patients with T2DM is associated with higher prevalence of CKD, suggesting that it could be a marker for the detection and evaluation of diabetic kidney disease.

Key Words: Type 2 diabetes mellitus; Neutrophil-to-lymphocyte ratio; Chronic kidney disease; Logistic regression; Diabetes mellitus

Core Tip: In elderly type 2 diabetes mellitus (T2DM) patients, elevated neutrophil-to-lymphocyte ratio (NLR) is strongly linked to an increased risk of chronic kidney disease (CKD), uncovering NLR as a potential independent biomarker for early detection of renal damage. This finding holds significant promise for addressing the current challenge of delayed CKD diagnosis in T2DM, signifying the potential utility of NLR as a convenient and sensitive detection method for identifying CKD in diabetic patients.



INTRODUCTION

Diabetes is a prevalent metabolic disease with significant implications for global health, and type 2 diabetes mellitus (T2DM) represents the predominant form of diabetes in China, accounting for over 90% of cases[1]. T2DM is one of the leading risk factors for the development and progression of chronic kidney disease (CKD)[2]. In Asia, it is estimated that > 60% of patients with diabetes will develop kidney complications, compared with 30%-40% in Europeans despite having a similar duration of diabetes[3,4]. Furthermore, CKD in diabetic individuals is associated with increased morbidity and premature mortality, which impose a substantial economic burden on healthcare systems[5,6]. Given the continuous increase in the number of people with diabetes, early detection and appropriate management of CKD in individuals with T2DM are crucial to prevent or delay the progression of kidney disease. However, since CKD is a complex multifactorial disease and the pathogenesis of the disease remains unclear, along with limited access to medical resources and the high cost of testing in some regions, patients are hindered from obtaining routine renal function screening and timely diagnosis. Therefore, the identification of an accurate and convenient marker for promptly detecting and assessing kidney function is essential to improve patient outcomes.

Recent studies have shown that the neutrophil-to-lymphocyte ratio (NLR), an inflammatory marker, strongly correlates with acute ischemic stroke, tumors, sepsis, and CKD[7-10]. However, prior research has mostly examined hospitalized patients with more severe conditions, overlooking diabetic patients in the general population. This article mainly explored the relationship between NLR and renal function in patients with T2DM, aiming to establish a theoretical framework for evaluating the predictive value of NLR in the early detection of renal damage in T2DM patients.

MATERIALS AND METHODS
Population

This study involved 1040 adults aged 65 years old or above diagnosed with T2DM from the health examination platform of the Community Health Service Center in Songnan Town, Baoshan District, Shanghai, China from June to August 2021. The investigation focused on three medical service stations located in the community health service center and affiliated institutes of Songnan Town. The diagnosis of T2DM was in accordance with Chinese guidelines for the prevention and treatment of T2DM (2020 edition)[11], namely, a fasting plasma glucose (FPG) level ≥ 7.0 mmol/L or a previous diagnosis of T2DM and currently receiving oral medication. Participants were excluded if they had incomplete or uncertain basic information, type 1 DM, a history of hormone therapy within a year, any type of malignancy, a current acute infection, or an established hematologic disease. Oral consent was obtained from all participants, and the study was approved by the central ethics committee.

Implant procedure

Demographics (sex and age) and disease history, such as hypertension, were self-reported by all participants through comprehensive questionnaires completed by trained general practitioners and volunteers. Height and weight were measured using an electronic height scale, and body mass index (BMI) was calculated as the weight in kilograms divided by the height in meters squared. Waist and hip circumferences were measured using a soft skin caliper, and blood pressure was measured using an Omron sphygmomanometer (HBP-1120u).

For laboratory testing, the participants’ whole blood was drawn into an EDTA vacuum anticoagulant tube and mixed by inversion several times. Additionally, 6 mL of fasting venous blood was obtained in the early morning, and the supernatant was collected after centrifugation. FPG, serum creatinine (Scr), blood urea nitrogen (BUN), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglyceride (TG) levels were detected using an automatic biochemical analyzer (Hitachi 7080). The total number of neutrophils and lymphocytes were detected using a Mairui 5100 automatic hematology analyzer, and NLR levels were calculated. All blood samples were collected by the Department of Laboratory Medicine in the Community Health Service Center, Songnan Town, Baoshan District, Shanghai, China. The laboratory received quality control from the standardized protocol for blood biochemical testing from the Shanghai Centers for Disease Control and Prevention.

