Assessment of Retinal Nerve Fiber Layer Thickness using Optical Coherence Tomograghy (OCT) in patients with Diabetic Retinopathy in relation to HbA1c

 INTRODUCTION

In affluent countries, diabetic retinopathy is the most common form of the disease and a leading cause of blindness. Excessive blood glucose levels are one of the most critical causes in the development of diabetes-related retinopathy. Directly affecting retinal cells via hyperglycemia is also critical.¹

The prevalence of diabetic retinopathy in persons who have had diabetes for a decade or longer is as high as 80%.²

One of the numerous aspects that contribute to good eyesight is the ability of the retinal neurons to function normally. Early in diabetes, the quality of vision begins to deteriorate, which may reflect the early stages of neural malfunction.³

In the early phases of diabetic retinopathy, the retinal nerve fibre layer is one of the most important structural neurons in the retina. People with diabetes have been found to have RNFL thinning or abnormalities, according to a number of studies. There have been reports of retinal nerve fibre layer loss among diabetic patients without diabetic retinopathy who had a poor glucose control. Another ocular manifestation of diabetes besides diabetic retinopathy could be a malfunction in the retinal nerve fibre layer. RNFL loss may contribute to diabetic optic nerve dysfunction if it is not detected early enough.⁴

OCT is an imaging technique that can be used to diagnose a wide range of eye disorders. RNFL and optic nerve head thickness can be measured objectively and quantitatively with high precision. Diabetic eyes with or without indications of DR show a clinical decrease in the thickness of the central retinal or one cellular layer compared to control groups, according to several studies (persons without DM). In diabetics with mild diabetic retinopathy (DR), the retinal nerve fibre layer in the periphery of the macula thins first, leading to a reduction in inner retinal thickness in the macular area.⁵

Diabetic retinopathy may benefit from the automatic stacking of retinal structures by SD-OCT, according to the findings of Vujosevic and Midena. To prevent and treat diabetes-related vision loss, early detection of retinal nerve fibre layer (RNFL) thinning can benefit ophthalmologists.⁶

In the diagnosis of diabetic individuals at risk for developing problems such as retinopathy, HbA1c is regarded one of the most discriminative and useful techniques. HbA1c and mortality risk variables have recently been linked in men and women with type 2 diabetes. Diabetes patients, particularly those with retinopathy, have higher rates of Gram-positive bacteria, such as Staphylococci, than the general population.⁷

The Aim of the present study was to evaluate the relation of retinal nerve fiber layer thickness to HbA1c in patients with diabetic retinopathy.

PATIENTS AND METHODS

Between the months of February 2021 and January 2022, we examined the retinas of 60 people who had been diagnosed with Diabetic Retinopathy and were seen in the outpatient clinic of the Ophthalmology Department at Al-Azhar University Hospital (Cairo).

Two groups of patients were formed: 30 eyes with diabetic retinopathy in Group A (HbA1c 7%) were included in this study. In the second group B, there were 30 eyes of diabetic retinopathy with uncontrolled glycosylated hemoglobin (HbA1c >7%).

Inclusion criteria: Type I and type II diabetic retinopathy patients (DR).

Exclusion criteria: Presence of any other metabolic disease than DM,  opaque cornea, opaque lens, laser retinopexy, intra vitreal injection and intra ocular surgery that have been done within 3 months before OCT assessment, and glaucoma.

Before involvement in the study, all participants were required to sign a consent form.

Everyone was subjected to:

All of medical history.

On the day of the OCT evaluation, a blood sample was collected to determine the HbA1c level.

Attention to detail when performing an OCT exam.

As part of an eye checkup:

Visual acuity, both uncorrected an best corrected.

Applanation tonometer to measure intraocular pressure.

For examination of the anterior section, slit-lamp biomicroscopy is employed.

Slit-lamp biomicroscopy with a 90D lens for dilated fundus examination.

Retinal Nerve Fiber Layer OCT Cross Section (Topcon-DRI OCT Triton-).

Optical Coherence Tomography (OCT):

The thickness of the RNFL was measured using Deep Range Imaging-OCT.(DRI-OCT-1, Topcon, Tokyo, Japan).

A wavelength-swapping laser with an operational range of about 100 nm was used in the Deep Range Imaging-OCT system's creation. More than a million A-scans per second are acquired in tissue with an 8-nm axial resolution. Wide-angle and 3D horizontal (H) disc circle grid scanning of the Deep Range Imaging-OCT were employed in this experiment to examine each eye. Using a quicker scan setting and focusing on the posterior pole, the Deep Range Imaging-OCT image with a 12 9 mm wide-angle was acquired. Ophthalmologic and macular pictures were obtained during one scan.

Optical Coherence Tomography (OCT):

For all of the OCT measurements, there was a single point of contact. The same optical coherence tomography (OCT) apparatus (Topcon DRI OCT Triton + Swept Source OCT version 10.11) was used to evaluate the thickness of retinal nerve fibres in both the anterior and posterior segments (super luminescent LEDs with a wavelength of 1,050nm). In addition, an A-scan rate of 100,000 scans per second is feasible.

The Bab El-Shearyah University Hospital Lab used COBAS INTEGRA 400 plus to evaluate the HbA1c level, and the blood sample was taken the same day as the OCT examination.

Statistical Analysis:

In order to analyze the data acquired, Statistical Package of Social Services version 20 was used to execute it on a computer (SPSS). In order to convey the findings, tables and graphs were employed. The quantitative data was presented in the form of the mean, median, standard deviation, and confidence intervals. The information was presented using qualitative statistics such as frequency and percentage. The student's t test (T) is used to assess the data while dealing with quantitative independent variables. Pearson Chi-Square and Chi-Square for Linear Trend (X2) were used to assess qualitatively independent data. The significance of a P value of 0.05 or less was determined.

RESULTS

X2: Chi-square test                 t: T-student test                        U: Mann- Whitney test

p: p value for comparing between the two studied groups      *: Statistically significant at P <0.05

Table 1: Comparison between two groups as regard to patient’s DM characteristics

In Table (1): statistically significant differences between groups based on DM duration (P=0.022) and HbA1C (P<0.001) exhibit DM features.

X2: Chi-square test                 U: Mann- Whitney test

p: p value for comparing between the two studied groups      *: Statistically significant at P <0.05

Table 2: Comparison between two groups as regard to patient’s eye outcome

Table (2) demonstrate eye outcome and it show highly statistically significant differences between groups according to Un Corrected Visual Acurity (UCVA) (P=0.039), Best Corrected Visual Acurity (BCVA) (P=0.007) and Optical Coherence Tomography (OCT) (P<0.001).

X2: Chi-square test                 U: Mann- Whitney test

p: p value for comparing between the two studied groups                      *: Statistically significant at P <0.05

Table 3: Relation between DM duration and eye outcome

Table(3) demonstrate Relation between DM duration and eye outcome and it show highly statistically significant differences between groups according to Auto refractometer (P<0.001).

X2: Chi-square test                 U: Mann- Whitney test.

p: p value for comparing between the two studied groups.                     *: Statistically significant at P <0.05

Table 4: Relation between DM Treatment type and eye outcome

Table(4) demonstrate relation between DM Treatment type and eye outcome and it show no statistically significant differences between groups.

Table 5: Correlation between HbA1C and eye outcome

Table (5) demonstrate correlation between HbA1C and eye outcome and it show highly statistically negative correlation between HbA1C and each of un-corrected visual acurity (UCVA) (r=-0.319, P=0.013) and best corrected visual acurity (BCVA) (r=-0.450, P<0.001).

CASES

Fig. 3: RNFL not affected.

Fig.4: RNFL affected.