Online ISSN: 2515-8260

Keywords : Glaucoma

Assessment of prevalence of dry eye diseases in diabetic patients

Dr.Shreyanshi Sharma, Dr.SushilOjha

European Journal of Molecular & Clinical Medicine, 2022, Volume 9, Issue 3, Pages 1581-1585

Background:Diabetic patients might exhibit dry eye symptoms probably due to neuropathy,
metabolic dysfunction, or abnormal lacrimal secretions. The present study was conducted
to assess prevalence of dry eye diseases in diabetic patients.
Materials & Methods:92 diabetic patients of both genders were enrolled. Ocular
examinations, fasting blood sugar (FBS), postprandial blood sugar, and glycosylated
hemoglobin estimation (HbA1c) were recorded. Dry eye patient was diagnosed with the
help of slit-lamp examination, Schirmer’s test, tear film break-up time (BUT), and Rose
Bengal staining technique. Gradation of dry eye was done by the following standard
Results: Dry eye was present in 70 and negative in 22. The mean duration of diabetes was
11.4 years in positive cases and 5.6 years in negative cases. The difference was significant
(P< 0.05).Grade was mild in 32, moderate in 20 and severe in 18 patients. The difference
was significant (P< 0.05). Age group (years)<50 years had 24, 50-60 years had 30 and >60
years comprised of 16 patients. Blood sugarcontrol (HbA1c) was good in 12, fair in 10,
action suggested in 28 and poor in 20 patients. The difference was significant (P< 0.05).
Conclusion: There was high prevalence of dry eyes in diabetic patients. Grade of dry eyes
was mild, moderate and severe.

Diabetes and glaucoma: How deep is the relation?

Dr. Chaithra C M, Dr. Kshama. K

European Journal of Molecular & Clinical Medicine, 2022, Volume 9, Issue 2, Pages 1136-1139

Background and aim: India is one of the 7 countries of the IDF (International Diabetes Federation) SEA (south-east Asia) region. 463 million people have diabetes in the world and 88 million people in the SEA Region; by 2045 this will rise to 153 million. There were over 77,005,600 cases of diabetes in India in 2020.In our study we tried to determine the risk factors for development of Glaucoma, especially in Type-2 diabetics and its magnitude.
Methods: a cross sectional study done in KIMS OPD, Bangalore between January 2018-may 2019. Diabetes was diagnosed by history and measurement of blood sugar levels. Glaucoma was diagnosed by assessing optic disc morphology, visual fields, and intraocular pressure. Systemic blood pressure was also measured for the patients. Statistical significance was indicated by P < 0.05.
Results: Study cohort included 350 patients with Type-2 Diabetes (150 males and 250 females), mean age of 52+/- 9 years. Prevalence of glaucoma was 16% (95% CI; 13.4-18.3). Out of this 16%, 50% had primary open angle glaucoma, 32% primary angle closure, 12.5% neovascular glaucoma, 5.3% other types. 77% diabetics didn’t have Diabetic retinopathy. Presence of glaucoma was significantly associated with the duration of Diabetes (chi-square=5.80 and p<0.015). Presence of Diabetic retinopathy was Not significantly associated to the presence of glaucoma (odds ratio=1.42). Even presence of systemic hypertension did not affect the magnitude of glaucoma in diabetics.
Conclusion: Screening for glaucoma while screening Diabetic cases may yield us more cases of glaucoma and the duration of diabetes is one of the most important determinants for development of glaucoma.

Pattern of Red Eye Manifestations in a Tertiary Care Hospital in North India

Dr.Pallavi Sharma, Dr.Sachit Mahajan, Dr.Amit Sharma

European Journal of Molecular & Clinical Medicine, 2021, Volume 8, Issue 4, Pages 1912-1916

Background and Objectives: Red eye is common presentation to ophthalmology out-patient
and emergency clinics. The spectrum of diseases range from conjunctivitis, keratitis,
epicscleritis, scleritis, trauma, dry eye disease to orbital cellulitis, angle closure glaucoma and
endophthalmitis. Detailed history and complete ocular examination are necessary for accurate
diagnosis. This study was conceptualized to determine the most common causes of red eyes, in
an effort to generate evidence, which would help us in managing the causes of red eye more
Material and Methods: A cross-sectional study was carried was out in 500 patients who
presented to Ophthalmology out-patient clinics of GMC Jammu with red eye. Detailed history
was taken from each patient and complete ocular examination was performed. The data was
expressed as percentages and subsequently analyzed with the OpenEpi online software version
3. A p value <0.05 was considered as statistically significant. All p value used were two-tailed.
Results: The mean age in our study was 36.85±11.6 years with age range of 18-60 years. There
were 57.8% males and 42.2% females. Most patients (58.8%) were from urban areas. The most
common causes of red eye were conjunctivitis (35.4%), foreign bodies (26.8%) and
conjunctival degenerations (14.4%). Most of the patients (85.2%) presented within 14 days of
onset of red eye.
Conclusion: Red eye can be differential diagnosis of many ocular conditions. Accurate
diagnosis is very important for appropriate management. Most common causes of red eye
include conjunctivitis, foreign bodies and conjunctival degenerations.

