Spectral-Domain Optical Coherence Tomography Features in Open-Angle Glaucoma With Diabetes Mellitus and Inadequate Glycemic Control

Abstract

Purpose: To evaluate spectral-domain optical coherence tomography (SD-OCT) features according to glycemic control status in open-angle glaucoma with diabetes mellitus.

Methods: Subjects underwent comprehensive ocular examination, visual field testing, and SD-OCT imaging (Cirrus HD-OCT). The relationship between glycosylated hemoglobin (HbA_1c) and OCT measurements was compared between diabetic nonglaucomatous eyes and diabetic glaucomatous eyes. Glaucoma-discriminating ability was assessed using the area under the receiver operating characteristic curves (AUCs) for OCT parameters and compared between groups relative to the glycemic control group.

Results: Analysis was performed on 69 nonglaucomatous and 87 glaucomatous eyes in the nondiabetic group, and on 72 nonglaucomatous and 56 glaucomatous eyes in the diabetic group. Average, inferonasal, inferior, and inferotemporal ganglion cell–inner plexiform layer (GCIPL) thicknesses were positively correlated with HbA_1c in diabetic nonglaucomatous eyes (P = 0.040, 0.037, 0.025, and 0.013, respectively). The AUC of the average cup-to-disc area ratio (CDR), vertical CDR, and cup volume in diabetic eyes with poor glycemic control was significantly higher than those in nondiabetic eyes (P = 0.011, 0.003, and 0.043, respectively). The AUC of cube volume, cube average thickness, and minimal GCIPL thickness in diabetic eyes with poor glycemic control was lower than those in nondiabetic eyes (P = 0.006, 0.007, and 0.004, respectively).

Conclusions: In this study, optic nerve head parameters had a superior ability to discriminate glaucoma in diabetic eyes with poor glycemic control. Conversely, the ability to discriminate glaucoma using macular parameters tended to be lower for diabetic eyes with inadequate glycemic control.

Diabetes and glaucoma are two major causes of vision loss worldwide.¹ While the relationship between diabetes and glaucoma has intrigued researchers for years, a firm link has not yet been conclusively demonstrated and the topic remains controversial.¹ Indeed, epidemiologic studies of the association between diabetes mellitus (DM) and glaucoma have been inconsistent, and the association remains controversial.² Nevertheless, diabetic retinopathy often coexists with glaucomatous optic neuropathy. 

Optical coherence tomography (OCT) has been proposed as a powerful tool for retinal measurement for various retinal diseases, glaucoma, and other optic neuropathies. It is often hard to evaluate glaucomatous optic neuropathy accompanied by diabetic retinopathy because OCT measurements, such as peripapillary retinal nerve fiber layer (RNFL) thickness, macular inner retinal thickness, and total retinal thickness, which are helpful for diagnosing glaucoma, can be affected by systemic conditions like DM. To the best of our knowledge, there has been only one study examining the impact of DM on the glaucoma diagnostic ability of OCT. In that study, Stratus OCT from the time-domain era was used, and only RNFL parameters were studied.³ In addition, no study has investigated the diagnostic performance of OCT parameters for glaucoma in different groups according to glycemic control status. 

This study aimed to evaluate the quantitative changes of RNFL thickness, optic nerve head (ONH), total retinal thickness, and ganglion cell–inner plexiform layer (GCIPL) thickness parameters obtained by spectral-domain (SD)-OCT (Cirrus HD-OCT; Carl Zeiss Meditec, Dublin, CA, USA) in nonglaucomatous and glaucomatous eyes in both diabetic and nondiabetic patients. In addition, we compared these measurements and their diagnostic power for open-angle glaucoma among groups according to glycemic control status. 

Methods

Subjects

In this retrospective study conducted over a 3-year period (March 2011 to February 2014) in a tertiary eye care center (Inha University Hospital, Incheon, Korea), the consecutive records of 124 diabetic patients and 156 nondiabetic patients with and without glaucoma were reviewed. This study received approval from the institutional review board of Inha University Hospital and was performed in accordance with the Declaration of Helsinki. 