Outcome definition

The estimated glomerular filtration rate (eGFR), expressed in ml/min/1.73 m2, was calculated with the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation on the basis of Scr[12]. The formula was as follows: (1) if female: Scr ≤ 0.7 mg/dL, eGFR = 144 × (Scr/0.7)-0.329 × (0.993)age; Scr > 0.7 mg/dL, eGFR = 144 × (Scr/0.7)-1.209 × (0.993)age; and (2) if male: Scr ≤ 0.9 mg/dL, eGFR = 141 × (Scr/0.9)-0.411 × (0.993)age; Scr > 0.9 mg/dL, eGFR = 141 × (Scr/0.9)-1.209 × (0.993)age. CKD was defined as an eGFR of 60 mL/min/1.73 m2 or less[13].

Other definitions

(1) Hypertension was defined according to the Chinese guidelines for the prevention and treatment of hypertension (2018 Revision)[14], with systolic blood pressure (SBP) ≥ 140 mmHg and/or diastolic blood pressure (DBP) ≥ 90 mmHg, or with a previous diagnosis of hypertension and currently being treated with oral antihypertensive drugs; (2) Smoking referred to those who smoked ≥ 1 cigarette per day on average, continuously or cumulatively for the past 6 months; (3) Drinking was defined as consuming alcohol at least once a week at a dose of ≥ 50 g of ethanol per occasion, continuously or cumulatively over the past 6 months; and (4) Regular exercise referred to participation in physical activity at least 5 d per week, cumulatively for ≥ 30 min per day, for 6 consecutive months or more.

Statistical analysis

Continuous variables were expressed as the mean ± SD or median with interquartile range and were analyzed by an independent Student’s t test or one-way analysis of variance test for normally and nonnormally distributed variables (the Kolmogorov–Smirnov test). Categorical data were analyzed using the chi-square test and are presented as frequencies (percentages). The NLR level was analyzed as a continuous variable and divided by quartiles. Multivariate logistic regression analyses were conducted to assess the independent association between NLR and diabetic kidney disease (DKD). After adjusting for age, sex, BMI, FPG, TG, LDL-C, and lifestyle factors, odds ratios (ORs) with 95% confidence intervals (CIs) were reported. The predictive value of NLR for renal dysfunction in different eGFR groups was tested by the area under the receiver operating characteristic curve (AUROC), and the optimal cutoff point of the NLR was obtained by calculating the Youden index. The Youden index is a method of evaluating the authenticity of a screening test, which represents the total ability of the screening method to detect true patients and nonpatients. A higher index is associated with a better effect and greater authenticity of the screening test. The NLR that corresponded to the maximum Youden index was then determined to be the optimal cutoff NLR in this study.

All statistical analyses were performed using SAS software (version 9.4). A two-tailed P value < 0.05 was considered statistically significant.

RESULTS
Implant data

Table 1 shows the general characteristics of the study population. A total of 1040 participants diagnosed with T2DM were included in the analysis and divided into four groups according to their NLR: quartile 1 (NLR < 1.38, 261 patients), quartile 2 (1.38 ≤ NLR < 1.76, 258 patients), quartile 3 (1.76 ≤ NLR < 2.30, 262 patients), and quartile 4 (NLR ≥ 2.30, 259 patients). No significant difference was observed among the groups concerning age, BMI, SBP, DBP, FPG, TG, platelet counts, smoking, drinking, regular exercise, and hypertension (Table 1). However, significant differences were found in terms of sex, BUN, Scr, eGFR, TC, LDL-C, HDL-C, neutrophil, lymphocyte and white blood cell (WBC) counts among the four groups (P < 0.05).

