The aim of the present study was to investigate the correlation of neutrophil to lymphocyte ratio (NLR), mean platelet volume (MPV), and platelet distribution width (PDW) with diabetic nephropathy (DN) and diabetic retinopathy (DR). We searched for eligible studies from PubMed, Embase, Web of Science, and CNKI up to 1 December 2017. Standardized mean difference (SMD) was calculated with a confidence interval (CI) of 95%. A total of 48 studies were included in our meta-analysis. Compared with patients with type Ⅱ diabetes mellitus (T2DM) and without DR, NLR, MPV, and PDW were higher in patients with DR (SMD = 0.77; 95% CI: 0.49–1.05; P<0.001; SMD = 0.68; 95% CI: 0.36–0.99; P<0.001; SMD = 0.52; 95% CI: 0.28–0.76; P<0.01). Compared with patients with T2DM and without DN, NLR, MPV, and PDW were higher in patients with DN (SMD = 0.63; 95% CI: 0.43–0.83; P<0.001; SMD = 0.81; 95% CI: 0.36–1.25; P<0.001; SMD = 0.70; 95% CI: 0.50–0.90; P<0.001). We also found that MPV was strongly associated with the severity of DR, and NLR was closely related to the degree of DN. Our findings indicated that NLR, MPV, and PDW could be recommended as inexpensive diagnostic biomarkers for DN and DR. However, considering several limitations in the present study, further high-quality clinical studies should be performed to investigate the relationship of NLR, MPV, and PDW to DN and DR.

Introduction

Diabetes is a global health burden and its morbidity and mortality are increasing in recent decades, especially in populations from the low- and middle-income countries [1,2]. Diabetes is a systemic metabolic disorder disease that can result in several long-term micro- and macrovascular complications, including diabetic retinopathy (DR) and diabetic nephropathy (DN). It was reported that ~28.5–40.3% of patients with type II diabetes mellitus (T2DM) suffered from DR and 25–40% had DN [3–5]. To make things worse, DR and DN are serious microvascular complications and have been considered as the major cause of blindness and end-stage renal failure, respectively [3–5]. Thus, it is very significant for clinicians and researchers to elucidate pathogenesis of DR and DN and identify high-risk patients.

Diabetes mellitus (DM) is a chronic systemic disease. A flood of literatures have suggested that chronic inflammation was involved in insulin resistance and DM development [6–9]. Moreover, accumulated evidence have implicated that inflammatory response also plays a key part in the development and progression of DR and DN [10–13]. In the studies exploring the association of chronic inflammation with DR and DN, elevated C-reactive protein levels were observed in patients with DR, as compared in DM patients without DR. Besides, various inflammatory cytokines, such as interleukin-1, -6, -8, and tumor necrosis factor α were also considered to be tightly associated with the pathogenesis of DN. In recent years, neutrophil to lymphocyte ratio (NLR) as a novel indicator of systemic inflammatory response in various diseases emerged and was considered as an independent predictor of major morbidity, mortality, and long-term survival in many clinical settings [14–16]. Particularly, an increasing evidence showed that NLR was also closely related to the development and progression of DR and DN [13,17,18]. In addition to inflammation, prothrombotic state in DM patients was also reported to be implicated in the development and acceleration. Mean platelet volume (MPV), which can be readily obtained from the hematological analyzers, is a parameter to evaluate the platelet size and can reflect the platelet functions and activation. Platelets with higher MPV value have more metabolic and enzymatic activities than lower size, with more thromboxan-A2, b-thromboglobulin, and adhesion molecules releasing [19,20]. Besides, platelet distribution width (PDW) is a parameter that can directly mirror the variability of platelet size. Its high value indicates increased production of larger reticulated platelet and also suggests high activity. Thus, numerous studies have focussed on investigating the relationship of MPV and PDW to the development and progression of DR and DN, and several studies suggested that there was a positive link.

However, in retrospect, the conclusions regarding the relationship of NLR, MPV, and PDW to the development and progression of DR and DN were conflicting [21–23]. One of the reasons for the inconsistency might be that the sample size was small in a single study and the power of statistical results was challenged. Therefore, we herein performed a meta-analysis and systematic review to comprehensively assess the correlation of NLR, MPV, and PDW with DR and DN.

Methods

This meta-analysis was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statements [24]. Study selection, data extraction, and quality assessment were completed by two investigators separately.

Study selection

We searched PubMed, Embase, Web of Science, and CNKI up to 11 December 2017 to retrieve eligible studies. Literature search was performed using the following keywords: ‘neutrophil to lymphocyte ratio/NLR’ or ‘mean platelet volume/MPV’ or ‘platelet distribution/PDW’ in combination with ‘diabetic retinopathy/DR’ or ‘diabetic nephropathy/DN’. Moreover, references of the included studies were also examined. No language or date limitations were applied in this meta-analysis.

Inclusion criteria

Studies that met the following inclusion criteria were included in this meta-analysis. (i) The enrolled patients in studies were clearly diagnosed with T2DM. (ii) The data of NLR, MPV, and PDW were presented as the mean value with sufficient data (SD). (iii) There were comparisons of NLR, MPV, and PDW values between DM, and DR or DN.

Exclusion criteria

Studies have been excluded based on the following criteria: (i) reviews, editorials, meeting abstracts, case reports, and non-comparative studies; (ii) duplicate publications; (iii) data were unavailable or only reported in abstracts; (iv) articles were submitted by same authors or institution which might have overlapping patients.

Data extraction

All the data were extracted from each eligible article by two independent reviewers, and all disagreements on eligibility during the extraction were discussed and resolved through a consensus. The extracted information included the name of first author, publication year, study design, country, number of patients in case and control groups, mean age and sex in each group, the mean value with SD of NLR, MPV, PDW.

Methodology quality assessment

The Newcastle–Ottawa scale (NOS) was used for the assessment of included studies [25]. And a score of 0–9 points has been assigned to each study, and studies ≥6 points were considered to be of relatively high quality.

Statistical analysis

The statistical analysis was performed by using STATA version 12.0 (Stata Corporation, College Station, TX, U.S.A.). Standard mean difference (SMD) and its 95% confidence interval (CI) was used to depict the pooled continuous variables. If the data of NLR, MPV, and PDW were reported in non-proliferative DR/proliferative DR (NPDR/PDR) or microalbuminuria/macroalbuminuria (MIA/MA) groups, the data in NPDR or MIA were used to compare with control group. Based on the 95% CI not crossing 0, the SMD < 0 suggested that the specific hematologic inflammatory marker increased in control group. In addition, statistical heterogeneity amongst the studies was evaluated by Cochrane Q test (χ2) and I2 test. Moreover, a random-effect model was conducted to calculate the SMD when significant heterogeneity existed amongst some studies (P<0.05 and I2 ≥ 50%), otherwise, fixed-effect model was used. Sensitivity analysis was performed to verify the stabilization of our results, by excluding the articles one by one in each corresponding group, and then obtained meta-analysis results from the remaining studies. Furthermore, the Begg’s test and Egger’s test were performed to evaluate the publication bias [26,27]. If the significant publications bias exist (P<0.01 for Begg’s test and Egger’s test), Duval wnd Tweedie’s [28] non-parametric trim-and-fill method was conducted to evaluate the effects of bias on the results.

Results

Study selection

The flow chart diagram of the process of study selection was shown in Figure 1. A total of 190 articles were yielded through primary study searching for PubMed, Embase, Web of Science, and CNKI. Of these studies, 44 were from PubMed, 67 from Embase, 52 from Web of Science, and 27 from CNKI. Amongst these studies, 17 articles were removed because of duplication, and 105 publications were excluded due to reviews, meeting abstracts, and studies not pertinent to DR or DN after screening the title and abstract. Thus, the remaining 68 articles were left for the full-text review. Of the 68 studies, 9 articles were excluded since control group’s subjects were not DM patients, but healthy people, and 11 articles were removed owing to the lack of available data. Finally, 48 articles with 9118 patients were enrolled in this meta-analysis [21–23,29–73].

Flow chart of study selection process

Characteristics of included studies

All the selected studies were published from 2000 to 2017. The number of the included subjects in the case group and the control group ranged from 20 to 328 and 20 to 192, respectively. Of these 48 articles, 27 came from China [22,30,34,36,37,41,43–46,48,49,55–60,64,65,67,68,70–73], 16 from Turkey [21,23,29,31,35,38,40,42,47,50–54,61,69], 3 from India [32,63,39], 1 from Greece [62] and 1 from Kazakhstan [33]. Amongst these studies, 21 reported NLR (9 enrolled patients with DR, 12 enrolled patients with DN) [21,23,31,32,34,35,38,41–43,45,47,50–54,56–60,62,63,65,67–69,71–73], 33 reported the data of MPV (23 enrolled patients with DR, 10 enrolled patients with DN) [22,29,30,33,36–40,44,46,48–50,55,61,64,66,70,73], and 12 reported PDW (12 enrolled patients with DR, 3 enrolled patients with DN) [21,23,32,41,43,50,58–60,65,67–69,71]. The basic characteristics and data of our interest of the eligible studies were summarized in Tables 1–6. Moreover, the methodological quality of the included articles were assessed according to NOS, and the scores ranged from 5 to 7, indicating that the quality of selected studies were moderate to high.