Role of Polyphenolic Compounds in Management of Oxidative Stress Associated With Glaucoma

Chandrashekhar Mahadeo Chakole; Meenakshi Kanwar Chauhan

European Journal of Molecular & Clinical Medicine, 2020, Volume 7, Issue 9, Pages 2064-2084

Glaucoma is a first rank common cause of irreversible vision loss. It is also
recognized as a neurodegenerative disease which progress with age, results in optic
neuropathy. The exact cause of glaucoma remains unclear although oxidative stress
considered as one of the reasons for cell death in the retinal ganglion cell and retinal
pigment epithelium. Oxidative stress could result after imbalance between formation and
utilization of reactive oxygen species. Current pharmacotherapy of glaucoma includes
lowering down of elevated level of IOP, which is not sufficient enough to retard
irreversible vision loss in some instances. Hence, alternative neuroprotective therapy is
warranted. Polyphenolic compounds possess antioxidant, anti-inflammatory properties and
also show the neuroprotective effect in an experimental model. Amongst the natural
polyphenolic compounds resveratrol, curcumin, rutin, quercetin, myricetin have been
studied and showed potential as neuroprotection against cell apoptosis. Moreover, the extra
supplement of a polyphenolic compound may also improve antioxidant status, which was
underestimated in glaucoma disorder. Despite the potential, the polyphenolic compounds
yet to explore for clinical use in ocular disorder. Hence it is an excellent opportunity for
the future researcher to transform these substances from lab to clinic as neuroprotectants
in glaucoma.


J. Josphin Mary; R. Charanya; V. Shanthi; G. Sridevi

European Journal of Molecular & Clinical Medicine, 2020, Volume 7, Issue 9, Pages 1447-1453
DOI: 10.31838/ejmcm.07.09.154

Glaucoma is a persistent, permanent eye disease that contributes to vision and quality of life loss. Within this paper we build a deep learning system for the automatic diagnosis of glaucoma with a Convolutionary neural network. Deep learning algorithms, such as CNNs, that infer a hierarchical representation of images to differentiate between glaucoma and NG trends of diagnostic decisions. The DL architecture proposed contains six learning strategies: four Convolutionary strata and two entirely linked layers. Strategies for drop-out and data rise were implemented to further enhance the treatment of glaucoma. Extensive validation of ORIGA and SCES databases is carried out. The findings show that the recipient's operating curve field under curve (AUC) is significantly higher than the state of the art algorithms in glaucoma identification at 0,831 and 0,887 in the two databases. The method may be used for the detection of glaucoma.

Meteopathogenic Mechanisms Of Development And Aspects Of Prevention Of Glaucoma Under The Conditions Of A Risk Continental Climate Of Uzbekistan

Ne’matjon S. Mamasoliev; B. M. Nazarov; Ziyadullo N. Mamasoliev

European Journal of Molecular & Clinical Medicine, 2020, Volume 7, Issue 8, Pages 4209-4220

In recent years, there have been significant changes in the field of screening
diagnostics and glaucoma prevention. At the same time, the specificity of glaucoma
control, due to a number of regional reasons, needs corrections. In a prospective clinical
and meteorological study, 1112 cases of glaucoma were analyzed. A direct dependence of
the development of glaucoma on the level of fluctuations of the main meteorological
elements – atmospheric pressure, relative humidity of air, solar fusion and thermal regime
was noted. The scientific foundations have been created for the implementation of effective
methods of meteorological prevention off glaucoma in the sharply continental climate of

Automated Identification of Glaucoma from Fundus Images using Deep learning Techniques

Ajitha S; Dr. M V Judy; Dr. Meera N; Dr. Rohith N

European Journal of Molecular & Clinical Medicine, 2020, Volume 7, Issue 2, Pages 5449-5458

Glaucoma has arisen as the one of the main sources of visual impairment. A typical technique for diagnosing glaucoma is through assessment optic nerve head by an experienced ophthalmologist. This methodology is arduous and burns-through a lot of time. Despite the fact that the analysis of this infection has not yet been discovered, the period of primary identification can preserve from the glaucoma. Subsequently, customary glaucoma screening is basic and suggested. The issue can be settled by applying machine learning techniques for glaucoma detection. We present an automated glaucoma screening framework using a pre-trained Alexnet model with SVM classifier to enhance the classification accuracy . In this study, we used three publicly available dataset as HRF, Origa and Drishti_GS1 dataset. The proposed model achieved the image classification accuracy of 91.21%. This study showed that using pre-trained CNN with SVM for glaucoma detection showed greater accuracy in automatic image classification than just CNN or SVM.