Systemic immune inflammatory index (SII) and urine albumin creatinine ratio (ACR) are associated with Diabetic macular epiretinal membrane

doi:10.21203/rs.3.rs-3974407/v1

Purpose

To investigate the correlation between systemic immune inflammatory index (SII) or other metabolic index and diabetic macular epiretinal membrane (dERM) in hospitalized patients with diabetes mellitus (DM).

Methods

This retrospective study included 81 dERM inpatients and other 81 matched controls. Main indicators involved in comparison between group were macular volume coefficient, Body Mass Index (BMI), insulin usage rate, hypertension prevalence, SII, albumin (Alb), lipid indicators, uric acid, glycated hemoglobin and urine albumin creatinine ratio (ACR). Conditional logistic regression analysis was operated to evaluate the risk factors for dERM occurrence. Spearman correlation test was conducted to analyze the correlation between the above indicators in the dERM group and their Optical coherence tomography biomarkers.

Results

Each of macular volume coefficients, SII and ACR in the dERM group was significantly higher than those in the control group while Alb decreased (all p < 0.05). There was no significant difference in the rest of indicators between the two groups. Regression analysis predicted risk factors as SII (OR 3.92, 95% CI 1.90–9.65, p < 0.01) and ACR (OR 4.43, 95%CI 1.89–10.42, p < 0.01). Correlation analysis showed that hyperreflective foci (HRF), intraretinal cystoid space (IRC), and disorganization of retinal inner layers (DRIL) were all related to the thickness of the macular fovea. In addition, HRF showed a significant correlation with SII and ACR. IRC were also related to ACR, excepted DRIL.

Conclusion

Higher SII and ACR are closely related to dERM among DM hospitalized patients.

diabetes mellitus

macular epiretinal membrane

Systemic immune inflammation index

Optical coherence tomography

Epiretinal membrane (ERM) is an avascular fibrous membrane that occurs on the surface of the inner limiting membrane (ILM) of the macular area[1]. ERM is one of the most common macular diseases causing visual impairment and metamorphopsia, and is estimated to affect approximate 9.1% of ageing patients worldwide[1; 2]. In clinical practice, nearly 80% of ERM is idiopathic, and its pathogenesis has not yet been elucidated[3]. While in secondary ERM, diabetes mellitus (DM) and diabetic retinopathy (DR) are regarded as strong risk factors. Over one-fifth patients with DM, and approximately 6% with DR were observed in ERM patients[46].

Compared to idiopathic ERM, ERM combined with DM has about twice thickening of the ILM and tends to be more significant in macular circulation and inner microstructure changes[7]. Some scholars call REM with DM or DR as diabetic macular epiretinal membrane (dERM), which can lead to stubborn diabetes macular edema (DME) and indicate an unsatisfactory response to anti-vascular endothelial growth factor (VEGF) therapy and a poor prognosis[810].

With the introduction of spectral-domain optical coherence tomography (SD-OCT), a non-invasive, quick and convenient retinal imaging modality with in-depth cross-sectional data, the sensitivity to detect fundus diseases has been significantly improved. In recent years, there has been a growing focus on the clinical significance of various OCT biomarkers, extending beyond the realm of disease diagnosis to encompass prognosis and treatment efficacy assessment[11]. In the exploration of the etiology of DR or DME, the scope has expanded from intraocular inflammatory cytokines to encompass systemic inflammatory indices and other laboratory parameters[1215].

For example, systemic immune inflammatory index (SII) is a new composite systemic immune inflammation index proposed by Hu et al. in 2014, which combines peripheral blood neutrophil, lymphocyte, and platelet counts[16]. Compared to traditional inflammatory indicators such as interleukin-6 and immunoglobulin, SII is economically accessible. Previous studies shed light on the association between SII and some OCT biomarkers in DME, such as subretinal fluid and hyperreflective foci (HRF)[15]. However, few studies focused on the correlation of systemic laboratory tests and ILM status.

Given the current opinion of the great importance of dERM in DME prognosis, this study aims to analyze the correlation between systemic inflammation, nutritional metabolism indicators, and the occurrence of dERM. It may deepen our understanding of OCT biomarkers, providing a more comprehensive insight into diabetic fundus complications and potential implications for intervention strategies.

This was a retrospective, observational, case-controlled study carried out in Affiliated Jinhua Hospital of Zhejiang University School of Medicine from March 2022 to July 2023. It was based on clinical data of DM inpatients who accepted fundus screening in the Ophthalmology Department. This study was performed in accordance with the principles of the Helsinki Declaration and approved by the Ethics Committee of Affiliated Jinhua Hospital of Zhejiang University School of Medicine (Approval Number: 2023-18, retrospectively registered).

