European Journal of Cardiovascular Medicine

A slowly progressing optic neuropathy that can cause permanent blindness, glaucoma affected 66.8 million individuals globally in 2000.One Glaucoma occurrence in India varies between 4.96% to 14.6%.1 According to the WHO, diabetic retinopathy and glaucoma are serious eye conditions that require prompt treatment. The VISION 2020 program states that glaucoma is a major contributor to the global blindness rate, while cataracts are thought to be the main reason of impaired vision.2

Because glaucoma is a type of irreversible optic neuropathy, it can cause impaired vision. This condition is also a major contributor to permanent blindness worldwide. An estimated 66.8 million individuals worldwide have experienced glaucoma, according to information. Increased central corneal thickness brought on by diabetes mellitus might raise intraocular pressure (IOP). Additionally, research has linked DM to POAG.1

Given that diabetes is a microangiopathy and that the pathophysiology of glaucoma may involve a degradation of an optic disc's microcirculation, it is easy to accept diabetes as a known risk factor for persistent open angle glaucoma. Numerous research have been conducted worldwide to determine whether different forms of diabetes and primary open-angle glaucoma are related. Yet, in underdeveloped nations, there is insufficient evidence to identify meaningful correlations among two ailments. The purpose of this study is to determine whether diabetes and POAG are related in the Indian population.

After receiving ethical approval from the Institutional Review Committee, the study was carried out. Prior to enrolment, all subjects provided written informed permission. The patients were split up into 3 categories. Group 1 consisted of patients with glaucomatous optic disc, visual field abnormalities, and an IOP more than 20 mmHg who were diagnosed with POAG. Patients with an RBS >12 mg/dl who have been diagnosed with type II DM are included in Group 2, while age-matched, seemingly healthy people are included in Group 3.

In the Performa, pertinent initial patient data was collected. At the OPD visit, a comprehensive ocular examination and a detailed clinical history were completed. Vision tests, gonioscopy, applanation tonometry, perimetry, slit lamp tests, and direct and indirect ophthalmoscopic fundus examinations with photographs were performed on the patients, and appropriate care was then implemented. Prior dilation, three IOP measures were collected from each eye using a Goldmann applanation tonometer, and the mean was calculated for investigation. Automated perimetry was performed with near refractive correction. Statistical analysis was performed using the SPSS, version 23. Mean, standard deviation, odds ratio, relative risk and 95% CI were calculated. Proportions were compared using the Chi-square test. A ‘p’ value of less than 0.05 was considered significant.

Patient aged <40years and >80 years in all groups.

·         For Group I: patients having a corneal ulcer, dystrophy, ectasia, active infections, ocular tumors, congenital anomalies, uveitis, trauma, pigment dispersion syndrome, exfoliation syndrome, rubeosis on slit lamp biomicroscopy, the gonioscopic finding of occludable angle in either eye and visual field defect not compatible with POAG. 

·         For Group II: Type I DM (IDDM) and pseudophakic patients.

·         For Group III: pseudophakic patients.

This study was conducted in 150 patients where complete ophthalmological workup was done and both eyes were examined. Each group comprised of 50 patients each. 

Table 1: Mean values of data collected for all 3 groups

In the POAG group, 82% of the patients were male and 18% were female, with an average age of 59.6±8.11 yrs. The bulk of the individuals within the diabetes sample were over 50, and there was no statistically significant variation between the sexes. However, an unaltered group that was age-matched was chosen. Among population with diabetes group, POAG was detected in 16 out of 50 participants, 12 of whom were male (75.00%) and 4 of whom were female.

 Table 2: Gender distribution of patients among study groups.

Table 3: age distribution of patients with POAG among diabetic groups.

Table 4: prevalence of POAG among diabetics.

Table 5: Relationship between duration of diabetes and prevalence of POAG.

Table 6: Relationship between age and IOP values

 The association between diabetic retinopathy and glaucoma was not confirmed (p=0.625, RR: 0.84, 95% CI 0.42-1.69). The individuals' median period with glaucoma proved three years, with a mean of 4.13 years (SD±3.59). We discovered a statistically significant correlation amongst glaucoma and the length of time spent with type 2 diabetes.

  Table 7: Relationship between age and RBS among study groups.

This shows that there is no significant correlation between IOP and blood sugar levels, which may be due to the fact that the patients were on treatment for both diabetes and glaucoma.

According to estimates from the World Health Organisation, glaucoma accounts for 12.8% of India's 8.9 million blind individuals.3 Regarding the importance of glaucoma for public health, little is known about its prevalence and potential risk factors in India.4 In order to start treatment to stop its spread, early detection is crucial. It has been established that a number of risk variables are important in POAG instances.5 Nevertheless, data regarding the correlation between diabetes mellitus and POAG are desperately needed. The average age of POAG patients in this study was 59.6±9.47 years, which was comparable to the findings of earlier Indian population-based investigations.

The Blue Mountains Eye research, in which average age of the research group was 66.2±9.8 and that of POAG was 75.9±8.6.6, suggests that age is a separate risk factor for the development of POAG. POAG individuals in our investigation had a shorter average age of 59.6±9.47. 6

In our research, POAG was shown to be higher in males than in females. The outcome was comparable to that of Leske et al. and the Aravind Comprehensive Eye Survey.7

It appears that DM and POAG are directly related. Numerous theories on the physiological connections between DM and POAG have been put forth. Initial, there is increasing proof that lipid abnormalities and chronic hyperglycemia may raise the risk of stress-induced neuronal damage. Substantial proof for this relationship has been presented, in particular, by data from labs. 8

Secondly, studies revealed that diabetes eyes had reduced retinal blood flow and a diminished ability to auto-regulate blood flow. Patients consequently exhibit overexpression of hypoxia-inducible factor-1 (HIF-1α) and relative hypoxia. Crucially, increasing IOP caused the rise in HIF-1α concentrations within the optic nerve head, retina, and ganglion cells of human glaucomatous eyes.9 

It is contentious notwithstanding pretty compelling findings gleaned from numerous investigations. The issue is that there may be detection prejudice in these research. In other words, those with diabetes have a greater probability to have glaucoma identified and to be closely monitored by ophthalmologists. The "ideal investigation" of T2D and POAG risk that tracked individuals for a lengthy period and was free from detection bias is hard to come by. Therefore, diabetes and ageing are two additional significant risk variables for POAG progression. Therefore, complete verification is crucial.

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7.       Becker B. Diabetes mellitus and primary open-angle glaucoma. Am J Ophthalmol. 1971;71:1-13.

8.       Leske MC. The epidemiology of open-angle glaucoma: a review. Am J Epidemiol.

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