For subjects with or without DM, eligibility criteria were determined by a glaucoma specialist (NRK) based on a complete ophthalmologic examination, which included a review of patient medical history, best-corrected visual acuity measurements through manifestation refraction, Goldmann applanation tonometry, slit-lamp examination of the anterior segment, gonioscopy, dilated fundus examination, red-free fundus photography (Canon, Tokyo, Japan), Humphrey standard automated perimetry visual test (Carl Zeiss Meditec), and Cirrus OCT (Carl Zeiss Meditec). 

Normal eyes were recruited from subjects with no history of glaucoma (personally or in a first-degree relative), no history or evidence of intraocular surgery, no media opacity on slit-lamp examination, and no retinal pathologic features. A normal eye was defined as having an intraocular pressure <21 mm Hg, a normal-appearing RNFL according to red-free stereophotography, a normal-appearing ONH according to color stereophotography, normal visual field (VF) test results based on normal glaucoma hemifield test results, and a normal mean deviation and pattern standard deviation (P > 0.05). 

Glaucoma was defined as a glaucomatous VF defect confirmed by reliable VF examinations and the appearance of a glaucomatous optic disc with typical loss of the neuroretinal rim by slit-lamp biomicroscopy (cup-to-disc ratio > 0.7; intereye cup asymmetry > 0.2; or neuroretinal rim notching, focal thinning, disc hemorrhaging, or vertical elongation of the optic cup). Only patients with open anterior chamber angles and clear ocular media by slit-lamp evaluation were enrolled. Patients with histories of intraocular surgery and neurologic disorders were excluded. 

Diabetes mellitus was defined as a fasting glucose level of at least 126 mg/dL or current use of antidiabetic medications. Glycemic status was categorized as either good glycemic control or poor glycemic control for hemoglobin A_1c (HbA_1c) levels < 7.0% and ≥ 7.0%, respectively.⁴ Enrolled subjects with diabetes had mild to severe nonproliferative diabetic retinopathy based on the International Clinical Diabetic Retinopathy Disease Severity Scale. Fluorescein angiography (TRC-50EX; Topcon Instruments Corp., Tokyo, Japan) was performed in subjects with DM to determine the stage of retinopathy and to exclude subjects with macular edema. Two ophthalmologists (SYJ, SJP) determined, in a masked fashion, the classifications of diabetic retinopathy. Exclusion criteria for diabetic eyes were macular edema, history of panretinal photocoagulation (PRP), history of intravitreal injection, and history of intraocular surgery. Patients with other concomitant retinal diseases were also excluded. 

Optical Coherence Tomography

A Cirrus HD-OCT (software version 6.0) was used to acquire one optic disc cube protocol and one macular cube protocol in each qualifying eye. The optic disc cube protocol was designed to position the cube scan on the ONH. This protocol generated a cube of data through a 6-mm-square grid by acquiring a series of 200 horizontal scan lines, each composed of 200 A-scans (40,000 points). The RNFL thickness at each pixel was measured and an RNFL thickness map was generated. A calculation circle 3.46 mm in diameter and consisting of 256 A-scans was automatically positioned around the optic disc, and the mean and sectoral (temporal, superior, nasal, and inferior) RNFL thicknesses were then measured. 

The ONH parameters that were analyzed consisted of rim area, optic disc area, mean cup-to-disc area ratio (CDR), vertical CDR, and cup volume. These parameters were automatically measured using an ONH analysis algorithm developed for the Cirrus HD-OCT. Specifically, the algorithm defines the disc and cup margins within the three-dimensional data cube, and then identifies the termination of Bruch's membrane as the disc edge. The rim width around the entire circumference of the optic disc was then determined by measuring the thickness of the neuroretinal tissue in the optic nerve as it turned to exit through the opening in Bruch's membrane. 