Table 1
The main characteristics of the included studies on the relationship of MPV and PDW with diabetic nephropathy
   No. of patients    
Author Year Study design Country Proteinuria (−) Proteinuria (+) Age Mean/Median Male/Female NOS 
    MIA MA    
Bavbek 2007 [31Turkey 39 75 P(-): 59.5 ± 8.1
P(+): 59.4 ± 10.8 
P(-): 27/12
P(+): 47/28 
Buch 2017 [32India 264 36 NR NR 
Dindar 2013 [35Turkey 35 25 NR NR 
Kahraman 2016 [39Turkey 54 34 24 P(-): 59.9 ±7.9
MIA: 64.1 ±8.9
MA: 56.8 ±12.5 
P(-): 16/38
MIA: 16/18
MA: 7/17 
UNUBOL 2011 [42Turkey 230 124 P(-): 56.87±9.65
P(+): 55.73±11.07 
P(-): 108/122
P(+): 54/70 
Turgutalp 2012 [47Turkey 160 144 P(-): 55.14 + 10.90
P(+): 54.08 + 12.16 
P(-): 77/83
P(+): 74/70 
Cui 2006 [34China 30 42 NR P(-): 15/15
P(+): 20/22 
Liang 2008 [41China 68 68 P(-): 69.1
P(+): 67.1 
P(-): 32/36
P(+): 30/38 
Ma 2007 [43China 72 80 P(-): 67.6
P(+): 68.3 
P(-): 32/40
P(+): 34/46 
Sun 2007 [45China 35 31 30 P(-): 57.3±14.6
MIA: 57.6±13.5
MA: 58.2±13.2 
P(-): 18/17
MIA: 16/15
MA: 16/14 
Akbas 2014 [29Turkey 132 34 34 P(-): 56.03±10.54
MIA: 60.35±11.40
MA: 59.03±9.61 
P(-): 69/63
MIA: 16/18
MA: 18/16 
Ao 2017 [30China 80 100 100 P(-): 57.1±11.1
MIA: 56.4±8.5
MA: 70.6±7.6 
P(-): 41/39
MIA: 55/45
MA: 56/44 
Ciray 2015 [33USA 52 62 P(-): 56.9 ± 10.1
P(+): 62.1 ± 11.7 
NR 
Demirtas 2015 [53Turkey 193 114 NR NR 
Huang 2014 [37China 138 115 NR NR 
Feng 2016 [36China 38 52 30 P(-): 61.8±9.1
MIA: 57.7±10.80
MA: 63.1±10.1 
P(-): 23/15
MIA: 18/34
MA: 16/14 
Kahraman 2016 [38Turkey 54 34 24 P(-): 59.9 ±7.9
MIA: 64.1 ±8.9
MA: 56.8 ±12.5 
P(-): 16/38
MIA: 16/18
MA: 7/17 
Khandare 2017 [39India 56 59 P(-): 50.05±11.29
P(+): 52.29±11.45 
P(-): 26/33
P(+): 25/31 
Ren 2015 [44China 165 124 41 P(-): 56.90±11.25
MIA: 55.35±11.26
MA: 55.02±10.04 
P(-): 81/84
MIA: 71/53
MA: 26/15 
Tian 2017 [46China 72 49 P(-): 57.32±10.43
P(+): 61.14±12.03 
P(-): 39/33
P(+): 29/20 
Xu 2016 [48China 86 74 P(-): 44.41±10.81
P(+): 49.22±12.71 
P(-): 48/38
P(+): 48/26 
Zhu 2016 [49China 180 112 P(-): 45.270±7.542
P(+): 48.070±9.377 
P(-): 80/100
P(+): 60/52 
   No. of patients    
Author Year Study design Country Proteinuria (−) Proteinuria (+) Age Mean/Median Male/Female NOS 
    MIA MA    
Bavbek 2007 [31Turkey 39 75 P(-): 59.5 ± 8.1
P(+): 59.4 ± 10.8 
P(-): 27/12
P(+): 47/28 
Buch 2017 [32India 264 36 NR NR 
Dindar 2013 [35Turkey 35 25 NR NR 
Kahraman 2016 [39Turkey 54 34 24 P(-): 59.9 ±7.9
MIA: 64.1 ±8.9
MA: 56.8 ±12.5 
P(-): 16/38
MIA: 16/18
MA: 7/17 
UNUBOL 2011 [42Turkey 230 124 P(-): 56.87±9.65
P(+): 55.73±11.07 
P(-): 108/122
P(+): 54/70 
Turgutalp 2012 [47Turkey 160 144 P(-): 55.14 + 10.90
P(+): 54.08 + 12.16 
P(-): 77/83
P(+): 74/70 
Cui 2006 [34China 30 42 NR P(-): 15/15
P(+): 20/22 
Liang 2008 [41China 68 68 P(-): 69.1
P(+): 67.1 
P(-): 32/36
P(+): 30/38 
Ma 2007 [43China 72 80 P(-): 67.6
P(+): 68.3 
P(-): 32/40
P(+): 34/46 
Sun 2007 [45China 35 31 30 P(-): 57.3±14.6
MIA: 57.6±13.5
MA: 58.2±13.2 
P(-): 18/17
MIA: 16/15
MA: 16/14 
Akbas 2014 [29Turkey 132 34 34 P(-): 56.03±10.54
MIA: 60.35±11.40
MA: 59.03±9.61 
P(-): 69/63
MIA: 16/18
MA: 18/16 
Ao 2017 [30China 80 100 100 P(-): 57.1±11.1
MIA: 56.4±8.5
MA: 70.6±7.6 
P(-): 41/39
MIA: 55/45
MA: 56/44 
Ciray 2015 [33USA 52 62 P(-): 56.9 ± 10.1
P(+): 62.1 ± 11.7 
NR 
Demirtas 2015 [53Turkey 193 114 NR NR 
Huang 2014 [37China 138 115 NR NR 
Feng 2016 [36China 38 52 30 P(-): 61.8±9.1
MIA: 57.7±10.80
MA: 63.1±10.1 
P(-): 23/15
MIA: 18/34
MA: 16/14 
Kahraman 2016 [38Turkey 54 34 24 P(-): 59.9 ±7.9
MIA: 64.1 ±8.9
MA: 56.8 ±12.5 
P(-): 16/38
MIA: 16/18
MA: 7/17 
Khandare 2017 [39India 56 59 P(-): 50.05±11.29
P(+): 52.29±11.45 
P(-): 26/33
P(+): 25/31 
Ren 2015 [44China 165 124 41 P(-): 56.90±11.25
MIA: 55.35±11.26
MA: 55.02±10.04 
P(-): 81/84
MIA: 71/53
MA: 26/15 
Tian 2017 [46China 72 49 P(-): 57.32±10.43
P(+): 61.14±12.03 
P(-): 39/33
P(+): 29/20 
Xu 2016 [48China 86 74 P(-): 44.41±10.81
P(+): 49.22±12.71 
P(-): 48/38
P(+): 48/26 
Zhu 2016 [49China 180 112 P(-): 45.270±7.542
P(+): 48.070±9.377 
P(-): 80/100
P(+): 60/52 

Abbreviation: R: Retrospective study design; P: Proteinuria; MIA: Microalbuminuria; MA: Macroalbuminuria

Table 2
values of NLR in T2DM subjects with and without diabetic nephropathy
 Neutrophil to Lymphocyte Ratio 
First author Proteinuria (−) Proteinuria (+) 
   MIA MA 
 Mean SD Mean SD Mean SD 
Akbas 2014 [291.56 0.85 1.96 0.73 2.03 1.52 
Ao 2017 [301.67 0.54 1.85 0.77 2.44 0.73 
Ciray 2015 [331.77 0.56 2.27 ± 1.25 
Demirtas 2015 [531.68 0.20 1.99±0.28 
Huang 2014 [372.20 0.62 2.48±0.59 
Feng 2016 [362.03 1.26 2.72 1.47 3.54 1.15 
Kahraman 2016 [381.9 0.9 2.6 1.0 3.6 1.3 
Khandare 2017 [391.94 0.65 2.83±0.85 
Ren 2015 [441.84 0.61 2.14 1.30 2.74 1.74 
Tian 2017 [461.76 0.76 2.14±1.06 
Xu 2016 [481.81 0.56 2.27±0.92 
Zhu 2016 [491.836 0.733 2.654±1.465 
 Neutrophil to Lymphocyte Ratio 
First author Proteinuria (−) Proteinuria (+) 
   MIA MA 
 Mean SD Mean SD Mean SD 
Akbas 2014 [291.56 0.85 1.96 0.73 2.03 1.52 
Ao 2017 [301.67 0.54 1.85 0.77 2.44 0.73 
Ciray 2015 [331.77 0.56 2.27 ± 1.25 
Demirtas 2015 [531.68 0.20 1.99±0.28 
Huang 2014 [372.20 0.62 2.48±0.59 
Feng 2016 [362.03 1.26 2.72 1.47 3.54 1.15 
Kahraman 2016 [381.9 0.9 2.6 1.0 3.6 1.3 
Khandare 2017 [391.94 0.65 2.83±0.85 
Ren 2015 [441.84 0.61 2.14 1.30 2.74 1.74 
Tian 2017 [461.76 0.76 2.14±1.06 
Xu 2016 [481.81 0.56 2.27±0.92 
Zhu 2016 [491.836 0.733 2.654±1.465 
Table 3
The values of mean platelet volume and platelet distribution width T2DM subjects with and without diabetic nephropathy
 Mean Platelet Volume (fl) Platelet Distribution Width (%) 
First author Proteinuria (−) Proteinuria (+) Proteinuria (−) Proteinuria (+) 
   MIA MA   MIA MA 
 Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD 
Bavbek 2007 [318.3 1.3 8.6±1.3 NR NR NR NR NR 
Buch 2017 [3210.47 2.06 11.01±2.23 13.99 3.48 15.72±3.97 
Dindar 2013 [3510.80 1.09 11.07±1.13 NR NR NR 
Kahraman 2016 [388.8 1.0 8.8 1.2 8.3 0.9 NR NR NR 
UNUBOL 2011 [428.61 1.06 8.95±1.14 NR NR NR 
Turgutalp 2012 [479.85 0.74 10.61± 0.55 NR NR NR 
Cui 2006 [348.3 1.1 9.1±1.3 NR NR NR 
Liang 2008 [4110.2 1.2 13.2±1.3 17.1 1.2 18.2±1.2 
Ma 2007 [438.3 1.1 10.3±1.3 17.2 1.3 18.1±1.3 
Sun 2007 [458.25 1.13 10.13 2.01 11.19 2.56 NR NR NR 
 Mean Platelet Volume (fl) Platelet Distribution Width (%) 
First author Proteinuria (−) Proteinuria (+) Proteinuria (−) Proteinuria (+) 
   MIA MA   MIA MA 
 Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD 
Bavbek 2007 [318.3 1.3 8.6±1.3 NR NR NR NR NR 
Buch 2017 [3210.47 2.06 11.01±2.23 13.99 3.48 15.72±3.97 
Dindar 2013 [3510.80 1.09 11.07±1.13 NR NR NR 
Kahraman 2016 [388.8 1.0 8.8 1.2 8.3 0.9 NR NR NR 
UNUBOL 2011 [428.61 1.06 8.95±1.14 NR NR NR 
Turgutalp 2012 [479.85 0.74 10.61± 0.55 NR NR NR 
Cui 2006 [348.3 1.1 9.1±1.3 NR NR NR 
Liang 2008 [4110.2 1.2 13.2±1.3 17.1 1.2 18.2±1.2 
Ma 2007 [438.3 1.1 10.3±1.3 17.2 1.3 18.1±1.3 
Sun 2007 [458.25 1.13 10.13 2.01 11.19 2.56 NR NR NR 