Research subjects

Inclusion criteria included (1) age equal to or greater than 18 years old; (2) diagnosed with DM, either type 1 or 2; (3) first confirmed ERM according to fundus screening images include fundus photography and OCT examination; (4) For patients with binocular diseases, the more severe eye shall be encompassed within the study, while for those with comparable status, the right eye will be selected.

Exclusion criteria included (1) previous history of fundus surgery such as intravitreal injection, vitrectomy, or retinal laser surgery; (2) other eye surgeries within 6 months, such as cataract surgery; (3) combined with identified vitreoretinal diseases, such as retinal vein occlusion, proliferative diabetes retinopathy, etc. (4) prolonged utilization of immunosuppressants and hormones in combination with severe hematological disorders, severe liver and kidney dysfunction, or a history of malignant tumors; (6) fever, systemic infection, and infectious disease within 2 weeks; (7) suboptimal image quality for diagnosis or examinations missing.

The control group was matched based on admission time, age, gender and duration of DM, which might affect our results. Their eyes were screened without dERM and DME, and OCT parameters of right eye were included for comparison.

Clinical data collection

General clinical data were collected from the electronic medical record system, including gender, age, duration of DM, Body Mass Index (BMI), medication history of insulin, and whether hypertension is present.

All patients received venous blood from the elbow for relevant laboratory tests, including blood routine (blood cell analyzer SYSMEXXN-10), counting of peripheral blood neutrophils, lymphocytes, and platelets. Routine biochemical tests (automatic biochemical analyzer, Beckman AU5831/AU5821) detected serum albumin (Alb), blood lipid routine, and uric acid (UA) levels. The concentration of glycosylated hemoglobin (HbA1c) was measured by the fully automated glycosylated hemoglobin analyzer (BIORAD-100). Random urine samples are taken for albumin creatinine ratio (ACR) detection (fully automated specific protein analyzer, Biosystems BA400).

The formula for calculating the systemic immune inflammation index (SII) was shown as following:

SII = platelet count × Neutrophil count/lymphocyte count[16]

According to Working Group on Obesity in China, overweight was defined as 24 ≤ BMI < 28 kg/m2, and BMI ≥ 28 kg/m2 as obesity[17]. In addition, hyperlipidemia was defined as total cholesterol (TC) ≥ 5.72 mmol/L and/or triglycerides (TG) ≥ 1.70 mmol/L, or high-density lipoprotein cholesterol (HDL-C) < 0.90 mmol/L, or use of lipid-lowering medications[18]. Hyperuricemia was defined as UA ≥ 420 µmol/L in males or ≥ 360 µmol/L in females[19].

OCT biomarkers evaluation

OCT inspection adopted Cirrus HD-OCT5000 (Carl Zeiss), with a macular cube 512 × 128 scan protocol, scanning range 6 × 6mm, scan signal ≥ 7, and used the system's built-in analysis software to obtain the central macular thickness (CMT), macular volume (MV), and the average macular thickness (AMT). The fundus photography examination was performed using darkroom non dilated film (Kowa nonmyd 7). The above examinations were completed by specialized ophthalmologists.

Diagnostic criteria for ERM on OCT: as an irregular, hyper-reflective layer on the internal limiting membrane (ILM) in the macular area, commonly associated with retinal wrinkling and hypo-reflective spaces between the ERM and ILM[20]. Disorganization of retinal inner layers (DRIL) was defined as the inability to distinguish boundaries between any two of these inner retinal layers; Intraretinal cystoid space (IRC) was a hypo-reflex, cystic change in the outer and inner layers of the retina; Hyperreflective foci (HRF) was defined as discrete distribution points in any retinal layer visible on OCT, with clear boundaries, no tail shadow, diameter < 30um, and signal intensity similar to that of the nerve fiber layer[21; 22]. Examples of the annotation were provided in Fig. 1.

The white arrows indicate the ERM, the red pentagonal stars represent the IRC, and the blue circles represent HRF, DRIL can be seen in fovea zone. (The right high reflection material is distributed in the outer layer of the retina, with a size greater than 30um and a tail shadow, which was speculated to be a hard exudate.)

Diagnostic criteria for dERM

ERM images of OCT were described above, while in fundus photography examination, ERM was shown as gold foil like reflection on the surface of the retina in the macular area, combining with local small vascular tortuosity and extremely fine radial folds. Patients who were confirmed with ERM through fundus screening complicated with DM or non-proliferative can be diagnosed with dERM.