Macular cube scans in an area of 6 × 6 mm² were centered on the fovea using the macular cube 512 × 128 or 200 × 200 scan protocol. Software included with the scanning device was used to produce retinal thickness maps, which were then averaged over nine retinal subfields in a 6-mm-diameter circle centered at the true fovea location, as defined by the Early Treatment Diabetic Retinopathy Study (ETDRS); ETDRS areas include a central 1-mm disc and inner and outer rings of 3 and 6 mm, respectively. The central foveal subfield thickness (central macular thickness) bounded by the innermost 1-mm-diameter circle was then calculated. The overall average macular thickness (cube average thickness) and overall macular cube volume over the entire grid area were also obtained from the computational software output based on the proportional contribution of the regional macular thicknesses. 

We next used the Ganglion Cell Analysis (GCA) algorithm, which processes data from three-dimensional volume scans using the macular 512 × 128 or 200 × 200 acquisition protocol. The algorithm identifies the outer boundary of the RNFL and the outer boundary of the inner plexiform layer (IPL). The difference between the RNFL and the IPL outer boundary segmentations yields the combined thickness of the RGC layer and the IPL, which in turn provides a measurement of the macular GCIPL thickness within a 14.13-mm² elliptical annulus area centered on the fovea. The mean, minimum, and six individual sectors (superior, superonasal, inferonasal, inferior, inferotemporal, and superotemporal) of GCIPL thickness were provided. The minimum GCIPL measurement was determined by sampling 360 spokes of measurements extending from the center of the fovea to the edge of the ellipse in 1° intervals and selecting the spoke with the lowest average.⁵ 

All of the images obtained in this study had a signal strength ≥ 6. All of the scans were required to specifically center the optic disc or the fovea. Inaccurate images owing to segmentation algorithm errors, involuntary saccades, or blinking artifacts were excluded from our analysis. 

Statistics

When both of a patient's eyes were eligible, one eye was randomly selected for analysis. Clinical factors associated with OCT parameters in nonglaucomatous eyes were evaluated using univariate linear regression analysis. Relationships between HbA_1c levels and OCT parameters were evaluated using multivariate linear regression analysis adjusted for age and sex in diabetic nonglaucomatous and glaucomatous eyes. In the pooled population without glaucoma, OCT parameters among groups (nondiabetic eyes versus diabetic eyes with HbA_1c < 7.0% versus diabetic eyes with HbA_1c ≥ 7.0%) were analyzed using 1-way analysis of variance and Scheffe's post hoc tests. Receiver operating characteristic curves were used to describe the ability of each parameter to discriminate between glaucomatous and nonglaucomatous eyes in the nondiabetic group, the diabetic group with good glycemic control, and the diabetic group with poor glycemic control. Data analysis was carried out using the Statistical Package for Social Sciences (SPSS) version 20.0 (SPSS, Inc., Chicago, IL, USA). 

Results

Subjects

Sixty-nine eyes of 69 nondiabetic nonglaucoma subjects (normal), 87 eyes of 87 nondiabetic glaucoma patients (OAG [open-angle glaucoma]), 72 eyes of 72 diabetic nonglaucoma subjects (DM − OAG), and 56 eyes of 56 diabetic glaucoma patients (DM + OAG) were included in the present study. 

The characteristics of the study population are shown in Table 1. The average CDR was significantly larger in glaucomatous eyes than in nonglaucomatous eyes in both the nondiabetic and diabetic groups. Visual field examinations also revealed different retinal sensitivities between the nonglaucomatous and glaucoma groups in both the nondiabetic and diabetic groups. No significant differences were found between nonglaucomatous and glaucomatous eyes with respect to age, sex, intraocular pressure, spherical equivalent, and disc area in either the nondiabetic group or the diabetic group. 