Table 1 Characteristics of all type 2 diabetes mellitus patients categorized by the neutrophil-to-lymphocyte ratio quartiles.
Variables
Total
Quartile 1 (NLR < 1.38)
Quartile 2 (1.38 ≤ NLR < 1.76)
Quartile 3 (1.76 ≤ NLR < 2.30)
Quartile 4 (NLR ≥ 2.30)
N1040261258262259
Male1, n (%)490 (47.1)99 (37.9)119 (46.1)130 (49.6)142 (54.8)
Age (yr)71.9 ± 5.571.5 ± 5.572.0 ± 5.771.9 ± 5.472.3 ± 5.5
BMI (kg/m2)25.0 ± 4.025.1 ± 3.625.3 ± 4.625.1 ± 3.724.7 ± 4.2
SBP (mmHg)145.3 ± 20.3144.8 ± 19.7144.4 ± 19.4146.5 ± 20.2145.3 ± 22.0
DBP (mmHg)78.7 ± 11.777.8 ± 11.579.0 ± 10.878.9 ± 11.079.2 ± 13.5
FPG (mmol/L)7.8 ± 2.47.6 ± 1.88.0 ± 2.87.8 ± 2.48.0 ± 2.3
BUN1 (mmol/L)6.8 ± 2.16.4 ± 1.66.9 ± 2.26.6 ± 2.07.1 ± 2.3
Scr1 (mmol/L)74.1 ± 21.868.2 ± 16.173.1 ± 19.475.3 ± 22.179.8 ± 26.8
eGFR1 (mL/min/1.73 m2)80.2 ± 15.783.6 ± 12.980.7 ± 15.079.3 ± 16.077.7 ± 17.0
TC1 (mmol/L)4.7 ± 1.25.0 ± 1.24.8 ± 1.34.7 ± 1.14.6 ± 1.1
TG (mmol/L)1.7 ± 1.51.6 ± 1.21.8 ± 2.01.7 ± 1.51.5 ± 1.1
LDL-C1 (mmol/L)3.0 ± 0.93.2 ± 1.03.0 ± 1.02.9 ± 0.92.9 ± 0.9
HDL-C1 (mmol/L)1.5 ± 0.41.5 ± 0.31.4 ± 0.31.5 ± 0.41.5 ± 0.4
Neutrophil13.7 ± 1.02.9 ± 0.73.5 ± 0.83.9 ± 0.94.5 ± 1.0
Lymphocyte12.1 ± 0.62.6 ± 0.72.2 ± 0.51.9 ± 0.41.5 ± 0.4
WBC16.3 ± 1.46.1 ± 1.36.3 ± 1.46.3 ± 1.46.5 ± 1.4
Platelet189.1 ± 48.5187.6 ± 46.3191.7 ± 46.2191.2 ± 52.0185.8 ± 49.4
Smoking, n (%)174 (16.7)36 (13.8)48 (18.6)47 (17.9)43 (16.6)
Drinking, n (%)179 (17.2)36 (13.8)54 (20.9)48 (18.3)41 (15.8)
Regular exercise, n (%)197 (18.9)53 (20.3)52 (20.2)51 (19.5)41 (15.8)
Hypertension, n (%)714 (68.7)171 (65.5)182 (70.5)187 (71.4)174 (67.2)

Using the definition of CKD, there were 132 cases in total. As shown in Figure 1, patients in the higher NLR quartile group had a greater prevalence of CKD (P for trend = 0.0011).

Figure 1
Figure 1 Comparison of chronic kidney disease prevalence in different neutrophil-to-lymphocyte ratio quartiles. The numbers above the bars and in brackets represent the cases and corresponding proportions of chronic kidney diseases in each neutrophil-to-lymphocyte ratio quartile group. CKD: Chronic kidney diseases.
Association between NLR and CKD in T2DM patients