Abbreviation: MIA: Microalbuminuria; MA: Macroalbuminuria

Table 4
The main characteristics of the included studies on the relationship of MPV and PDW diabetic retinopathy
   No. of    
Author Year Study design Country Cases with DM Cases with NPDR Cases with PDR Age Mean/Median Male/Female NOS 
Akdoğan 2016 [50Retrospective Turkey 158 120 DM:57.3±12.2
DR: 59.8±9.2
 
DM: 59/99
DR: 47/73 
Ateş 2009 [51Retrospective Turkey 30 30 30 NR NR 
Buch, 2017 [32Retrospective India 220 80 NR NR 
Citirik 2015 [23Prospective Turkey 43 45 52 DM:60.4 ± 8.5
NPDR:61.4 ± 9.3
PDR:59.4 ± 7.2 
DM: 22/21
NPDR: 17/28
PDR: 20/32 
Demirtas 2015 [53Prospective Turkey 240 67 NR NR 
Dindar 2013 [35Retrospective Turkey 36 24 NR NR 
GÜNGÖR 2016 [54Retrospective Turkey 50 52 NR DM: 19/31
DR: 18/34 
Li 2014 [56Retrospective China 72 67 70 DM:54.2 ± 9.2
NPDR:57.7± 10.0
PDR:58.3 ± 9.4 
DM:35/37
NPDR:34/33
PDR:33/37 
Li 2013 [57Retrospective China 103 132 NR NR 
Li 2016 [58Retrospective China 52 47 DM: 55.1±15.2
DR: 54.1±10.8 
DM: 31/21
DR:26/21 
Ma 2017 [59Retrospective China 20 20 20 DM:57.3± 6.5
NPDR:60.8± 7.3
PDR:57.6 ± 7.3 
DM:12/8
NPDR:8/12
PDR:12/8 
Niu 2013 [60Retrospective China 20 25 DM:46.5±8.3
DR:51.2±8.3 
DM:12/8
DR:13/12 
Papanas 2004 [62Retrospective Greece 89 167 NR NR 
Radha 2016 [63Retrospective India 30 14 NR NR 
Sheng 2017 [64Retrospective China 102 102 NR NR 
Tetikoğlu 2016 [21Retrospective Turkey 63 56 80 NR NR 
Tuzcu 2014 [52Retrospective Turkey 70 64 58 DM: 55.8 ±10.5
NPDR: 60.1 ± 8.6
PDR: 57.5 ± 9.3 
DM:38/32
NPDR:32/32
PDR:31/27 
Wei 2017 [67Retrospective China 94 52 40 DM: 58.14 ± 11.93
DR: 58.42 ± 12.09 
DM:50/44
DR:49/43 
Xu 2014 [68Retrospective China 45 40 NR DM: 23/22
DR:26/14 
Yilmaz 2016 [69prospective Turkey 89 88 86 DM: 60.9 ± 6.3
NPDR: 62.7 ± 7.2
PDR: 61.7 ± 7.9 
DM:49/40
NPDR:48/40
PDR:49/37 
Yu 2000 [71Retrospective China 60 40 NR NR 
Yue 2015 [22Retrospective China 125 62 59 DM: 56.00 ± 3.75
NPDR: 53.50 ± 3.56
PDR: 56.0 ± 3 
DM:73/52
NPDR:34/28
PDR:28/31 
Zhang 2002 [72Retrospective China 20 20 DM:58.0±9.0
DR:60.0±1.3 
DM: 9/11
DR:8/12 
Zhou 2016 [73Retrospective China 328 51 DM: 57 ±16
DR: 63 ±15 
DM: 198/130
DR: 34/17 
Akdoğan 2016 [50Retrospective Turkey 158 120 DM:57.3±12.2
DR: 59.8±9.2 
DM: 59/99
DR: 47/73 
Ciray 2015 [33Retrospective Kazakhstan 59 55 DM: 57.8 ± 11.5
DR: 61.8 ± 10.8 
NR 
Kuang 2015 [55Retrospective China 62 44 22 DM:60.73 ± 11.24
NPDR:60.50 ± 8.45
PDR:55.18 ± 13.05 
DM:29/33
NPDR:17/27
PDR:11/11 
Öztürk 2013 [61Retrospective Turkey 97 79 NR NR NR 
Shen 2016 [64Retrospective China 118 134 58 DM:55.19 ± 5.51
NPDR:58.04 ± 7.53
PDR:59.84 ± 8.76 
DM:63/55
NPDR:73/61
PDR:34/24 
Ulu 2013 [66Retrospective Turkey 34 24 NR NR 
Wei 2017 [67Retrospective China 94 52 40 DM: 58.14 ± 11.93
DR: 58.42 ± 12.09 
DM:50/44
DR:49/43 
Wang 2015 [18Retrospective China 138 131 DM: 60.3 ± 6.0
DR: 66.6 ± 5.8 
DM:65/73
DR:53/78 
Yin 2015 [70Retrospective China 64 28 36 DM: 56.83 ± 9.01
NPDR: 53.09 ± 8.82
PDR: 53.16 ± 10.64 
DM:35/29
NPDR:13/15
PDR:19/17 
Yue 2015 [22Retrospective China 125 62 59 DM: 56.00 ± 3.75
NPDR: 53.50 ± 3.56
PDR: 56.0 ± 3 
DM:73/52
NPDR:34/28
PDR:28/31 
Zhou 2016 [73Retrospective China 328 51 DM: 57 ±16
DR: 63 ±15 
DM: 198/130
DR: 34/17 
   No. of    
Author Year Study design Country Cases with DM Cases with NPDR Cases with PDR Age Mean/Median Male/Female NOS 
Akdoğan 2016 [50Retrospective Turkey 158 120 DM:57.3±12.2
DR: 59.8±9.2
 
DM: 59/99
DR: 47/73 
Ateş 2009 [51Retrospective Turkey 30 30 30 NR NR 
Buch, 2017 [32Retrospective India 220 80 NR NR 
Citirik 2015 [23Prospective Turkey 43 45 52 DM:60.4 ± 8.5
NPDR:61.4 ± 9.3
PDR:59.4 ± 7.2 
DM: 22/21
NPDR: 17/28
PDR: 20/32 
Demirtas 2015 [53Prospective Turkey 240 67 NR NR 
Dindar 2013 [35Retrospective Turkey 36 24 NR NR 
GÜNGÖR 2016 [54Retrospective Turkey 50 52 NR DM: 19/31
DR: 18/34 
Li 2014 [56Retrospective China 72 67 70 DM:54.2 ± 9.2
NPDR:57.7± 10.0
PDR:58.3 ± 9.4 
DM:35/37
NPDR:34/33
PDR:33/37 
Li 2013 [57Retrospective China 103 132 NR NR 
Li 2016 [58Retrospective China 52 47 DM: 55.1±15.2
DR: 54.1±10.8 
DM: 31/21
DR:26/21 
Ma 2017 [59Retrospective China 20 20 20 DM:57.3± 6.5
NPDR:60.8± 7.3
PDR:57.6 ± 7.3 
DM:12/8
NPDR:8/12
PDR:12/8 
Niu 2013 [60Retrospective China 20 25 DM:46.5±8.3
DR:51.2±8.3 
DM:12/8
DR:13/12 
Papanas 2004 [62Retrospective Greece 89 167 NR NR 
Radha 2016 [63Retrospective India 30 14 NR NR 
Sheng 2017 [64Retrospective China 102 102 NR NR 
Tetikoğlu 2016 [21Retrospective Turkey 63 56 80 NR NR 
Tuzcu 2014 [52Retrospective Turkey 70 64 58 DM: 55.8 ±10.5
NPDR: 60.1 ± 8.6
PDR: 57.5 ± 9.3 
DM:38/32
NPDR:32/32
PDR:31/27 
Wei 2017 [67Retrospective China 94 52 40 DM: 58.14 ± 11.93
DR: 58.42 ± 12.09 
DM:50/44
DR:49/43 
Xu 2014 [68Retrospective China 45 40 NR DM: 23/22
DR:26/14 
Yilmaz 2016 [69prospective Turkey 89 88 86 DM: 60.9 ± 6.3
NPDR: 62.7 ± 7.2
PDR: 61.7 ± 7.9 
DM:49/40
NPDR:48/40
PDR:49/37 
Yu 2000 [71Retrospective China 60 40 NR NR 
Yue 2015 [22Retrospective China 125 62 59 DM: 56.00 ± 3.75
NPDR: 53.50 ± 3.56
PDR: 56.0 ± 3 
DM:73/52
NPDR:34/28
PDR:28/31 
Zhang 2002 [72Retrospective China 20 20 DM:58.0±9.0
DR:60.0±1.3 
DM: 9/11
DR:8/12 
Zhou 2016 [73Retrospective China 328 51 DM: 57 ±16
DR: 63 ±15 
DM: 198/130
DR: 34/17 
Akdoğan 2016 [50Retrospective Turkey 158 120 DM:57.3±12.2
DR: 59.8±9.2 
DM: 59/99
DR: 47/73 
Ciray 2015 [33Retrospective Kazakhstan 59 55 DM: 57.8 ± 11.5
DR: 61.8 ± 10.8 
NR 
Kuang 2015 [55Retrospective China 62 44 22 DM:60.73 ± 11.24
NPDR:60.50 ± 8.45
PDR:55.18 ± 13.05 
DM:29/33
NPDR:17/27
PDR:11/11 
Öztürk 2013 [61Retrospective Turkey 97 79 NR NR NR 
Shen 2016 [64Retrospective China 118 134 58 DM:55.19 ± 5.51
NPDR:58.04 ± 7.53
PDR:59.84 ± 8.76 
DM:63/55
NPDR:73/61
PDR:34/24 
Ulu 2013 [66Retrospective Turkey 34 24 NR NR 
Wei 2017 [67Retrospective China 94 52 40 DM: 58.14 ± 11.93
DR: 58.42 ± 12.09 
DM:50/44
DR:49/43 
Wang 2015 [18Retrospective China 138 131 DM: 60.3 ± 6.0
DR: 66.6 ± 5.8 
DM:65/73
DR:53/78 
Yin 2015 [70Retrospective China 64 28 36 DM: 56.83 ± 9.01
NPDR: 53.09 ± 8.82
PDR: 53.16 ± 10.64 
DM:35/29
NPDR:13/15
PDR:19/17 
Yue 2015 [22Retrospective China 125 62 59 DM: 56.00 ± 3.75
NPDR: 53.50 ± 3.56
PDR: 56.0 ± 3 
DM:73/52
NPDR:34/28
PDR:28/31 
Zhou 2016 [73Retrospective China 328 51 DM: 57 ±16
DR: 63 ±15 
DM: 198/130
DR: 34/17 

Abbreviation: DM: Diabetes mellitus; NPDR: Non-proliferative diabetic retinopathy; PDR: Proliferative diabetic retinopathy.