Table 1

 

Demographic Features of Study Participants

 

Among 124 diabetic eyes, glaucomatous eyes had diabetes for 9.27 years while nonglaucomatous eyes had diabetes for 11.40 years; the difference was not statistically significant (P = 0.093). The HbA_1c level was marginally higher in nonglaucomatous subjects compared with glaucoma patients (8.44 ± 2.07% and 7.71 ± 1.73%, P = 0.052). A total of 58 eyes had diabetic retinopathy, of which 42 eyes did not have glaucoma and 16 eyes had glaucoma (P = 0.001). Eyes with diabetic retinopathy had mild to severe nonproliferative diabetic retinopathy without maculopathy. 

Factors Associated With OCT Parameters in Nonglaucomatous Eyes

Age was negatively correlated with average RNFL thickness, cube average thickness, and average GCIPL thickness (P = 0.001, < 0.001, and < 0.001, respectively). Female sex was significantly associated with a thinner cube average and average GCIPL thickness (P = 0.004 and 0.021, respectively). Pattern standard deviation was significantly correlated with average GCIPL thickness in the positive direction (P = 0.041). Diabetes mellitus existence, type of DM, duration of DM, and HbA_1c levels were not correlated with average RNFL thickness, rim area, cube average thickness, and average GCIPL thickness (all P > 0.05). Other clinical factors including intraocular pressure, spherical equivalent, and mean deviation were not correlated with average RNFL thickness, rim area, cube average thickness, or average GCIPL thickness (all P > 0.05) (Table 2). 

Table 2

 

Relationship Between Clinical Factors and OCT Parameters in 69 Normal and 72 Diabetic Nonglaucomatous Eyes (n = 141)

 

OCT Measurements According to the Status of Glycemic Control

Table 3 shows the relationship between glycosylated hemoglobin levels and OCT parameters evaluated in diabetic nonglaucomatous eyes and diabetic glaucomatous eyes. In diabetic eyes, temporal RNFL thickness was positively correlated with the HbA_1c level (correlation coefficient = 0.037, P = 0.008). One macular parameter, cube average thickness, was positively related to the HbA_1c level (correlation coefficient = 0.026, P = 0.036). In addition, average GCIPL, inferonasal GCIPL, inferior GCIPL, and inferotemporal GCIPL thicknesses were positively correlated with the HbA_1c level (correlation coefficient = 0.045, 0.037, 0.042, and 0.045, P = 0.040, 0.037, 0.025, and 0.013, respectively). 

Table 3

 

Relationship Between OCT Parameters Measured Using Spectral-Domain Optical Coherence Tomography and HbA_1c (%) in 58 Diabetic Nonglaucomatous Eyes and 50 Diabetic Glaucomatous Eyes

 

Comparison of OCT Measurements in Nondiabetic and Diabetic Eyes

Comparisons of the OCT measurements in the pooled population of subjects with nonglaucomatous eyes (69 nondiabetic eyes, 16 diabetic eyes with HbA_1c < 7.0%, and 42 diabetic eyes with HbA_1c ≥7.0%) are shown in Table 4. The average RNFL thickness and other RNFL sectoral parameters (temporal, superior, nasal, and inferior thickness) did not differ significantly among groups. For the ONH parameters, including rim area, disc area, average CDR, vertical CDR, and cup volume, no differences were found between eyes with and without diabetes. 

Table 4

 

OCT Parameters Measured Using Spectral-Domain Optical Coherence Tomography in 69 Normal Eyes, 18 Diabetic Eyes With Good Glycemic Control, and 42 Diabetic Eyes With Poor Glycemic Control

 

We next examined macular parameters. Total retinal thickness parameters such as central macular thickness, cube volume, and cube average thickness were not found to be significantly different among the groups (P = 0.937, 0.729, and 0.902, respectively). The average GCIPL thickness and other GCIPL sectoral parameters (superotemporal, superior, superonasal, inferonasal, inferior, and inferotemporal thickness) did not differ significantly among the three groups (all P > 0.05). The minimum GCIPL thickness differed significantly among nondiabetic eyes, diabetic eyes with good glycemic control, and diabetic eyes with poor glycemic control (79.70 ± 7.25, 76.63 ± 10.44, and 74.60 ± 11.59, respectively, P = 0.020). 