As shown in Table 2, we found that high NLR was associated with a higher prevalence of CKD in T2DM patients in multivariate regression models even after adjustment for important clinical parameters, including age, sex, smoking, drinking, regular exercise, BMI, SBP, FPG, TG and LDL-C (P value < 0.0001). With an SD increase in the NLR, the prevalence of CKD increased by 44%. Furthermore, when NLR was categorized into quartiles, the association between NLR and CKD remained, and there was a 3.3-fold increased prevalence of CKD in T2DM patients in the highest quartile of NLR (OR 3.30, 95%CI: 1.78-6.12, P = 0.0001) compared to those in the lowest quartile. AUROC was analyzed to determine the predictive value of the NLR for the risk stratification of renal dysfunction. As shown in Figure 2, compared with the higher eGFR group (< 90 mL/min/1.73 m2 and < 60 mL/min/1.73 m2), the NLR had the highest AUROC (0.902) when eGFR was < 30 mL/min/1.73 m2 (P = 0.005, 95%CI: 0.840-0. 959). The AUROC for eGFR < 90 mL/min/1.73 m2 and eGFR < 60 mL/min/1.73 m2 was 0.553 (P = 0.019, 95%CI: 0.515-0.591) and 0.606 (P = 0.026, 95%CI: 0.556-0.657), respectively (Figure 2). The cutoff values (sensitivity and specificity) for different eGFR groups (< 90 mL/min/1.73 m2, < 60 mL/min/1.73 m2, and < 30 mL/min/1.73 m2) were 1.525 (69.1%, 40.9%), 1.605 (78.8%, 41.0%) and 2.525 (approximately 100%, 81.1%), respectively.

Figure 2
Figure 2 Predictive value of neutrophil-to-lymphocyte ratio for estimated glomerular filtration rate decline. ROC: Receiver operating characteristic curve; AUC: Area under the curve; eGFR: Estimated glomerular filtration rate.
Table 2 Association between neutrophil-to-lymphocyte ratio and chronic kidney disease in type 2 diabetic patients.
ExposureAge-and-sex adjusted model
Multivariate model

OR (95%CI)
P value
OR (95%CI)
P value
NLR (per SD)1.39 (1.17-1.65)0.00021.44 (1.21-1.72)< 0.0001
Quartile 1 (< 1.38)ReferenceReference
Quartile 2 (1.38–1.76)1.69 (0.89-3.22)0.11001.57 (0.81-3.04)0.1785
Quartile 3 (1.76–2.30)2.42 (1.30-4.50)0.00522.52 (1.35-4.73)0.0039
Quartile 4 (≥ 2.30)3.07 (1.68-5.62)0.00033.30 (1.78-6.12)0.0001
P for trend0.0001< 0.0001
DISCUSSION

In this cross-sectional study comprising 1040 patients diagnosed with T2DM, we observed that higher NLR was significantly associated with an increased prevalence of CKD, even after adjusting for various confounding factors. These findings shed light on the possibility of utilizing NLR as a promising clinical marker, facilitating early detection and subsequent management of CKD among patients with T2DM.

CKD is a common and severe complication in individuals with diabetes, although its precise pathogenesis remains poorly understood. It is recognized that a sequence of pathological events, including parenchymal cell loss, chronic inflammation, renal fibrosis, and reduced regenerative capacity of the kidney, can contribute to the development and progression of CKD[15]. Metabolic disorders in diabetic patients activate inflammatory signals within the body, and elevated levels of inflammatory factors contribute to kidney injury[16]. Chronic inflammation has been implicated in the development of complications associated with T2DM, and various inflammatory molecules, such as adipokines, chemokines, adhesion molecules, and cytokines, have been identified as contributors to CKD development[17]. However, several of these markers, such as C-reactive protein, interleukin-6, and tumor necrosis factor-α, are expensive and not routinely measured in clinical practice.

NLR has recently emerged as a discerning inflammatory indicator that provides insights into the equilibrium between neutrophils and lymphocytes, two critical constituents of the immune system. While neutrophils function as nonspecific instigators of inflammation, lymphocytes play regulatory and protective roles in the context of inflammatory responses[18]. NLR has garnered recognition as a reliable metric for gauging the extent of systemic inflammation[19,20]. Previous studies have shown a positive association between NLR and well-established inflammation markers, such as interleukin-6 and C-reactive protein[21,22]. Notably, in comparison to other inflammatory markers, the NLR exhibits advantages in terms of stability, cost-effectiveness, and accessibility[23].