Statistical analysis

Continuous variables with normal distribution are represented by mean ± standard deviation, measurement data with skewed distribution are represented by median (interquartile spacing) (M [P25, P75]), and categorical variables are represented by numbers and percentages.

All continuous variables were tested for normal distribution by the Kolmogorov-Smirnov test. According to grouping and normality, paired sample t-test or Mann- Whitney-Wilcoxon test was adopted. Paired χ2 McNemar test was used for classification comparison. After converting the above research indicators into binary variables, a conditional logistic regression analysis was conducted to further explore the risk factors affecting the occurrence of dERM. Using Spearman correlation test to assess the correlation between various OCT biomarkers in the dERM group and laboratory results.

All data were analyzed by SPSS 25.0 statistical software, with a P value < 0.05(two-tailed) as significant. Prism 9.5.1 software was used for above results visualization.

Patient characteristics

Between March 2022 and July 2023, a total of 96 dERM patients were screened. Five cases of fibroproliferative DR in fundus photography, 4 cases of concomitant hematological diseases, 2 cases of current pulmonary or urinary system infections, 2 cases of type 1 DM (lack of matched case–control pair), 1 case with a history of vitrectomy surgery within six months, and 1 case with missing examination items were excluded. A total of 81 cases and controls were included in the study, with 42 males (51.9%) and 39 females (48.1%) in each group.

Comparison of clinical characteristics

Clinical characteristics between two groups compared here included age, duration of DM, insulin medication, hypertension status, BMI, macular parameters in OCT (CMT, MV and AMT), SII, Alb, serum lipids (TG, TC and HDL-C), UA, HbA1c and ACR. Statistical comparison results were summarized in Table 1.

Table 1

Comparison of general characteristics and laboratory tests
	dERM group (n = 81)	Control group (n = 81)	p value
Age (years)	69(63, 73.5)	69(64, 73)	0.816
Duration of DM (years)	10(6, 20)	10(7.5, 15)	0.110
Insulin Medication	42(51.9%)	32(39.5%)	0.174^##
hypertension	60(19.3%)	51(15.8%)	0.163^##
BMI (kg/m²)	24.14 ± 3.18	23.52 ± 2.88	0.185^#
CMT (um)	322(291.5, 376)	248.09 ± 18.22	0.000^**
MV (mm³)	10.8 (10.2, 11.4)	10.1(9.8, 10.3)	0.000^**
AMT (um)	300 (285, 318)	279(272.5, 287)	0.000^**
SII	465.37(312.65, 703.24)	346.84(262.29, 479.56)	0.002^**
Alb (g/L)	37.99 ± 4.33	39.53 ± 3.14	0.010^*#
TC (mmol/L)	4.16 ± 1.36	4.27 ± 1.25	0.600^#
TG (mmol/L)	1.23(0.91,1.99)	1.34(0.94, 2.12)	0.298
HDL-C (mmol/L)	1.21 ± 0.43	1.22 ± 0.35	0.780^#
UA (umol/L)	327.11 ± 102.60	328.38 ± 89	0.934^#
HbA1c %	8.31 ± 2.15	8.13 ± 1.90	0.618^#
ACR (mg/mmol)	4.20(0.51, 29.17)	0.97(0.34, 2.45)	.000^**

Normally distributed data was represented as M ± SD, skewed distribution as (M [P25, P75]), and categorical variables as numbers and percentages. (* p value < 0.05, * * p value < 0.01, # paired sample t-test, ## McNemar test, without# Mann- Whitney-Wilcoxon test) Abbreviations: dERM—diabetic macular epiretinal membrane; CMT—Central macular thickness; MV—Macular volume; AMT—Average macular thickness; SII—Systemic immune inflammatory index; Alb —Albumin; TC —Total cholesterol; TG—Triglycerides; HDL-C—High-density lipoprotein cholesterol; UA—Uric acid; HbA1c—Glycosylated hemoglobin; ACR —Albumin creatinine ratio.