Diagnostic Ability of OCT for Glaucoma in Patients With or Without DM

The area under the receiver operating characteristic curve (AUC) values showing the discriminating power for glaucoma from the Cirrus OCT are summarized in the Figure and Table 5. 

Figure

 

Area under the receiver operating characteristic curves of the OCT parameters for distinguishing nonglaucomatous eyes from eyes with mild to moderate glaucoma. (A) Nondiabetic eyes. (B) Diabetic eyes with good glycemic control. (C) Diabetic eyes with poor glycemic control.

Table 5

 

Comparisons of Area Under the Receiver Operating Characteristic Curve (AUC) Values for Glaucoma Detection According to Status of Glycemic Control in Diabetic Eyes

 

In nondiabetic eyes, the average RNFL thickness and minimum GCIPL thickness had the largest AUCs and sensitivities at specificities greater than 80%: average RNFL (0.871, 73.9%) and minimum GCIPL (0.872, 78.3%). Comparison of the AUCs of average RNFL, vertical CDR, average GCIPL, and cube average thickness did not reveal any significant differences (all P > 0.05, Fig. 1A). In diabetes with good glycemic control, the highest AUC for glaucoma detection was found for the vertical CDR (0.883). The average RNFL thickness, cube average thickness, and average GCIPL thickness exhibited a differentiating ability similar to that of the vertical CDR (P = 0.260, 0.074, and 0.165, respectively) (Fig. 1B). In diabetes with poor glycemic control, the vertical CDR (AUC, 0.923) exhibited the best glaucoma-discriminating ability, which was similar to that of the average RNFL thickness (AUC, 0.810) (P = 0.097) and significantly higher than that of cube average thickness (AUC, 0.615) and average GCIPL (AUC, 0.716) (P < 0.001 and = 0.005, respectively) (Fig. 1C). 

When we compared the glaucoma diagnostic abilities of OCT parameters between the nondiabetic and diabetic groups, the AUC of the average CDR, vertical CDR, and cup volume parameter in diabetic eyes with poor glycemic control was significantly higher than those in nondiabetic eyes (P = 0.011, 0.003, and 0.043, respectively). The AUCs of total macular parameters including cube volume and cube average thickness in diabetic eyes with poor glycemic control (HbA_1c ≥7.0%) were lower than those in nondiabetic eyes (P = 0.006 and 0.007, respectively). When we evaluated inner macular thickness parameters, the AUC of minimum GCIPL thickness in diabetic eyes with poor glycemic control was significantly lower than that in nondiabetic eyes (P = 0.004). 

Discussion

This study investigated whether DM, and further inadequate glycemic control, affects OCT RNFL, ONH, total retina, and GCIPL measurements. In addition, the diagnostic ability of these parameters for glaucoma was evaluated. The temporal RNFL thickness, cube average thickness, average GCIPL thickness, inferonasal GCIPL thickness, inferior GCIPL thickness, and inferotemporal GCIPL thickness tended to be greater according to higher HbA_1c levels in diabetic eyes. The minimum GCIPL thickness had a tendency to be less among patients with DM. In diabetic patients with poor glycemic control, the vertical CDR exhibited significantly higher diagnostic abilities than average GCIPL thickness and cube average thickness. The minimum GCIPL thickness, cube volume, and cube average thickness had significantly lower diagnostic abilities in diabetic eyes with poor glycemic control than in nondiabetic eyes. 