Table 5
values of NLR in T2DM subjects with and without diabetic retinopathy
 Neutrophil to Lymphocyte Ratio (%) Platelet to Lymphocyte Ratio (%) 
First author Cases without DR Cases with NPDR Cases with PDR Cases without DR Cases with NPDR Cases with PDR 
 Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD 
Akdoğan [502.4 1.9 3.0 ± 4.4 116 66 140 ± 87 
Ciray 2015 [331.99 1.03 2.10 ± 1.02 NR NR NR NR 
Kuang 2015 [551.68 0.48 2.20 0.40 2.58 0.41 NR NR NR NR 
Öztürk 2013 [612.04 0.72 2.58±1.34 NR NR NR NR 
Shen 2016 [641.52 0.26 1.68 0.21 1.95 0.17 NR NR NR NR 
Ulu 2013 [661.96 0.86 3.59 ±2.07 NR NR NR NR 
Wei 2017 [67NR NR NR NR NR  98.46 10.63 127.25 ± 12.98 
Wang 2015 [] 2.1 1.3 3.7 ± 1.4 NR NR NR NR 
Yin 2015 [701.54 0.55 1.83 0.59 2.15 0.77 NR NR NR NR 
Yue 2015 [221.74 0.245 2.05 0.3 1.91 0.28 94.04 12.365 105.07 17.47 115.73 14.54 
Zhou 2016 [732.4 1.5 4.4±2.7 NR NR NR NR 
 Neutrophil to Lymphocyte Ratio (%) Platelet to Lymphocyte Ratio (%) 
First author Cases without DR Cases with NPDR Cases with PDR Cases without DR Cases with NPDR Cases with PDR 
 Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD 
Akdoğan [502.4 1.9 3.0 ± 4.4 116 66 140 ± 87 
Ciray 2015 [331.99 1.03 2.10 ± 1.02 NR NR NR NR 
Kuang 2015 [551.68 0.48 2.20 0.40 2.58 0.41 NR NR NR NR 
Öztürk 2013 [612.04 0.72 2.58±1.34 NR NR NR NR 
Shen 2016 [641.52 0.26 1.68 0.21 1.95 0.17 NR NR NR NR 
Ulu 2013 [661.96 0.86 3.59 ±2.07 NR NR NR NR 
Wei 2017 [67NR NR NR NR NR  98.46 10.63 127.25 ± 12.98 
Wang 2015 [] 2.1 1.3 3.7 ± 1.4 NR NR NR NR 
Yin 2015 [701.54 0.55 1.83 0.59 2.15 0.77 NR NR NR NR 
Yue 2015 [221.74 0.245 2.05 0.3 1.91 0.28 94.04 12.365 105.07 17.47 115.73 14.54 
Zhou 2016 [732.4 1.5 4.4±2.7 NR NR NR NR 

Abbreviation: NLR: Neutrophil to lymphocyte ratio; T2DM: Type 2 diabetes mellitus; NPDR: Non-proliferative diabetic retinopathy; PDR: Proliferative diabetic retinopathy.

Table 6
values of MPV and PDW in T2DM subjects with and without diabetic retinopathy
 Mean Platelet Volume (fl) Platelet Distribution Width (%) 
First author Cases with DM Cases with NPDR Cases with PDR Cases with DM Cases with NPDR Cases with PDR 
 Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD 
Akdoğan 2016 [509.7 1.2 9.6 ± 1.0 16.2 0.8 16.2 ± 0.5 
Ateş 2009 [517.76 0.72 7.94 0.61 8.18 0.89 NR NR NR NR NR NR 
Buch, 2017 [3210.24 2.04 11.40 ± 1.96 13.94 3.33 14.92 ± 4.14 
Citirik 2015 [237.94 0.63 8.05 0.76 8.10 0.68 14.85 1.27 15.15 1.19 14.92 1.15 
Demirtas 2015 [539.20 0.92 9.54±0.88 NR NR NR NR NR NR 
Dindar 2013 [3510.68 1.68 11.26 ± 1.08 NR NR NR NR NR NR 
GÜNGÖR 2016 [548.8 1.1 9.3 ± 1.0 NR NR NR NR NR NR 
Li 2014 [567.8 1.1 8.3 1.38 8.9 1.65 NR NR NR NR NR NR 
Li 2013 [579.05 0.44 9.73 ± 0.53 NR NR NR NR NR NR 
Li 2016 [5810.39 0.90 10.72 ± 1.57 13.80 3.32 16.17 ± 1.66 
Ma 2017 [598.12 0.82 8.96 0.86 10.76 1.12 15.66 2.37 17.85 2.26 17.90 2.41 
Niu 2013 [6010.25 2.04 14.21 ± 2.35 16.05 1.56 18.12 ± 1.25 
Papanas 2004 [6210.9 1.1 15.8 ± 1.3 NR NR NR NR NR NR 
Radha 2016 [638.39 0.67 9.2 ± 0.61 NR NR NR NR NR NR 
Sheng 2017 [659.76 0.86 10.17 ± 0.92 11.31 1.67 12.04 ± 1.88 
Tetikoğlu 2016 [218.51 1.0 8.42 0.9 8.91 0.7 16.9 0.7 16.8 0.7 17.3 3.1 
Tuzcu 2014 [527.90 1.26 8.20 1.55 8.78 1.73 NR NR NR NR NR NR 
Wei 2017 [6711.12 1.3 11.50 1.39 11.56 1.06 13.70 2.90 14.40 2.88 14.20 1.99 
Xu 2012 [6811.21 1.71 13.44 ± 2.01 15.98 1.23 17.41 ± 1.42 
Yilmaz 2016 [697.84 0.76 7.90 0.85 8.31 0.76 13.02 1.29 13.49 1.18 13.77 1.26 
Yu 2000 [7110.93 2.35 13.08 ± 2.04 17.77 1.97 21.48 ± 5.94 
Yue 2015 [22NR NR NR NR NR NR 
Zhang 2002 [729.82 1.53 10.19 ± 2.06 NR NR NR NR NR NR 
Zhou 2016 [7310.0 1.1 10.4 ± 1.1 NR NR NR NR NR NR 
 Mean Platelet Volume (fl) Platelet Distribution Width (%) 
First author Cases with DM Cases with NPDR Cases with PDR Cases with DM Cases with NPDR Cases with PDR 
 Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD 
Akdoğan 2016 [509.7 1.2 9.6 ± 1.0 16.2 0.8 16.2 ± 0.5 
Ateş 2009 [517.76 0.72 7.94 0.61 8.18 0.89 NR NR NR NR NR NR 
Buch, 2017 [3210.24 2.04 11.40 ± 1.96 13.94 3.33 14.92 ± 4.14 
Citirik 2015 [237.94 0.63 8.05 0.76 8.10 0.68 14.85 1.27 15.15 1.19 14.92 1.15 
Demirtas 2015 [539.20 0.92 9.54±0.88 NR NR NR NR NR NR 
Dindar 2013 [3510.68 1.68 11.26 ± 1.08 NR NR NR NR NR NR 
GÜNGÖR 2016 [548.8 1.1 9.3 ± 1.0 NR NR NR NR NR NR 
Li 2014 [567.8 1.1 8.3 1.38 8.9 1.65 NR NR NR NR NR NR 
Li 2013 [579.05 0.44 9.73 ± 0.53 NR NR NR NR NR NR 
Li 2016 [5810.39 0.90 10.72 ± 1.57 13.80 3.32 16.17 ± 1.66 
Ma 2017 [598.12 0.82 8.96 0.86 10.76 1.12 15.66 2.37 17.85 2.26 17.90 2.41 
Niu 2013 [6010.25 2.04 14.21 ± 2.35 16.05 1.56 18.12 ± 1.25 
Papanas 2004 [6210.9 1.1 15.8 ± 1.3 NR NR NR NR NR NR 
Radha 2016 [638.39 0.67 9.2 ± 0.61 NR NR NR NR NR NR 
Sheng 2017 [659.76 0.86 10.17 ± 0.92 11.31 1.67 12.04 ± 1.88 
Tetikoğlu 2016 [218.51 1.0 8.42 0.9 8.91 0.7 16.9 0.7 16.8 0.7 17.3 3.1 
Tuzcu 2014 [527.90 1.26 8.20 1.55 8.78 1.73 NR NR NR NR NR NR 
Wei 2017 [6711.12 1.3 11.50 1.39 11.56 1.06 13.70 2.90 14.40 2.88 14.20 1.99 
Xu 2012 [6811.21 1.71 13.44 ± 2.01 15.98 1.23 17.41 ± 1.42 
Yilmaz 2016 [697.84 0.76 7.90 0.85 8.31 0.76 13.02 1.29 13.49 1.18 13.77 1.26 
Yu 2000 [7110.93 2.35 13.08 ± 2.04 17.77 1.97 21.48 ± 5.94 
Yue 2015 [22NR NR NR NR NR NR 
Zhang 2002 [729.82 1.53 10.19 ± 2.06 NR NR NR NR NR NR 
Zhou 2016 [7310.0 1.1 10.4 ± 1.1 NR NR NR NR NR NR 

Abbreviation: T2DM: Type 2 diabetes mellitus; NPDR: Non-proliferative diabetic retinopathy; PDR: Proliferative diabetic retinopathy.

Meta-analysis results

The association of NLR with DN and degree of albuminuria

A total of 12 studies involving 2404 patients were included for the meta-analysis of the association of NLR with the presence of DN [29,30,33,36–40,44,46,48,49], and 5 articles reported the data regarding the relationship between NLR and degree of albuminuria (MIA and MA) [29,30,36,38,44]. Random-effect model was applied since the significant heterogeneity was present for the presence of DN (I2 = 80.0; P<0.01), and degree of albuminuria (I2 = 53.1; P=0.07). From the results of our meta-analysis, NLR level was significantly higher in patients with DN (SMD = 0.63; 95% CI: 0.43–0.83) (Figure 2A) and MA (SMD = 0.56; 95% CI: 0.29–0.82) (Figure 2B), as compared with those without DN and MIA.

Results of forest plot of the relationship between NLR and DN
Figure 2
Results of forest plot of the relationship between NLR and DN

Forest plot of the relationship between NLR and DN (A); forest plot of the relationship between NLR and the degree of DN (B).