In comparison to the control group, patients with dERM exhibited higher OCT macular parameters, including CMT (322 [291.5, 376] vs 248.09 ± 18.22), MV (10.8 [10.2, 11.4] vs 10.1 [9.8, 10.3]), and AMT (300 [285, 318] vs 279 [272.5, 287]) (all p < 0.01). These findings were visually represented in Fig. 2. Additionally, the dERM group demonstrated significantly elevated SII (465.37 [312.6, 703.24] vs 346.84 [262.29, 479.56]) and ACR (4.20 [0.51, 29.17] vs 0.97 [0.34, 2.45]) compared to controls (all p < 0.01), while Alb was decreased (37.99 ± 4.33 vs 39.53 ± 3.14, p < 0.05). Statistically significant comparison results of laboratory tests were summarized in Fig. 3. Statistical differences were not observed in other indexes.

Conditional logistic regression analysis

Referral to the upper limit of normal, convert the continuous variables mentioned above into binary variables. The BMI below 24kg/m2 is considered normal and used to determine if an individual is overweight or obese. Dyslipidemia is diagnosed with above specific criteria integrating TC, TG, HDL-C, and LDL-C levels. The reference values for Alb, UA, and ACR are 40g/L, 420umol/L (males)or 360umol/L(females), and 2.5mg/mmol, respectively. As there are no established normal reference values for SII, this study utilized the average of two sets of SII values (461.65) as the cut-off point and converted them into binary data to determine the presence of high SII.

The transformed binary variables were employed as the independent variable, and the presence of dERM as the dependent variable, and conditional logistic regression analysis of the paired groups was presented in Table 2. The odds ratio (OR)of dERM in the high SII group was calculated to be 3.919, with a 95% confidence interval (CI) of (1.591, 9.654). The relative risk of the high ACR group was up to 4.432, with a 95% CI of (1.885, 10.423). To briefly summarize the results, elevated SII or ACR was a risk factor for dERM among hospitalized DM patients.

Table 2

Conditional logistic regression results
	p value	OR	95% CI
Overweigh/obese	0.709	0.863	0.397–1.873
High SII	0.003^**	3.919	1.900-9.654
Low Alb	0.812	0.904	0.394–2.077
Dyslipidemia	0.632	0.825	0.374–1.816
Hyperuricemia	0.976	1.017	0.331–3.124
High ACR	0.001^**	4.432	1.885–10.421

(** p value < 0.01) Abbreviations: SII—Systemic immune inflammatory index; Alb —Albumin; ACR —Albumin creatinine ratio.

Spearman correlation analysis of different OCT Biomarkers

The Spearman correlation analysis results between other OCT biomarkers (including IRC, HRF and DRIL) and inter group Statistically significant difference indicators were shown in Table 3. IRC, HRF and DRNL in the dERM group were all related to CMT, but not to MV and Alb. IRC was also associated with AMT. HRF showed a significant correlation with SII. Both HRF and IRC were related to ACR, excepted DRIL. But the correlation coefficient Rs values ranged from 0.2 to 0.4, just indicating a weak positive correlation. Therefore, these results may support that such typical confounding factors, like macular edema (IRC) or HRF had little effect on our study.

Table 3

Correlation analysis of different OCT biomarkers
	IRC (n = 23)		HRF (n = 40)		DRIL (n = 41)
	r_s	p	r_s	p	r_s	p
CMT	0.330	0.003^**	0.234	0.036^*	0.248	0.026^*
MV	0.163	0.146	0.160	0.155	0.036	0.750
AMT	0.220	0.048^*	0.189	0.091	0.073	0.518
SII	0.100	0.377	0.233	0.036^*	0.065	0.561
Alb	0.651	0.051	-0.041	0.715	0.065	0.565
ACR	0.242	0.030^*	0.278	0.012^*	0.048	0.674

(*p value < 0.05, ** p value < 0.01) Abbreviations: IRC—Intraretinal cystoid space; HRF—Hyperreflective foci; DRIL—Disorganization of retinal inner layers; CMT—Central macular thickness; MV—Macular volume; AMT—Average macular thickness; SII—Systemic immune inflammatory index; Alb —Albumin; ACR —Albumin creatinine ratio.

This study conducted a retrospective analysis of multiple risk factors associated with dERM based on the data obtained from fundus screenings of hospitalized diabetes patients. In dERM group, we observed an elevation in SII, coupled with a reduction in Alb levels. Especially concerning the SII, which was significantly associated with an increased hazard of dERM (OR = 3.919 [95%CI 1.591–9.654]).