Diagnosis of Glaucoma in Patients With Diabetes Mellitus

Differentiating between diabetic change and glaucomatous change can be challenging in some cases. Specifically, some early-stage glaucoma patients present with a reduced RNFL thickness only, without characteristic optic disc changes, making it difficult to differentiate glaucomatous changes from diabetic changes. Indeed, a case of a localized RNFL defect developing after a retinal cotton-wool spot in a patient with DM and hypertension has been reported.⁶ In addition, a previous study reported that optic nerves in eyes treated with PRP are more likely to be judged as abnormal by glaucoma specialists.⁷ Visual field losses in eyes with glaucoma and coexisting diabetic retinopathy often demonstrate amorphous patterns, which are influenced by retinal hemorrhaging, exudates, and retinal nerve fiber impairment.³ 

Effect of Glycosylated Hemoglobin Levels on Retinal Changes

There have been a few studies evaluating the relationship between retinal thickness changes and glycemic control. Chihara et al.⁸ reported that the incidence of RNFL defects is not correlated with the glycosylated hemoglobin level at the time of examination. Likewise, a 3-year follow-up study of retinal thickness alterations in patients with type 2 DM using a retinal thickness analyzer (RTA) found no correlation between changes in retinal thickness and changes in HbA_1c values.⁹ In a study using Heidelberg retina tomography (HRT) III, rim area and rim volume measurements were not significantly correlated with HbA_1c levels.¹⁰ Furthermore, a study evaluating the effect of glycemic control on RNFL thickness reported that RNFL measurements following 1-month blood glucose regulation were not significantly different.¹¹ On the other hand, another study reported that RNFL thickness decreased after 4 months of glycemic control, which was explained by the transient deterioration of diabetic retinopathy following intensive glycemic control.¹² In this study, among a number of parameters evaluated, cube average thickness, average GCIPL, inferonasal GCIPL, inferior GCIPL, and inferotemporal GCIPL thickness parameters measured in the macular area were positively correlated with HbA_1c levels at the time of OCT examination. Retinal changes in DM can be due to a variety of pathways involving several factors. In addition, the severity of diabetic retinopathy, duration of diabetes, type of DM, and glycosylated hemoglobin values can complicate diabetic eyes with different phenotypes. For example, while prolonged duration of poor glycemic control might induce retinal thinning, simultaneous intracellular or extracellular edema can lead to increased retinal thickness. Accordingly, diagnosing glaucoma in eyes of patients with DM using OCT can be challenging. 

Optic Disc Parameters for Diagnosis of Glaucoma in Diabetic Eyes

A number of clinical studies have reported RNFL defects or thinning in diabetic eyes without glaucoma, which is in accordance with the histopathologic evidence in diabetic eyes.^8,13–15 According to an experimental report, there is an impairment in retrograde axonal transport and a reduction in the cross-sectional size of large optic nerve fibers in diabetic rats.¹⁶ Other morphologic studies using TUNEL staining have demonstrated that enhanced apoptosis of neuroglial elements may lead to an early onset of diabetes-associated RNFL loss.¹⁷ In this study, RNFL thickness did not differ significantly between diabetic and nondiabetic eyes. In a previous study, RNFL thickness measured by Stratus OCT did not decrease significantly in diabetic subjects compared to healthy subjects.³ The differences in results from previous studies may have been due to the study populations being evaluated as well as the type of imaging devices and algorithms used to measure retinal thickness. 

In eyes with glaucomatous optic neuropathy, pathologic cupping in ONH progresses as the number of nerve fibers and glial cells decreases. Previous studies have demonstrated that unlike the situation with glaucoma, optic nerve cupping is not a feature of diabetes, although both disease entities exhibit RNFL wedge defects.^18,19 In this study, ONH parameters were not significantly different between nondiabetic eyes and diabetic eyes. Furthermore, several studies have reported that the neuroretinal rim is preserved in diabetes, and can thus provide important clues for differentiating glaucoma and diabetes.^7,19,20 Another recent article introduced clock hour–based analysis of the rim–RNFL correlation, which may be helpful in differentiating normal-tension glaucoma in diabetic patients.²¹ 