Figure 2
Results of forest plot of the relationship between NLR and DN

Forest plot of the relationship between NLR and DN (A); forest plot of the relationship between NLR and the degree of DN (B).

The association of NLR with DR

A total of ten studies with 1911 patients, which provided the data about the association of NLR with the presence of DR [22,33,50,55,61,64,66,70,73], were included in this meta-analysis. The heterogeneity tests showed the extinction of significant heterogeneity (I2 = 86.5; P<0.01), so random-effect model was used. The results suggested that NLR level was substantially higher in patients with DR (SMD = 0.77; 95% CI: 0.49–1.05) (Figure 3A) than those without DR. Additionally, four articles with 443 patients were also included for the meta-analysis of the association between NLR and the degree of DR (NPDR and PDR). However, no significant association between NLR and the degree of DR was observed in this meta-analysis (SMD = 0.57; 95% CI: −0.34–1.47) (Figure 3B).

Results of forest plot of the relationship between NLR and DR
Figure 3
Results of forest plot of the relationship between NLR and DR

Forest plot of the relationship between NLR and DR (A); forest plot of the relationship between NLR and the degree of DR (B).

Figure 3
Results of forest plot of the relationship between NLR and DR

Forest plot of the relationship between NLR and DR (A); forest plot of the relationship between NLR and the degree of DR (B).

The association of MPV with DN

A total of ten studies with 1700 patients reported the data of MPV for DN [31,32,34,35,38,41–43,45,47]. Considering the significant heterogeneity (I2 = 93.3; P<0.01), random-effect meta-analysis was conducted and the results showed that MPV was higher in patients with DN than DM patients without DN (SMD = 0.81; 95% CI: 0.36–1.25) (Figure 4).

Forest plot of the relationship between MPV and DN

The association of MPV with DR

There were 23 articles with 3437 patients, which had data of MPV for DR [21,23,32,35,50–54,56–60,62,63,65,67–69,71–73]. Random-effects model was used to pool the data because of the significant heterogeneity amongst the included studies (I2 = 94.1; P<0.01). From the result, we observed that MPV was higher in DR group as compared with DM patients without DR (SMD = 0.68; 95% CI: 0.36–0.99) (Figure 5A). Moreover, a total of eight studies with 858 patients investigated the association of MPV with the degree of DR. Similarly, random-effect model was applied due to the significant heterogeneity (I2 = 67.3; P<0.01). The result showed that MPV level was significantly higher in patients with PDR than in NPDR (SMD = 0.44; 95% CI: 0.20–0.69), indicating that MPV was closely correlated with the progression of DR (Figure 5B).

Results of forest plot of the relationship between MPV and DR
Figure 5
Results of forest plot of the relationship between MPV and DR

Forest plot of the relationship between MPV and DR (A); forest plot of the relationship between MPV and the degree of DR (B).

Figure 5
Results of forest plot of the relationship between MPV and DR

Forest plot of the relationship between MPV and DR (A); forest plot of the relationship between MPV and the degree of DR (B).

The association of PDW with DN

Three articles with 588 patients were included in the meta-analysis of the association between PDW and DN [32,41,43]. Heterogeneity analysis indicated the absence of significant heterogeneity (I2 = 29.6; P=0.241), so fixed-effect model was used. The result of meta-analysis showed that PDW level was elevated in DR group compared with DM group (SMD = 0.70; 95% CI: 0.50–0.90) (Figure 6).

Forest plot of the relationship between PDW and DN

The association of PDW with DR

A total of 12 articles with 1681 patients explored the relationship between PDW and DR [21,23,32,50,58–60,65,67–69,71]. Considering the significant heterogeneity amongst the 12 studies (I2 = 79.3; P<0.01), random-effect model was applied when we performed the meta-analysis. As the results showed, PDW level was significantly higher in DR group (SMD = 0.52; 95% CI: 0.28–0.76) than in DM group (Figure 7A). Furthermore, there were five studies with 539 patients, which referred to the relationship between PDW and the severity of DR. Hence, in the present study, we also performed the meta-analysis to investigate relationship between PDW and the severity of DR. However, the result indicated that there was no significant association of PDW with the severity of DR (SMD = 0.08; 95% CI: –0.09–0.25) (Figure 7B).

Results of forest plot of the relationship between PDW and DR
Figure 7
Results of forest plot of the relationship between PDW and DR

Forest plot of the relationship between PDW and DR (A); forest plot of the relationship between PDW and the degree of DR (B).

Figure 7
Results of forest plot of the relationship between PDW and DR

Forest plot of the relationship between PDW and DR (A); forest plot of the relationship between PDW and the degree of DR (B).

Sensitive analysis

For the purpose of verifying the robustness of the meta-analysis results, we conducted sensitivity analysis by excluding the articles one by one in each step, and then obtained the meta-analysis results of the remaining studies. The results implied that the synthesized SMDs of NLR for DN (Figure 8A), NLR for DR (Figure 8B), as well as MPV for DN (Figure 8C), MPV for DR (Figure 8D) and PDW for DR (Figure 8E) did not change substantially when omitting any individual study, indicating that the results of meta-analysis were robust although significant heterogeneity existed amongst the included studies. Owing to the limitation of study number, sensitivity analysis was not applicable for the synthesized SMDs of the other data.

The sensitive analysis of selected studies

Figure 8
The sensitive analysis of selected studies

NLR for DN (A), NLR for DR (B), MPV for DN (C), MPV for DR (D), PDW for DR (E).

Figure 8
The sensitive analysis of selected studies

NLR for DN (A), NLR for DR (B), MPV for DN (C), MPV for DR (D), PDW for DR (E).

Publication bias

The assessment of publication bias of the included studies was performed by using Begg’s and Egger’s test. From the results of the publication bias test, we found that there was no evidence of publication bias for the pooled SMDs of NLR for DN (Begg’s test, P=0.244; Egger’s test, P=0.990) (Figure 9A) and for DR (Begg’s test, P=0.929; Egger’s test, P=0.588) (Figure 9B). Similarly, the publication bias for the pooled SMD of MPV for DN was not observed either (Begg’s test, P=0.371; Egger’s test, P=0.690) (Figure 9C).

The funnel plots for the assessment of potential publication bias

Figure 9
The funnel plots for the assessment of potential publication bias

NLR for DN (A), NLR for DR (B), MPV for DR (C), MPV for DR (D), PDW for DR (E).

Figure 9
The funnel plots for the assessment of potential publication bias

NLR for DN (A), NLR for DR (B), MPV for DR (C), MPV for DR (D), PDW for DR (E).

Nevertheless, publication bias might exist amongst the eligible studies referring to MPV (Begg’s test, P=0.039; Egger’s test, P=0.148) (Figure 9D) and PDW (Begg’s tests, P=0.06; Egger’s tests, P=0.02) (Figure 9E) for DR. Consequently, we used meta-trim method to figure out the effect of publication bias on the dependability of the meta-analysis results. The results of meta-trim method showed that the adjusted SMDs of MPV and PDW were (0.68; 95% CI: 0.36–0.99) and (0.28; 95% CI: 0.018–0.540), respectively, indicating that the publication bias did not substantially affect the stability of the pooled results of the MPV and PDW for DR. In addition, the publication bias test was not applicable for the pooled SMD of PDW for DN owing to the limitation of the number of the eligible studies.

Discussion

To our knowledge, this is the first meta-analysis focussing on the association of NLR, MPV, and PDW with DN and DR. In our meta-analysis, we found that NLR, MPV, and PDW was higher in patients with DR or DN. In addition, we also observed that MPV was strongly associated with the severity of DR, and NLR was closely related to the degree of DN.

White blood cells and their subtypes have been widely considered as inflammatory markers in various diseases including DM. NLR calculated by blood routine examination is readily available and inexpensive. It has better stability since it reflects the balance between the peripheral blood neutrophils and lymphocytes, which is less affected by various physiological and pathological status, as compared with independent neutrophils, lymphocytes, and total white blood cell count. In recent years, studies have reported that NLR might be a novel inflammatory marker, and there was a significant relationship of NLR to conventional markers of inflammation. For instance, several studies showed that there was a positive association of NLR with serum IL-6 and C-reactive protein [74,75]. Furthermore, it has been recognized that chronic inflammation has a significant role in the development and deterioration of DM-associated complications [76]. Several studies have reported that various inflammatory molecules such as adipokines, chemokines, adhesion molecules, and cytokines, could contribute to the development of DN [77]. A study showed that NLR, as a novel inflammation marker, is inversely associated with glomerular filtration rate (GFR) patients with chronic kidney disease [14]. Particularly, a 3-year follow-up study showed that NLR could serve as a predictor of worsening renal function in diabetes patients [78]. Additionally, numerous studies have shown that elevated NLR was associated with the presence of DN and MA [75,79–81]. In consistence with that, this meta-analysis confirmed that DM patients with DN, albuminuria, or MA have higher NLR, as compared with those without DN, albuminuria, or with MIA, which indicated that NLR plays an important role in the development and progression of DN.

It has also been demonstrated that chronic inflammation plays an important role in the development of DR with the help of various systemic and local (vitreous and aqueous fluids) inflammatory factors [82–85]. Neutrophils may contribute to the development and progression of microangiopathy and inflammation, when they adhere to the endothelial cell wall [86,87]. A study by Woo et al. [88] showed that neutrophil count in circulation was higher in patients with DR, and was closely associated with DR grades, indicating the considerable role of neutrophil-mediated inflammation in the development and progression of DR. Furthermore, several recent literatures have proposed that NLR, as a novel inflammation marker, was found to be higher in patients with DR and linked with the severity of DR [13,18,61,88,89]. However, in a study by Ciray et al. [79], NLR was not found to be associated with the pathogenesis of DR. In our meta-analysis, it was observed that NLR might be involved in the presence of DR, but not linked with the DR grade, indicating that NLR might only play a role in the early stage of DR. However, only four studies with the low number of cases were in place for the meta-analysis of the association between NLR and the DR grade. Therefore, the role of NLR in the later stage of DR remains controversial and further studies are in need to figure out this issue.

Albuminuria can lead to some changes in the levels of numerous biomarkers in blood circulation, which could be applied to diagnosis and the risk evaluation of progression of kidney diseases [90,91]. Several studies have shown that MPV and PDW values are higher in DM patients with DN when compared with those without DN. Similarly, our meta-analysis also demonstrated that DM patients with DN have increased level of MPV than those without DN. These results indicated that MPV and PDW values could be used for the diagnosis of DN. Furthermore, a few studies showed that the MPV values increased with DN stage proceeding, which suggested that MPV could be applied to determine the stage of DN and monitoring the progress of DN. Certainly, the exact causal association of MPV and PDW with DN need to be further explored, which will help physicians make full use of MPV and PDW in clinical practices.