Growing evidence substantiates the connection between elevated NLR and progression and prognosis of CKD[24-28]. Although DKD is the most common cause of CKD, the relationship between NLR and CKD in T2DM patients is still relatively understudied[29]. Notably, a previous study showed a positive correlation between neutrophil levels and urinary albumin excretion in individuals with T2DM, while lymphocyte levels displayed a negative correlation[30]. Similarly, a hospital-based investigation involving 655 adult patients with T2DM elucidated the independent association of NLR with the risk of developing DKD[31]. Additionally, a cross-sectional survey conducted in seven communities in China involving 4813 diabetic adults revealed a positive relationship between a higher NLR and a higher prevalence of DKD[32]. Furthermore, elevated NLR not only manifested as a risk factor for DKD but also served as a prognostic indicator for early detection of DKD[33]. In a small case-control study, significant differences were observed in NLR among different groups of T2DM patients based on their albuminuria status[34]. A meta-analysis that included 48 studies demonstrated higher NLR values in patients with DKD than in those without DKD[35]. Last but not least, a longitudinal 3-year follow-up study underscored the potential of NLR as a robust predictor of deteriorating renal function in individuals with diabetes[36].

Limits of the study

Our study adds to the literature by providing compelling evidence of a significant association between NLR and CKD prevalence in patients with T2DM. However, it should be noted that this study had some limitations. First, as a cross-sectional study, a causal relationship between NLR and CKD could not be established. Second, the small sample might have introduced selection bias. Third, due to data constraints, our study population was not assessed for urine albumin and CRP, consequently relying on eGFR to evaluate kidney function and WBC counts to assess inflammatory markers as a control for NLR. Last, as this study was conducted at a single center and only included patients aged 65 years and older, the generalizability of our findings to other settings may be limited. Therefore, future investigations should consider larger sample sizes and adopt prospective study designs to further explore this association.

CONCLUSION

Our findings revealed a significant association between elevated NLR levels and reduced eGFR, as well as a higher prevalence of CKD in Chinese adults with T2DM. These results suggest that NLR has potential as a valuable biomarker for early detection of kidney damage in diabetes patients. However, it is crucial to emphasize the need for further research to validate these findings and elucidate the potential causal relationship between NLR and CKD.

ACKNOWLEDGEMENTS

The authors thank all team members and participants in the Community Health Service Center of Songnan Town, Baoshan District, Shanghai, China.

Footnotes

Provenance and peer review: Unsolicited article; Externally peer reviewed.

Peer-review model: Single blind

Specialty type: Endocrinology and metabolism

Country/Territory of origin: China

Peer-review report’s scientific quality classification

Grade A (Excellent): 0

Grade B (Very good): 0

Grade C (Good): C, C

Grade D (Fair): D

Grade E (Poor): 0

P-Reviewer: Kurasawa S, Japan; Ohashi N, Japan S-Editor: Liu JH L-Editor: A P-Editor: Xu ZH

