scholarly journals Evaluation of Macular Function Tests with Diabetic Retinopathy

2021 ◽  
Vol 10 (20) ◽  
pp. 1463-1468
Author(s):  
Abhinav Ashok Agrawal ◽  
Niharika Krishna Shetty
Keyword(s):  
Diabetic Retinopathy ◽  
Early Detection ◽  
Vision Loss ◽  
Stress Test ◽  
Clinical Stage ◽  
Posterior Segment ◽  
Paroxysmal Supraventricular Tachycardia ◽  
Macular Function ◽  
Cross Sectional ◽  
Amsler Grid

BACKGROUND Diabetic retinopathy (DR) is reported to be the leading cause of vision loss in adults aged between 20–74 years. Early detection and prompt evaluation is essential to prevent the blindness related to diabetes. Simple and quick out-patient department (OPD) tests are essential for early detection of maculopathy in diabetes, which will enhance the treatment and rehabilitation. The purpose of this study was to evaluate the correlation of photo stress test and Amsler’s grid test with diabetic retinopathy and maculopathy. We also wanted to study the variation in photo stress test and the patterns of visual disturbances using Amsler grid in different stages of diabetic retinopathy. METHODS All patients with type 2 diabetes were included for a study duration of one year. A cross sectional study design was planned. Anterior and posterior segment evaluation was done. Photo stress test was performed with a torch light and the recovery time was recorded. Amsler grid was performed on each patient at 33 cm distance. The results were recorded in terms of micropsia, macropsia, metamorphopsia, and any other ill-defined scotomas. The posterior segment, in terms of vitreous and retina was evaluated with 20 D lens on an indirect ophthalmoscopy and the macular details were evaluated on a 90 D lens with slit lamp biomicroscopy. Early Treatment Diabetic Retinopathy (ETDR) classification was used for classifying the retinopathy and the maculopathy stage in patients. RESULTS There was a correlation between paroxysmal supraventricular tachycardia (PST) and the stage of diabetic retinopathy; between PST and diabetic maculopathy; with increasing severity of diabetic retinopathy and maculopathy associated with higher or prolonged PST values. No correlation was found between Amsler’s grid and DR staging. CONCLUSIONS PST can be used to assess severity of diabetic retinopathy in a pre-clinical and early clinical stage in places where access to the equipment for posterior segment evaluation is unavailable. Amsler’s grid evaluation did not have a role in evaluation of macula in cases of diabetic retinopathy. KEY WORDS Macula, Amsler, Photostress Test, Metamorphopsia

Beyond vision loss: the independent impact of diabetic retinopathy on vision-related quality of life in a Chinese Singaporean population

2018 ◽  
Vol 103 (9) ◽  
pp. 1314-1319 ◽  
Author(s):  
Eva K Fenwick ◽  
Ryan E K Man ◽  
Alfred Tau Liang Gan ◽  
Neelam Kumari ◽  
Charlene Wong ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Diabetic Retinopathy ◽  
Vision Loss ◽  
Well Being ◽  
Linear Regression Models ◽  
Cross Sectional ◽  
Significant Difference ◽  
Related Quality ◽  
The Impact

Background/aimsTo assess the independent impact of diabetic retinopathy (DR) on three domains of vision-related quality of life (VRQoL) in a Chinese Singapore population.MethodsThe Singapore Chinese Eye Study (n=3353; 2009–2011) was a population-based, prospective, cross-sectional study conducted at the Singapore Eye Research Institute. The study population included 292 adults with diabetes, with and without DR. DR (better eye) was categorised as presence and absence of any DR; severity of DR (no vision-threatening DR (VTDR); severe non-proliferative DR (NPDR); PDR and/or clinically significant macular oedema and VTDR). Our main outcome was VRQoL which was measured using Rasch-calibrated scores from the ‘Reading’, ‘Mobility’ and ‘Emotional’ domains of the Impact of Vision Impairment questionnaire. The relationship between DR and VRQoL was assessed using multiple linear regression models.ResultsOf the 292 individuals (mean age 61.35 ± 9.66 years; 55.8% male), 201 (68.8%), 49 (16.8%), 20 (6.8%), 22 (7.5%) and 27 (9.2%) had no DR, minimal-mild NPDR, moderate-severe NPDR, PDR and VTDR, respectively. Any DR and VTDR were independently associated with 6% and 12% worse Reading scores and 7% and 18% poorer Emotional well-being, respectively, compared with those without DR. These associations persisted after separate adjustment for visual impairment and presenting visual acuity. No significant difference was found in the Mobility domain between persons with and without DR.ConclusionsWe documented that DR, particularly VTDR, was independently associated with restrictions in Reading and Emotional well-being. Understanding factors underlying the detrimental DR-VRQoL relationship may optimise rehabilitation outcomes for individuals with DR.

scholarly journals Early Detection of Diabetic Retinopathy Using PCA-Firefly Based Deep Learning Model