In the present study, diabetic eyes with poor glycemic control exhibited the highest AUCs for glaucoma diagnosis for the vertical CDR, average CDR, cup volume, and average RNFL thickness. In eyes with poor glycemic control, ONH and RNFL parameters seemed to be better at distinguishing glaucoma compared to total macular thickness and macular GCIPL parameters, probably because they are relatively less affected by DM status and glycemic control status. In other words, both ONH/RNFL parameters and macular total/GCIPL parameters are affected by neuronal thinning, whereas only macular parameters might be affected by retinal swelling. However, in clinical situations, clinical and photographic evaluations of the ONH should be performed simultaneously, because ONH analysis by OCT can be misleading in cases of ONH recognition algorithm errors or scan centration errors. In addition, ONH and RNFL parameters may also be affected by diabetic status, such as in cases of macular edema spreading widely to the optic disc region. 

Macular Parameters for Diagnosis of Glaucoma in Diabetic Eyes

Evidence of macular changes in DM should be considered significant because the macular region contains more than 50% of retinal ganglion cells (RGCs), the bodies of which reside in the inner layer, are multilayered, and are 10- to 20-fold thicker than their axons.^22,23 An OCT imaging study that investigated optic disc parameters on a clock-hour basis reported that diabetic peripapillary RNFL thinning occurs more frequently in areas located near the macula.²⁴ In addition, several groups have shown that total macular thickness is reduced in diabetic patients with no or minimal diabetic retinopathy compared to normal control subjects.^15,25–28 Van Dijk et al.^29,30 attributed the thinning of the total retina in type 1 DM to a selective thinning of the macular inner retinal layers. In this study, among subjects without glaucomatous optic neuropathy, the minimum GCIPL thickness had a tendency to be thinner in patients with DM, in accordance with previous reports. 

In comparing the diagnostic abilities of OCT parameters between the nondiabetic group and the diabetic group, the diagnostic abilities of macular total thickness and macular inner GCIPL parameters in the DM patient group had a tendency to be lower than those in the nondiabetic groups, especially the poor glycemic control group. One explanation is that the macular scan area can be affected more heavily by subclinical retinal edema than the peripapillary scan area. Another explanation is that the diagnostic abilities of macular parameters are lower due to the preceding loss of the RGC associated with diabetes. 

Limitations

There were some limitations to this study, including the small number of samples in each group. This study evaluated OCT parameters stratified by glycemic control, but not by diabetic retinopathy classification. Since this study was cross sectional in design, the causal relationship between DM and changes in the retina is indefinite. The RNFL changes in DM patients might have been confused with early glaucomatous changes. Most of the glaucoma patients included in this study had early-stage disease, and thus the diagnostic ability of our analysis may have been generally underestimated. Although we excluded patients with macular edema, another possible limitation was that patients with subclinical macular edema might have been included. Finally, subjects with enlarged CDR received more eye examinations than those without enlarged CDR, and consequently were more likely to have their open-angle glaucoma detected, which might have led to overestimating the diagnostic ability of ONH in both nondiabetic and diabetic patients. 

Conclusions

This study compared quantitative changes of SD-OCT parameters and their diagnostic abilities for open-angle glaucoma in nondiabetic eyes, diabetic eyes with good glycemic control, and diabetic eyes with poor glycemic control. The minimum GCIPL thickness differed significantly between diabetic and nondiabetic eyes. Optic nerve head parameters had a superior ability to discriminate glaucoma in diabetic eyes with poor glycemic control. The ability to diagnose glaucoma using macular parameters such as minimum GCIPL thicknesses, cube volume, and cube average thickness was significantly lower in diabetic eyes with poor glycemic control than in nondiabetic eyes. Further studies evaluating retinal qualitative changes observed by high-resolution OCT are needed to understand the mechanisms of neuronal changes in diabetes and glaucoma. 

Acknowledgments

Presented as a poster at the annual meeting of the American Academy of Ophthalmology, Las Vegas, Nevada, United States, November 14–17, 2015. 

Supported by an Inha University research grant. 

Disclosure: S.Y. Jeong, None; S.J. Park, None; H.S. Chin, None; S.H. Kim, None; N.R. Kim, None