References
1.  Clinical guidelines for prevention and treatment of type 2 diabetes mellitus in the elderly in China (2022 edition). Zhonghua Neike Zazhi. 2022;61:12-50.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in F6Publishing: 60]  [Reference Citation Analysis (0)]
2.  Martínez-Castelao A, Navarro-González JF, Górriz JL, de Alvaro F. The Concept and the Epidemiology of Diabetic Nephropathy Have Changed in Recent Years. J Clin Med. 2015;4:1207-1216.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 73]  [Cited by in F6Publishing: 92]  [Article Influence: 10.2]  [Reference Citation Analysis (1)]
3.  Zhang L, Long J, Jiang W, Shi Y, He X, Zhou Z, Li Y, Yeung RO, Wang J, Matsushita K, Coresh J, Zhao MH, Wang H. Trends in Chronic Kidney Disease in China. N Engl J Med. 2016;375:905-906.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 388]  [Cited by in F6Publishing: 509]  [Article Influence: 63.6]  [Reference Citation Analysis (0)]
4.  American Diabetes Association. 11. Microvascular Complications and Foot Care: Standards of Medical Care in Diabetes-2020. Diabetes Care. 2020;43:S135-S151.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 239]  [Cited by in F6Publishing: 261]  [Article Influence: 65.3]  [Reference Citation Analysis (0)]
5.  Wu AY, Kong NC, de Leon FA, Pan CY, Tai TY, Yeung VT, Yoo SJ, Rouillon A, Weir MR. An alarmingly high prevalence of diabetic nephropathy in Asian type 2 diabetic patients: the MicroAlbuminuria Prevalence (MAP) Study. Diabetologia. 2005;48:17-26.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 150]  [Cited by in F6Publishing: 153]  [Article Influence: 8.1]  [Reference Citation Analysis (0)]
6.  Jha V. Current status of chronic kidney disease care in southeast Asia. Semin Nephrol. 2009;29:487-496.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 60]  [Cited by in F6Publishing: 65]  [Article Influence: 4.3]  [Reference Citation Analysis (0)]
7.  Templeton AJ, McNamara MG, Šeruga B, Vera-Badillo FE, Aneja P, Ocaña A, Leibowitz-Amit R, Sonpavde G, Knox JJ, Tran B, Tannock IF, Amir E. Prognostic role of neutrophil-to-lymphocyte ratio in solid tumors: a systematic review and meta-analysis. J Natl Cancer Inst. 2014;106:dju124.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 1645]  [Cited by in F6Publishing: 2062]  [Article Influence: 206.2]  [Reference Citation Analysis (0)]
8.  Huang Z, Fu Z, Huang W, Huang K. Prognostic value of neutrophil-to-lymphocyte ratio in sepsis: A meta-analysis. Am J Emerg Med. 2020;38:641-647.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 98]  [Cited by in F6Publishing: 247]  [Article Influence: 49.4]  [Reference Citation Analysis (0)]
9.  Gong P, Liu Y, Gong Y, Chen G, Zhang X, Wang S, Zhou F, Duan R, Chen W, Huang T, Wang M, Deng Q, Shi H, Zhou J, Jiang T, Zhang Y. The association of neutrophil to lymphocyte ratio, platelet to lymphocyte ratio, and lymphocyte to monocyte ratio with post-thrombolysis early neurological outcomes in patients with acute ischemic stroke. J Neuroinflammation. 2021;18:51.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 36]  [Cited by in F6Publishing: 156]  [Article Influence: 52.0]  [Reference Citation Analysis (0)]
10.  Ao G, Wang Y, Qi X, Wang F, Wen H. Association of neutrophil-to-lymphocyte ratio and risk of cardiovascular or all-cause mortality in chronic kidney disease: a meta-analysis. Clin Exp Nephrol. 2021;25:157-165.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 5]  [Cited by in F6Publishing: 5]  [Article Influence: 1.3]  [Reference Citation Analysis (0)]
11.  Diabetics Branch of Chinese Medical Association. Guidelines for Prevention and Treatment of Type 2 Diabetes in China (2020 edition). Zhongguo Tangniaobing Zazhi. 2021;13:315-409.  [PubMed]  [DOI]  [Cited in This Article: ]
12.  Levin A, Stevens PE. Summary of KDIGO 2012 CKD Guideline: behind the scenes, need for guidance, and a framework for moving forward. Kidney Int. 2014;85:49-61.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 394]  [Cited by in F6Publishing: 520]  [Article Influence: 47.3]  [Reference Citation Analysis (0)]
13.  Revision Committee of Guidelines on Hypertension Prevention and Treatment. Guidelines for Hypertension Prevention and Treatment in China (2018 Revision). Zhongguo Xinxueguan Zazhi. 2019;24:24-56.  [PubMed]  [DOI]  [Cited in This Article: ]