It has been demonstrated that persistent presence of hyperglycemia, dyslipidemia, and insulin resistance could lead to endothelial and pericyte injury, which leaves DM patients in a ‘prothrombotic condition’ [92]. Furthermore, the morphologic and functional forms of platelets, which are related to enhanced platelet activity, were found to be increased in patients with DM [92]. Platelets with higher MPV value have more metabolic and enzymatic activities than the lower and produce more thromboxan-A2, b-thromboglobulin, and adhesion molecules releasing [19,20], which implicated that MPV might be connected with elevated thrombotic potential. In consistence with numerous studies focussing on the correlation of MPV with DR, this meta-analysis also showed that increased MPV was associated with the presence of DR and its severity. In addition, PDW is a parameter reflecting the variability of platelet size, and its high value indicated increased production of larger reticulated platelet, indicating that PDW value, similar to MPV, is closely linked with thrombotic potential. Consistently, from the results of meta-analysis, we found that higher PDW was related to the presence of DR, but there were no differences in PDW between patients with NPDR and PDR. Considering that only five studies were available for the meta-analysis of the relationship of PDW to the severity of DR, the small sample size might partly account for the negative association of PDW with the severity of DR. Thus, further studies are needed to further explore the correlation between PDW and the severity of DR.

When interpreting the results of the present study, several limitations should be taken into consideration. First, although random-effect model was applied, significant heterogeneity amongst studies was still observed. It might be attributed to differences in some characteristics of the included studies including age, ethnicity, diseases’ duration, and body mass index, in detecting instrument, in experimental designs and in quality of the included studies. Second, the number of included studies was insufficient for a persuasive meta-analysis of the association of NLR, MPV, and PDW with the DR grade. Third, the standard of the stage of DR/DN with T2DM patients was not uniform and may affect the results. Finally, this meta-analysis did not investigate the relationship of the NLR, MPV, and PDW to other factors that may influence the development of DR/DN, due to the lack of available data in the included studies.

In conclusion, this meta-analysis indicated that NLR MPV and PDW has a positive association with DN and DR. Furthermore, MPV is closely related to the severity of DR and DN. NLR, MPV, and PDW could be recommended as inexpensive diagnostic markers for DN and DR, and even antiplatelet agents might be effective to control the development of DN and DR. However, further high-quality clinical studies should be performed to investigate the relationship of NLR, MPV, and PDW to DN and DR.

Competing interests

The authors declare that there are no competing interests associated with the manuscript.

Author contribution

J.L. designed the study, interpreted the results,and finally approved the manuscript. JX.L. and LG.L. drafted the manuscript. YP.L. JX.Q. and SH.W. searched the literature, extracted data, and made the statistical analysis. SQ.A. and RF.Y. assessed the study quality.

Funding

This work was supported by the National Natural Science Foundation of China [grant numbers 81560146, 81660148, 81760151].