SII is calculated from blood cell count of neutrophils, lymphocytes and platelets and has been regarded as a predictive and prognostic marker in various diseases, such as multiple malignancies[23], autoimmune disorders[24; 25] and cardiovascular diseases et.al[26]. Previous research has substantiated the correlation between SII and OCT biomarkers, such as DME, HRF and subretinal fluid in DR patients[15; 27; 28]. Taking a step further, the present study revealed that dERM as an ILM-vitreoretinal interface lesion is closely associated with SII. There is also a weak positive correlation between HRF and SII. HRF is related to the activation and aggregation of microglia, which rapidly subsides or appears in anti VEGF therapy, indicating active inflammation of the retina[29]. Alb not only reflects the nutritional metabolism status of the body, but also participates in the regulation of inflammation as a negative inflammatory indicator[30; 31]. But there was no significant correlation with the occurrence of dERM in regression analysis. Reviewing the data, it can be found that the mean of serum albumin in both groups is lower than the normal reference value. In regression analysis, using 40g/L as a cut-off value for binary variable conversion may underestimate the role of Alb in dERM. These results suggested that the dERM pathogenesis is also related to systemic inflammation, not confined to the regional retina inflammation response.

In addition, our study showed that patients with higher ACR levels face over four-fold increased risk of developing dERM. Spearman correlation analysis revealed ACR are also associated with IRC and HRF. ACR is the ratio of microalbumin to creatinine in urine, which is commonly considered as a marker of systemic endothelial dysfunction and a predictor of diabetes complications, such as diabetic nephropathy and DR[32]. Both diabetic nephropathy and DR are two most important microangiopathic complications in DM, and they seem to progress in a parallel manner. From the perspective of OCT biomarkers, this study supported the above opinion, it may deepen our understanding of overall cognition of diabetic complications.

This study found that the macular volume coefficients of the dERM group was significantly higher than that of the control group, reflecting the significant change in macular morphology caused by dERM. Its potential mechanism may attribute to the contraction of the fibrous membrane, causing traction in the macular area and macular edema. The greater macular volume coefficients, especially CMT, usually indicated the poorer visual acuity[33; 34].

We did not observe any association between dERM or any OCT biomarkers and BMI, HbA1c, insulin use rate, hypertension, dyslipidemia, and hyperuricemia in this study, which may be related to the small sample size of this study, and the study subjects were all hospitalized patients, with some admission bias. Of course, HbA1c only reflects the blood glucose level for 2–3 months. The research on the correlation between chronic hyperglycemia and the occurrence of complications of diabetes may need more long-term monitoring indicators. In addition, in DM patients, BMI alone may underestimate the obesity rate[35]. Later research should include such comprehensive indicators as waist circumference and waist hip ratio.

However, this study has certain limitations. Firstly, this study is a single center retrospective study that did not follow up on the visual prognosis of dERM patients, and the sample size is small; Secondly, the study subjects were all hospitalized patients and poor eyes were selected for inclusion in the study, which may have admission bias and selection bias; Finally, different researchers also have a certain degree of subjectivity in determining OCT biomarkers. In future research, it is necessary to further expand the sample size and introduce a more objective and intelligent OCT biomarker interpretation system to further elucidate the relationship between dERM and other OCT biomarkers and systemic inflammation.

To conclude, higher SII and ACR are closely related to dERM among hospitalized DM patients, which emphasizes the importance of systemic inflammatory and endothelial dysfunction in dERM occurrence. It also supports an inflammatory origin of the OCT biomarkers like HRF and IRC.

Founding: This research was supported by the Jinhua Science and Technology Bureau (No.2022-3-059).

Competing Interest: The authors declare no financial or non-financial conflict of interest. All authors approved the manuscript for submission.

Author Contributions: All authors contributed to the study conceptualization and methodology; Data curation, formal analysis and original draft writing were performed by Daiying Zhou, Jing Chen and Cuicui Lu. Zhigang Lv and Juan Ye reviewed and edited the previous version of manuscript. All authors read and approved the final manuscript.

Ethics approval: The study was conducted in accordance with the Declaration of Helsinki, and approved by the Ethics Committee of Affiliated Jinhua Hospital of Zhejiang University School of Medicine (Approval Number: 2023-18).

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No competing interests reported.

Systemic immune inflammatory index (SII) and urine albumin creatinine ratio (ACR) are associated with Diabetic macular epiretinal membrane

Status:

Version 1

Abstract

Purpose

Methods

Results

Conclusion

Figures

Introduction

Materials and methods

Research subjects

Clinical data collection

OCT biomarkers evaluation

Diagnostic criteria for dERM

Statistical analysis

Results

Patient characteristics

Comparison of clinical characteristics

Conditional logistic regression analysis

Spearman correlation analysis of different OCT Biomarkers

Discussion

Declarations

References

Additional Declarations

Status:

Version 1