14.  Levey AS, Stevens LA, Schmid CH, Zhang YL, Castro AF 3rd, Feldman HI, Kusek JW, Eggers P, Van Lente F, Greene T, Coresh J; CKD-EPI (Chronic Kidney Disease Epidemiology Collaboration). A new equation to estimate glomerular filtration rate. Ann Intern Med. 2009;150:604-612.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 15626]  [Cited by in F6Publishing: 18852]  [Article Influence: 1256.8]  [Reference Citation Analysis (0)]
15.  Ruiz-Ortega M, Rayego-Mateos S, Lamas S, Ortiz A, Rodrigues-Diez RR. Targeting the progression of chronic kidney disease. Nat Rev Nephrol. 2020;16:269-288.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 192]  [Cited by in F6Publishing: 460]  [Article Influence: 115.0]  [Reference Citation Analysis (0)]
16.  Matoba K, Takeda Y, Nagai Y, Kawanami D, Utsunomiya K, Nishimura R. Unraveling the Role of Inflammation in the Pathogenesis of Diabetic Kidney Disease. Int J Mol Sci. 2019;20.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 86]  [Cited by in F6Publishing: 120]  [Article Influence: 24.0]  [Reference Citation Analysis (0)]
17.  Wada J, Makino H. Inflammation and the pathogenesis of diabetic nephropathy. Clin Sci (Lond). 2013;124:139-152.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 447]  [Cited by in F6Publishing: 544]  [Article Influence: 49.5]  [Reference Citation Analysis (0)]
18.  Khandare SA, Chittawar S, Nahar N, Dubey TN, Qureshi Z. Study of Neutrophil-lymphocyte Ratio as Novel Marker for Diabetic Nephropathy in Type 2 Diabetes. Indian J Endocrinol Metab. 2017;21:387-392.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 32]  [Cited by in F6Publishing: 26]  [Article Influence: 3.7]  [Reference Citation Analysis (0)]
19.  Winter L, Wong LA, Jerums G, Seah JM, Clarke M, Tan SM, Coughlan MT, MacIsaac RJ, Ekinci EI. Use of Readily Accessible Inflammatory Markers to Predict Diabetic Kidney Disease. Front Endocrinol (Lausanne). 2018;9:225.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 26]  [Cited by in F6Publishing: 35]  [Article Influence: 5.8]  [Reference Citation Analysis (0)]
20.  Ko HL, Jung J, Lee J, Lim JH, Im DW, Kim YC, Paek JH, Park WY, Kim KM, Lee S, Lee SW, Shin SJ, Kim DK, Han SS, Baek CH, Kim H, Park JY, Ban TH, Kim K. Dynamic nature and prognostic value of the neutrophil-to-lymphocyte ratio in critically ill patients with acute kidney injury on continuous renal replacement therapy: A multicenter cohort study. Front Med (Lausanne). 2023;10:1162381.  [PubMed]  [DOI]  [Cited in This Article: ]  [Reference Citation Analysis (0)]
21.  Okyay GU, Inal S, Oneç K, Er RE, Paşaoğlu O, Paşaoğlu H, Derici U, Erten Y. Neutrophil to lymphocyte ratio in evaluation of inflammation in patients with chronic kidney disease. Ren Fail. 2013;35:29-36.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 93]  [Cited by in F6Publishing: 105]  [Article Influence: 8.8]  [Reference Citation Analysis (0)]
22.  Karava V, Kondou A, Dotis J, Taparkou A, Farmaki E, Kollios K, Printza N. Exploring systemic inflammation in children with chronic kidney disease: correlates of interleukin 6. Pediatr Nephrol. 2024;39:1567-1576.  [PubMed]  [DOI]  [Cited in This Article: ]  [Reference Citation Analysis (0)]
23.  Yan YT, Liu HM, Kong YF, Liu JM, Li C, Zhao BC, Liu KX. Association of preoperative neutrophil-lymphocyte ratio with acute kidney injury in patients with non-cardiac surgery: difference among surgical types. Int Urol Nephrol. 2023;55:2647-2656.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 1]  [Reference Citation Analysis (0)]
24.  Yoshitomi R, Nakayama M, Sakoh T, Fukui A, Katafuchi E, Seki M, Tsuda S, Nakano T, Tsuruya K, Kitazono T. High neutrophil/lymphocyte ratio is associated with poor renal outcomes in Japanese patients with chronic kidney disease. Ren Fail. 2019;41:238-243.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 27]  [Cited by in F6Publishing: 20]  [Article Influence: 4.0]  [Reference Citation Analysis (0)]
25.  Yuan Q, Wang J, Peng Z, Zhou Q, Xiao X, Xie Y, Wang W, Huang L, Tang W, Sun D, Zhang L, Wang F, Zhao MH, Tao L, He K, Xu H; C-STRIDE study group. Neutrophil-to-lymphocyte ratio and incident end-stage renal disease in Chinese patients with chronic kidney disease: results from the Chinese Cohort Study of Chronic Kidney Disease (C-STRIDE). J Transl Med. 2019;17:86.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 38]  [Cited by in F6Publishing: 52]  [Article Influence: 10.4]  [Reference Citation Analysis (0)]