Abbreviations

     
  • CI

    confidence interval

  •  
  • DM

    diabetes mellitus

  •  
  • DN

    diabetic nephropathy

  •  
  • DR

    diabetic retinopathy

  •  
  • MA

    macroalbuminuria

  •  
  • MIA

    microalbuminuria

  •  
  • MPV

    mean platelet volume

  •  
  • NLR

    neutrophil to lymphocyte ratio

  •  
  • NOS

    Newcastle–Ottawa scale

  •  
  • NPDR

    non-proliferative DR

  •  
  • PDW

    platelet distribution width

  •  
  • PDR

    proliferative DR

  •  
  • SD

    sufficient data

  •  
  • SMD

    standardized mean difference

  •  
  • T2DM

    type Ⅱ DM

References

References
1
Pan
S.
,
Liu
Z.W.
,
Shi
S.
,
Ma
X.
,
Song
W.Q.
,
Guan
G.C.
et al. 
(
2017
)
Hamilton rating scale for depression-24 (HAM-D24) as a novel predictor for diabetic microvascular complications in type 2 diabetes mellitus patients
.
Psychiatry Res.
258
,
177
183
[PubMed]
2
Niu
W.
and
Qi
Y.
(
2012
)
An updated meta-analysis of methylenetetrahydrofolate reductase gene 677C/T polymorphism with diabetic nephropathy and diabetic retinopathy
.
Diabetes Res. Clin. Pract.
95
,
110
118
[PubMed]
3
Lee
R.
,
Wong
T.Y.
and
Sabanayagam
C.
(
2015
)
Epidemiology of diabetic retinopathy, diabetic macular edema and related vision loss
.
Eye Vis. (Lond.)
2
,
17
[PubMed]
4
Moon
J.
,
Lee
C.J.
,
Lee
S.H.
,
Kang
S.M.
,
Choi
D.
,
Yoo
T.H.
et al. 
(
2017
)
The impact of diabetes mellitus on vascular biomarkers in patients with end-stage renal disease
.
Yonsei Med. J.
58
,
75
81
[PubMed]
5
Ritz
E.
,
Rychlik
I.
,
Locatelli
F.
and
Halimi
S.
(
1999
)
End-stage renal failure in type 2 diabetes: a medical catastrophe of worldwide dimensions
.
Am. J. Kidney Dis.
34
,
795
808
[PubMed]
6
Schmidt
M.I.
,
Duncan
B.B.
,
Sharrett
A.R.
,
Lindberg
G.
,
Savage
P.J.
,
Offenbacher
S.
et al. 
(
1999
)
Markers of inflammation and prediction of diabetes mellitus in adults (Atherosclerosis Risk in Communities study): a cohort study
.
Lancet
353
,
1649
1652
[PubMed]
7
Pitsavos
C.
,
Tampourlou
M.
,
Panagiotakos
D.B.
,
Skoumas
Y.
,
Chrysohoou
C.
,
Nomikos
T.
et al. 
(
2007
)
Association between low-grade systemic inflammation and type 2 diabetes mellitus among men and women from the ATTICA Study
.
Rev. Diabet. Stud.
4
,
98
104
[PubMed]
8
Shoelson
S.E.
,
Lee
J.
and
Goldfine
A.B.
(
2006
)
Inflammation and insulin resistance
.
J. Clin. Invest.
116
,
1793
1801
[PubMed]
9
Stringhini
S.
,
Batty
G.D.
,
Bovet
P.
,
Shipley
M.J.
,
Marmot
M.G.
,
Kumari
M.
et al. 
(
2013
)
Association of lifecourse socioeconomic status with chronic inflammation and type 2 diabetes risk: the Whitehall II prospective cohort study
.
PLoS Med.
10
,
e1001479
[PubMed]
10
Tang
J.
and
Kern
T.S.
(
2011
)
Inflammation in diabetic retinopathy
.
Prog. Retin. Eye Res.
30
,
343
358
[PubMed]
11
Kern
T.S.
(
2007
)
Contributions of inflammatory processes to the development of the early stages of diabetic retinopathy
.
Exp. Diabetes Res.
2007
,
95103
[PubMed]
12
Semeraro
F.
,
Cancarini
A.
,
dell’Omo
R.
,
Rezzola
S.
,
Romano
M.R.
and
Costagliola
C.
(
2015
)
Diabetic retinopathy: vascular and inflammatory disease
.
J. Diabetes Res.
2015
,
582060
[PubMed]
13
Ulu
S.M.
,
Dogan
M.
,
Ahsen
A.
,
Altug
A.
,
Demir
K.
,
Acarturk
G.
et al. 
(
2013
)
Neutrophil-to-lymphocyte ratio as a quick and reliable predictive marker to diagnose the severity of diabetic retinopathy
.
Diabetes Technol. Ther.
15
,
942
947
[PubMed]
14
Solak
Y.
,
Yilmaz
M.I.
,
Sonmez
A.
,
Saglam
M.
,
Cakir
E.
,
Unal
H.U.
et al. 
(
2013
)
Neutrophil to lymphocyte ratio independently predicts cardiovascular events in patients with chronic kidney disease
.
Clin. Exp. Nephrol.
17
,
532
540
[PubMed]
15
Ghaffari
S.
,
Nadiri
M.
,
Pourafkari
L.
,
Sepehrvand
N.
,
Movasagpoor
A.
,
Rahmatvand
N.
et al. 
(
2014
)
The predictive value of total neutrophil count and neutrophil/lymphocyte ratio in predicting in-hospital mortality and complications after STEMI
.
J. Cardiovasc. Thorac. Res.
6
,
35
41
[PubMed]
16
Zhang
J.
,
Zhang
H.Y.
,
Li
J.
,
Shao
X.Y.
and
Zhang
C.X.
(
2017
)
The elevated NLR, PLR and PLT may predict the prognosis of patients with colorectal cancer: a systematic review and meta-analysis
.
Oncotarget
8
,
68837
68846
[PubMed]
17
Demirtas
L.
,
Degirmenci
H.
,
Akbas
E.M.
,
Ozcicek
A.
,
Timuroglu
A.
,
Gurel
A.
et al. 
(
2015
)
Association of hematological indicies with diabetes, impaired glucose regulation and microvascular complications of diabetes
.
Int. J. Clin. Exp. Med.
8
,
11420
11427
[PubMed]
18
Wang
R.T.
,
Zhang
J.R.
,
Li
Y.
,
Liu
T.
and
Yu
K.J.
(
2015
)
Neutrophil-Lymphocyte ratio is associated with arterial stiffness in diabetic retinopathy in type 2 diabetes
.
J. Diabetes Complications
29
,
245
249
[PubMed]
19
Kamath
S.
,
Blann
A.D.
and
Lip
G.Y.
(
2001
)
Platelet activation: assessment and quantification
.
Eur. Heart J.
22
,
1561
1571
[PubMed]
20
Chu
S.G.
,
Becker
R.C.
,
Berger
P.B.
,
Bhatt
D.L.
,
Eikelboom
J.W.
,
Konkle
B.
et al. 
(
2010
)
Mean platelet volume as a predictor of cardiovascular risk: a systematic review and meta-analysis
.
J. Thromb. Haemost.
8
,
148
156
[PubMed]
21
Tetikoğlu
M.
,
Aktas
S.
,
Sagdık
H.M.
,
Yigitoglu
S.T.
and
Özcura
F.
(
2016
)
Mean platelet volume is associated with diabetic macular edema in patients with type-2 diabetes mellitus
.
Semin. Ophthalmol.
32
,
651
654
22
Yue
S.
,
Zhang
J.
,
Wu
J.
,
Teng
W.
,
Liu
L.
and
Chen
L.
(
2015
)
Use of the monocyte-to-lymphocyte ratio to predict diabetic retinopathy
.
Int. J. Environ. Res. Public Health
12
,
10009
10019
23
Citirik
M.
,
Beyazyildiz
E.
,
Simsek
M.
,
Beyazyildiz
O.
and
Haznedaroglu
I.C.
(
2015
)
MPV may reflect subcinical platelet activation in diabetic patients with and without diabetic retinopathy
.
Eye
29
,
376
379
[PubMed]
24
Moher
D.
,
Liberati
A.
,
Tetzlaff
J.
,
Altman
D.G.
and
Group
P.
(
2010
)
Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement
.
Int. J. Surg.
8
,
336
341
[PubMed]
25
Stang
A.
(
2010
)
Critical evaluation of the Newcastle-Ottawa scale for the assessment of the quality of nonrandomized studies in meta-analyses
.
Eur. J. Epidemiol.
25
,
603
605
[PubMed]
26
Begg
C.B.
and
Mazumdar
M.
(
1994
)
Operating characteristics of a rank correlation test for publication bias
.
Biometrics
50
,
1088
1101
[PubMed]
27
Egger
M.
,
Davey Smith
G.
,
Schneider
M.
and
Minder
C.
(
1997
)
Bias in meta-analysis detected by a simple, graphical test
.
BMJ
315
,
629
634
[PubMed]
28
Duval
S.
and
Tweedie
R.
(
2000
)
Trim and fill: a simple funnel-plot-based method of testing and adjusting for publication bias in meta-analysis
.
Biometrics
56
,
455
463
[PubMed]
29
Akbas
E.M.
,
Demirtas
L.
,
Ozcicek
A.
,
Timuroglu
A.
,
Bakirci
E.M.
,
Hamur
H.
et al. 
(
2014
)
Association of epicardial adipose tissue, neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio with diabetic nephropathy
.
Int. J. Clin. Exp. Med.
7
,
1794
1801
[PubMed]
30
Ao
X.
(
2017
)
Study of the relationship between neutrophil to lymphocyte ratio and renal function impairment in diabetic nephropathy
.
Chin. J. Prev. Contr. Chron. Dis.
25
708
711
,
31
Bavbek
N.
,
Kargili
A.
,
Kaftan
O.
,
Karakurt
F.
,
Kosar
A.
and
Akcay
A.
(
2007
)
Elevated concentrations of soluble adhesion molecules and large platelets in diabetic patients: are they markers of vascular disease and diabetic nephropathy?
Clin. Appl. Thromb. Hemost.
13
,
391
397
[PubMed]
32
Buch
A.
,
Kaur
S.
,
Nair
R.
and
Jain
A.
(
2017
)
Platelet volume indices as predictive biomarkers for diabetic complications in Type 2 diabetic patients
.
J. Lab. Physicians
9
,
84
88
33
Ciray
H.
,
Aksoy
A.H.
,
Ulu
N.
,
Cizmecioglu
A.
,
Gaipov
A.
and
Solak
Y.
(
2015
)
Nephropathy, but not angiographically proven retinopathy, is associated with neutrophil to lymphocyte ratio in patients with type 2 diabetes
.
Exp. Clin. Endocrinol. Diabetes
123
,
267
34
Cui
X.
(
2006
)
Changes of blood lipids and platelet parameters in patients with type 2 diabetic nephropathy and its significance
.
Clin. Med.
26
,
79
80
35
Dindar
S.
,
Cinemre
H.
,
Sengul
E.
and
Annakkaya
A.N.
(
2013
)
Mean platelet volume is associated with glycaemic control and retinopathy in patients with type 2 diabetes mellitus
.
West Indian Med. J.
62
,
519
[PubMed]
36
Feng
R.
,
Liu
T.
,
Wang
N.
and
Liu
J.
(
2016
)
Correlation between neutrophil/lymphocyte ratio, platelet / lymphocyte ratio and diabetic nephropathy
.
Chin. J. Clin. Res.
29
,
1205
1207
37
Huang
W.
,
Huang
J.
,
Liu
Q.
,
Lin
F.
,
He
Z.
,
Zeng
Z.
et al. 
(
2015
)
Neutrophil–lymphocyte ratio is a reliable predictive marker for early‐stage diabetic nephropathy
.
Clin. Endocrinol. (Oxf.)
82
,
229
233
[PubMed]
38
Kahraman
C.
,
Kahraman
N.K.
,
Aras
B.
,
Coşgun
S.
and
Gülcan
E.
(
2016
)
The relationship between neutrophil-to-lymphocyte ratio and albuminuria in type 2 diabetic patients: a pilot study
.
Arch. Med. Sci.
12
,
571
575
39
Khandare
S.A.
,
Chittawar
S.
,
Nahar
N.
,
Dubey
T.N.
and
Qureshi
Z.
(
2017
)
Study of neutrophil-lymphocyte ratio as novel marker for diabetic nephropathy in type 2 diabetes
.
Indian J. Endocrinol. Metab.
21
,
387
40
Levent
D.
,
Husnu
D.
,
Emin Murat
A.
,
Adalet
O.
,
Aysu
T.
,
Ali
G.
et al. 
(
2015
)
Association of hematological indicies with diabetes, impaired glucose regulation and microvascular complications of diabetes
.
Int. J. Clin. Exp. Med.
8
,
11420
11427
[PubMed]
41
Liang
S.
,
Mo
W.
and
Ye
X.
(
2008
)
Changes of blood lipids and platelet parameters in diabetic nephropathy
.
Hebei Med.
14
,
801
804
42
Ü
M.
,
Ayhan
M.
and
Güney
E.
(
2012
)
The relationship between mean platelet volume with microalbuminuria and glycemic control in patients with type II diabetes mellitus
.
Platelets
23
,
475
480
[PubMed]
43
Ma
X.
,
M
C.
,
Wang
F.
and
Yang
M.
(
2007
)
Changes of the blood platelet and blood lipids in diabetic nephropathy
.
Transl. Med. J.
20
,
211
213
44
Ren
H.
,
Liu
J.
,
Wu
X.
,
Zhao
W.
,
Zhang
X.
,
Zhu
S.
et al. 
(
2015
)
Study on the relationship between neutrophil-to-lymphocyte ratio of peripheral blood and the type 2 diabetic nephropathy
.
Med. Innov. China
12
,
9
12
45
Sun
Q.
and
Wen
Q.
(
2007
)
The volume change of blood cells in diabetic nephropathy and its clinical significance
.
China Med. Herald
4
,
20
21
46
Tian
Y.
,
Lu
Q.
,
Yin
F.
,
Li
T.
,
Gu
H.
,
Wang
R.
et al. 
(
2017
)
Relationship between neutrophil-to-lymphocyte ratio and urine-to-creatinine ration in patients with type 2 diabetes mellitus
.
J. Med. Postgra.
30
,
1061
1064
47
Turgutalp
K.
,
Özhan
O.
,
Akbay
E.
,
Tombak
A.
,
Tiftik
N.
,
Ozcan
T.
et al. 
(
2014
)
Mean platelet volume and related factors in patients at different stages of diabetic nephropathy: a preliminary study
.
Clin. Appl. Thromb. Hemost.
20
,
190
48
Xu
X.
,
Zhong
X.
and
Pan
T.
(
2016
)
Relationship between neutrophil-to-lymphocyte ratio and early-stage diabetic nephropathy patients with newly diagnosed type 2 diabetes
.
Chin. J. Diabetes
24
,
598
600
49
Zhu
Y.
,
He
L.
,
Tang
J.
,
Li
Q.
and
Kang
Z.
(
2016
)
Clinic significance of neutrophil lymphocyte ratio in patients with type 2 diabetic nephropathy
.
Med. Philos.
37
,
33
34
50
Akdogan
M.
,
Ustundag-Budak
Y.
and
Huysal
K.
(
2016
)
The association of hematologic inflammatory markers with atherogenic index in type 2 diabetic retinopathy patients
.
Clin. Ophthalmol.
10
,
1797
1801
[PubMed]
51
Ateş
O.
,
Kiki
İ
,
Bilen
H.
,
Keleş
M.
,
Koçer
İ
,
Kulaçoğlu
D.N.
et al. 
(
2010
)
Association of mean platelet volume with the degree of retinopathy in patients with diabetes mellitus
.
Eur. J. General Med.
99
102
52
Ayhan Tuzcu
E.
,
Arica
S.
,
Ilhan
N.
,
Daglioglu
M.
,
Coskun
M.
,
Ilhan
O.
et al. 
(
2014
)
Relationship between mean platelet volume and retinopathy in patients with type 2 diabetes mellitus
.
Graefes Arch. Clin. Exp. Ophthalmol.
252
,
237
240
[PubMed]
53
Demirtas
L.
,
Degirmenci
H.
,
Akbas
E.M.
,
Ozcicek
A.
,
Timuroglu
A.
,
Gurel
A.
et al. 
(
2015
)
Association of hematological indicies with diabetes, impaired glucose regulation and microvascular complications of diabetes
.
Int. J. Clin. Exp. Med.
8
,
11420
11427
[PubMed]
54
Güngör
A.A.
,
Gürsoy
G.
,
Güngör
F.
,
Bayram
S.M.
and
Atalay
E.
(
2016
)
The relationship of mean platelet volume with retinopathy in type 2 diabetes mellitus
.
Turkish J. Med. Sciences
46
,
1292
55
Kuang
X.
and
Wang
S.
(
2015
)
Relationship of serum neutrophil-to-lymphocyte ratio with diabetic retinopathy
.
Chin. J. Diabetes
,
23
438
440
56
Li
H.
,
Bi
C.
and
Qu
C.
(
2014
)
Relationship between mean platelet volume and development of diabetic retinopathy: a cross-sectional study
.
Rec. Adv. Ophthalmol.
34
,
766
768
57
Li
J.
,
Chen
K.
,
Chen
W.
,
Zhang
K.
and
Deng
S.
(
2013
)
Changes and significance of mean platelet volume in patients with type 2 diabetes mellitus
.
Chongqing Med.
42
,
1742
1744
58
Li
S.
,
Cao
W.
and
Sun
X.
(
2016
)
Role of platelet parameters on neovascular glaucoma: a retrospective case-control study in China
.
PLoS ONE
11
,
e0166893
[PubMed]
59
Ma
F.
and
Zhang
Y.
(
2017
)
Changes and clinical significance of platelet activation and four platelet parameters in diabetic retinopathy
.
Rec. Adv. Ophthalmol.
37
,
164
166
60
Niu
S.
(
2013
)
Changes of HbAlc, FPG and platelet parameters in patients with diabetic retinopathy and risk factors
.
Rec. Adv. Ophthalmol.
33
,
655
657
61
Ozturk
Z.A.
,
Kuyumcu
M.E.
,
Yesil
Y.
,
Savas
E.
,
Yildiz
H.
,
Kepekci
Y.
et al. 
(
2013
)
Is there a link between neutrophil-lymphocyte ratio and microvascular complications in geriatric diabetic patients?
J. Endocrinol. Invest.
36
,
593
599
[PubMed]
62
Papanas
N.
,
Symeonidis
G.
,
Maltezos
E.
,
Mavridis
G.
,
Karavageli
E.
,
Vosnakidis
T.
et al. 
(
2004
)
Mean platelet volume in patients with type 2 diabetes mellitus
.
Platelets
15
,
475
478
[PubMed]
63
Radha
R.K.N.
and
Selvam
D.
(
2016
)
MPV in uncontrolled & controlled diabetics- its role as an indicator of vascular complication
.
J. Clin. Diagn. Res.
10
,
EC22
EC26
64
Shen
J.
,
Zhang
Q.
,
Li
M.
,
Xie
S.
,
Niu
M.
and
Wang
Y.
(
2016
)
Association between neutrophil-to-lymphocyte ratio and diabetic retinopathy
.
Chin. J. Diabetes
24
,
617
621
65
Sheng
X.
,
Xie
Q.
,
Liu
C.
,
Liu
W.
and
Fu
L.
(
2017
)
Changes of blood glucose and coagulation parameters in patients with diabetic retinopathy
.
Chin. J. Modern Med.
27
,
133
136
66
Ulu
S.M.
,
Dogan
M.
,
Ahsen
A.
,
Altug
A.
,
Demir
K.
,
Acartürk
G.
et al. 
(
2013
)
Neutrophil-to-lymphocyte ratio as a quick and reliable predictive marker to diagnose the severity of diabetic retinopathy
.
Diabetes Technol. Ther.
15
,
942
947
67
Wei
Y.
,
Guan
S.
,
Zhou
Q.
and
Yang
K.
(
2017
)
Platelet-to-lymphocyte ratio as potential biomarker in the diagnosis of diabetic retinopathy
.
Acta Univ. Med. Anhui
52
,
409
411
68
Xu
W.
,
Cai
Y.
and
Wang
C.
(
2012
)
Study on clinical significance of changes in MPV and HbAlc in patients with diabetic retinopathy
.
J. Clin. Exp. Med.
11
,
584
585
69
Yilmaz
T.
and
Yilmaz
A.
(
2016
)
Relationship between altered platelet morphological parameters and retinopathy in patients with type 2 diabetes mellitus
.
J. Ophthalmology
2016
,
1
5
70
Yin
Q.
,
Guo
S.
,
Zhang
Y.
,
Wang
J.
,
Ma
Z.
,
Ti
S.
et al. 
(
2015
)
Changes and significance of neutrophil-lymphocyte ratio in patients with type 2 diabetes and retinopathy
.
Chin. J. Microcirculation
46
49
71
Yu
N.
,
Qiu
W.
and
Jiang
L.
(
2000
)
Relationship between diabetic retinopathy and platelet volume
.
J. Pract. Diabetol.
2
,
33
34
72
Zhang
Y.
,
Liu
J.
and
Shang
G.
(
2002
)
Clinical analysis for mean platelet volume, mean red cells volume in diabetic retinopathy patients
.
J. Clin. Ophthalmol.
10
,
52
53
73
Zhou
X.
,
Liu
Q.
,
Bau
H.
and
Liang
L.
(
2016
)
Clinical significance of mean platelet volume and neutrophil-to-lymphocyte ratio in patients with diabetic retinopathy
.
Int. Eye Sci.
16
,
981
983
74
Okyay
G.U.
,
Inal
S.
,
Onec
K.
,
Er
R.E.
,
Pasaoglu
O.
,
Pasaoglu
H.
et al. 
(
2013
)
Neutrophil to lymphocyte ratio in evaluation of inflammation in patients with chronic kidney disease
.
Ren. Fail.
35
,
29
36
[PubMed]
75
Kahraman
C.
,
Kahraman
N.K.
,
Aras
B.
,
Cosgun
S.
and
Gulcan
E.
(
2016
)
The relationship between neutrophil-to-lymphocyte ratio and albuminuria in type 2 diabetic patients: a pilot study
.
Arch. Med. Sci.
12
,
571
575
[PubMed]
76
Navarro
J.F.
and
Mora
C.
(
2005
)
Role of inflammation in diabetic complications
.
Nephrol. Dial. Transplant.
20
,
2601
2604
[PubMed]
77
Rivero
A.
,
Mora
C.
,
Muros
M.
,
Garcia
J.
,
Herrera
H.
and
Navarro-Gonzalez
J.F.
(
2009
)
Pathogenic perspectives for the role of inflammation in diabetic nephropathy
.
Clin. Sci. (Lond.)
116
,
479
492
[PubMed]
78
Azab
B.
,
Daoud
J.
,
Naeem
F.B.
,
Nasr
R.
,
Ross
J.
,
Ghimire
P.
et al. 
(
2012
)
Neutrophil-to-lymphocyte ratio as a predictor of worsening renal function in diabetic patients (3-year follow-up study)
.
Ren. Fail.
34
,
571
576
[PubMed]
79
Ciray
H.
,
Aksoy
A.H.
,
Ulu
N.
,
Cizmecioglu
A.
,
Gaipov
A.
and
Solak
Y.
(
2015
)
Nephropathy, but not angiographically proven retinopathy, is associated with neutrophil to lymphocyte ratio in patients with type 2 diabetes
.
Exp. Clin. Endocrinol. Diabetes
123
,
267
271
[PubMed]
80
Huang
W.
,
Huang
J.
,
Liu
Q.
,
Lin
F.
,
He
Z.
,
Zeng
Z.
et al. 
(
2015
)
Neutrophil-lymphocyte ratio is a reliable predictive marker for early-stage diabetic nephropathy
.
Clin. Endocrinol. (Oxf.)
82
,
229
233
[PubMed]
81
Khandare
S.A.
,
Chittawar
S.
,
Nahar
N.
,
Dubey
T.N.
and
Qureshi
Z.
(
2017
)
Study of neutrophil-lymphocyte ratio as novel marker for diabetic nephropathy in type 2 diabetes
.
Indian J. Endocrinol. Metab.
21
,
387
392
[PubMed]
82
Lim
L.S.
,
Tai
E.S.
,
Mitchell
P.
,
Wang
J.J.
,
Tay
W.T.
,
Lamoureux
E.
et al. 
(
2010
)
C-reactive protein, body mass index, and diabetic retinopathy
.
Invest. Ophthalmol. Vis. Sci.
51
,
4458
4463
[PubMed]
83
Nowak
M.
,
Wielkoszynski
T.
,
Marek
B.
,
Kos-Kudla
B.
,
Swietochowska
E.
,
Sieminska
L.
et al. 
(
2010
)
Antioxidant potential, paraoxonase 1, ceruloplasmin activity and C-reactive protein concentration in diabetic retinopathy
.
Clin. Exp. Med.
10
,
185
192
[PubMed]
84
van Hecke
M.V.
,
Dekker
J.M.
,
Nijpels
G.
,
Moll
A.C.
,
Heine
R.J.
,
Bouter
L.M.
et al. 
(
2005
)
Inflammation and endothelial dysfunction are associated with retinopathy: the Hoorn Study
.
Diabetologia
48
,
1300
1306
[PubMed]
85
Kastelan
S.
,
Tomic
M.
,
Gverovic Antunica
A.
,
Salopek Rabatic
J.
and
Ljubic
S.
(
2013
)
Inflammation and pharmacological treatment in diabetic retinopathy
.
Mediators Inflamm.
2013
,
213130
[PubMed]
86
Fujita
T.
,
Hemmi
S.
,
Kajiwara
M.
,
Yabuki
M.
,
Fuke
Y.
,
Satomura
A.
et al. 
(
2013
)
Complement-mediated chronic inflammation is associated with diabetic microvascular complication
.
Diabetes Metab. Res. Rev.
29
,
220
226
[PubMed]
87
Sala
A.
and
Folco
G.
(
2001
)
Neutrophils, endothelial cells, and cysteinyl leukotrienes: a new approach to neutrophil-dependent inflammation?
Biochem. Biophys. Res. Commun.
283
,
1003
1006
[PubMed]
88
Woo
S.J.
,
Ahn
S.J.
,
Ahn
J.
,
Park
K.H.
and
Lee
K.
(
2011
)
Elevated systemic neutrophil count in diabetic retinopathy and diabetes: a hospital-based cross-sectional study of 30,793 Korean subjects
.
Invest. Ophthalmol. Vis. Sci.
52
,
7697
7703
[PubMed]
89
Yue
S.
,
Zhang
J.
,
Wu
J.
,
Teng
W.
,
Liu
L.
and
Chen
L.
(
2015
)
Use of the monocyte-to-lymphocyte ratio to predict diabetic retinopathy
.
Int. J. Environ. Res. Public Health
12
,
10009
10019
[PubMed]
90
Ghanny
S.
,
Ross
C.
,
Chan
A.K.
and
Chan
H.H.
(
2010
)
Coagulopathy in a patient with nephrotic syndrome
.
Am. J. Hematol.
85
,
708
710
[PubMed]
91
Rodriguez Villarreal
I.
,
Ortega
O.
,
Gallar
P.
,
Sanchez
M.
,
Callejas
R.
,
Gracia
C.
et al. 
(
2011
)
Clinical and biochemical characteristics of predialysis patients in terms of 25 hydroxy vitamin D levels
.
Nefrologia
31
,
185
191
[PubMed]
92
Ferroni
P.
,
Basili
S.
,
Falco
A.
and
Davi
G.
(
2004
)
Platelet activation in type 2 diabetes mellitus
.
J. Thromb. Haemost.
2
,
1282
1291
[PubMed]

Author notes

*

These authors contributed equally to this work.

This is an open access article published by Portland Press Limited on behalf of the Biochemical Society and distributed under the Creative Commons Attribution License 4.0 (CC BY).