26.  Roumeliotis S, Neofytou IE, Maassen C, Lux P, Kantartzi K, Papachristou E, Schurgers LJ, Liakopoulos V. Association of Red Blood Cell Distribution Width and Neutrophil-to-Lymphocyte Ratio with Calcification and Cardiovascular Markers in Chronic Kidney Disease. Metabolites. 2023;13.  [PubMed]  [DOI]  [Cited in This Article: ]  [Reference Citation Analysis (0)]
27.  Lin CH, Li YH, Wang YY, Chang WD. Higher Neutrophil-To-Lymphocyte Ratio Was Associated with Increased Risk of Chronic Kidney Disease in Overweight/Obese but Not Normal-Weight Individuals. Int J Environ Res Public Health. 2022;19.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 1]  [Cited by in F6Publishing: 1]  [Article Influence: 0.5]  [Reference Citation Analysis (0)]
28.  Kuo YT, Wang YY, Lin SY, Chang WD. Age and sex differences in the relationship between neutrophil-to-lymphocyte ratio and chronic kidney disease among an adult population in Taiwan. Clin Chim Acta. 2018;486:98-103.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 6]  [Cited by in F6Publishing: 6]  [Article Influence: 1.0]  [Reference Citation Analysis (0)]
29.  Alicic RZ, Rooney MT, Tuttle KR. Diabetic Kidney Disease: Challenges, Progress, and Possibilities. Clin J Am Soc Nephrol. 2017;12:2032-2045.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 1257]  [Cited by in F6Publishing: 1548]  [Article Influence: 221.1]  [Reference Citation Analysis (0)]
30.  Chung FM, Tsai JC, Chang DM, Shin SJ, Lee YJ. Peripheral total and differential leukocyte count in diabetic nephropathy: the relationship of plasma leptin to leukocytosis. Diabetes Care. 2005;28:1710-1717.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 61]  [Cited by in F6Publishing: 71]  [Article Influence: 3.7]  [Reference Citation Analysis (0)]
31.  Li L, Shen Q, Rao S. Association of Neutrophil-to-Lymphocyte Ratio and Platelet-to-Lymphocyte Ratio with Diabetic Kidney Disease in Chinese Patients with Type 2 Diabetes: A Cross-Sectional Study. Ther Clin Risk Manag. 2022;18:1157-1166.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in F6Publishing: 6]  [Reference Citation Analysis (0)]
32.  Wan H, Wang Y, Fang S, Chen Y, Zhang W, Xia F, Wang N, Lu Y. Associations between the Neutrophil-to-Lymphocyte Ratio and Diabetic Complications in Adults with Diabetes: A Cross-Sectional Study. J Diabetes Res. 2020;2020:6219545.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 33]  [Cited by in F6Publishing: 53]  [Article Influence: 13.3]  [Reference Citation Analysis (0)]
33.  Huang W, Huang J, Liu Q, Lin F, He Z, Zeng Z, He L. Neutrophil-lymphocyte ratio is a reliable predictive marker for early-stage diabetic nephropathy. Clin Endocrinol (Oxf). 2015;82:229-233.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 58]  [Cited by in F6Publishing: 65]  [Article Influence: 7.2]  [Reference Citation Analysis (0)]
34.  Jaaban M, Zetoune AB, Hesenow S, Hessenow R. Neutrophil-lymphocyte ratio and platelet-lymphocyte ratio as novel risk markers for diabetic nephropathy in patients with type 2 diabetes. Heliyon. 2021;7:e07564.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 3]  [Cited by in F6Publishing: 24]  [Article Influence: 8.0]  [Reference Citation Analysis (0)]
35.  Liu J, Liu X, Li Y, Quan J, Wei S, An S, Yang R, Liu J. The association of neutrophil to lymphocyte ratio, mean platelet volume, and platelet distribution width with diabetic retinopathy and nephropathy: a meta-analysis. Biosci Rep. 2018;38.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 26]  [Cited by in F6Publishing: 52]  [Article Influence: 8.7]  [Reference Citation Analysis (0)]
36.  Azab B, Daoud J, Naeem FB, Nasr R, Ross J, Ghimire P, Siddiqui A, Azzi N, Rihana N, Abdallah M, Patel P, Kleiner M, El-Sayegh S. Neutrophil-to-lymphocyte ratio as a predictor of worsening renal function in diabetic patients (3-year follow-up study). Ren Fail. 2012;34:571-576.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 62]  [Cited by in F6Publishing: 80]  [Article Influence: 6.7]  [Reference Citation Analysis (0)]