Electronics ◽  
2020 ◽  
Vol 9 (2) ◽  
pp. 274 ◽  
Author(s):  
Thippa Reddy Gadekallu ◽  
Neelu Khare ◽  
Sweta Bhattacharya ◽  
Saurabh Singh ◽  
Praveen Kumar Reddy Maddikunta ◽  
...  
Keyword(s):  
Machine Learning ◽  
Diabetic Retinopathy ◽  
Deep Learning ◽  
Early Detection ◽  
Dimensionality Reduction ◽  
Vision Loss ◽  
Principal Component ◽  
Screening Methods ◽  
Learning Approaches ◽  
Time Period

Diabetic Retinopathy is a major cause of vision loss and blindness affecting millions of people across the globe. Although there are established screening methods - fluorescein angiography and optical coherence tomography for detection of the disease but in majority of the cases, the patients remain ignorant and fail to undertake such tests at an appropriate time. The early detection of the disease plays an extremely important role in preventing vision loss which is the consequence of diabetes mellitus remaining untreated among patients for a prolonged time period. Various machine learning and deep learning approaches have been implemented on diabetic retinopathy dataset for classification and prediction of the disease but majority of them have neglected the aspect of data pre-processing and dimensionality reduction, leading to biased results. The dataset used in the present study is a diabetes retinopathy dataset collected from the UCI machine learning repository. At its inceptions, the raw dataset is normalized using the Standardscalar technique and then Principal Component Analysis (PCA) is used to extract the most significant features in the dataset. Further, Firefly algorithm is implemented for dimensionality reduction. This reduced dataset is fed into a Deep Neural Network Model for classification. The results generated from the model is evaluated against the prevalent machine learning models and the results justify the superiority of the proposed model in terms of Accuracy, Precision, Recall, Sensitivity and Specificity.

scholarly journals Andalusian program for early detection of diabetic retinopathy: implementation and 15-year follow-up of a population-based screening program in Andalusia, Southern Spain

2020 ◽  
Vol 8 (1) ◽  
pp. e001622 ◽  
Author(s):  
Rafael Rodriguez-Acuña ◽  
Eduardo Mayoral ◽  
Manuel Aguilar-Diosdado ◽  
Reyes Rave ◽  
Beatriz Oyarzabal ◽  
...  
Keyword(s):  
Diabetic Retinopathy ◽  
Early Detection ◽  
Vision Loss ◽  
Screening Program ◽  
Target Population ◽  
Population Based ◽  
Annual Incidence ◽  
Population Coverage ◽  
Visual Disability ◽  
The Impact

IntroductionDiabetic retinopathy (DR) is a preventable cause of vision loss and blindness worldwide. We aim at analyzing the impact of a population-based screening program of DR using retinal photography with remote reading in terms of population coverage, diagnosis of asymptomatic DR and impact on visual disability, in the region of Andalusia, Spain, in the period 2005–2019.Research design and methodsDescriptive study. Sociodemographic and clinical features included in the Andalusian program for early detection of diabetic retinopathy (APDR) were analyzed. Population coverage, annual incidence of DR, and DR severity gradation were analyzed. Estimated data on prevalence and incidence of legal blindness due to DR were included.Results407 762 patients with at least one successful DR examination during the study period were included. Most of the performed retinographies (784 584, 84.3%) were ‘non-pathological.’ Asymptomatic DR was detected in 52 748 (5.9%) retinographies, most of them (94.2%) being classified as ‘mild to moderate non-proliferative DR.’ DR was detected in 44 815 patients, while sight-threatening DR (STDR) in 6256 patients; cumulative incidence of DR was 11.0% and STDR was 1.5%, as DR and STDR was detected in 44 815 and 6256 patients, respectively. Annual incidence risk per patient recruitment year progressively decreased from 22.0% by January 2005 to 3.2% by June 2019.ConclusionsImplementation of a long-term population-based screening program for early detection of DR is technically feasible and clinically viable. Thus, after 15 years of existence, the program has enabled the screening of the vast majority of the target population allowing the optimization of healthcare resources and the identification of asymptomatic DR.

scholarly journals Deep Learning Approach for Automatic Microaneurysms Detection

Sensors ◽  
2022 ◽  
Vol 22 (2) ◽  
pp. 542
Author(s):  
Muhammad Mateen ◽  
Tauqeer Safdar Malik ◽  
Shaukat Hayat ◽  
Musab Hameed ◽  
Song Sun ◽  
...  
Keyword(s):  
Diabetic Retinopathy ◽  
Deep Learning ◽  
Early Detection ◽  
Sensitivity And Specificity ◽  
Classification Accuracy ◽  
Vision Loss ◽  
State Of The Art ◽  
The State ◽  
Learning Approach ◽  
Manual Analysis

In diabetic retinopathy (DR), the early signs that may lead the eyesight towards complete vision loss are considered as microaneurysms (MAs). The shape of these MAs is almost circular, and they have a darkish color and are tiny in size, which means they may be missed by manual analysis of ophthalmologists. In this case, accurate early detection of microaneurysms is helpful to cure DR before non-reversible blindness. In the proposed method, early detection of MAs is performed using a hybrid feature embedding approach of pre-trained CNN models, named as VGG-19 and Inception-v3. The performance of the proposed approach was evaluated using publicly available datasets, namely “E-Ophtha” and “DIARETDB1”, and achieved 96% and 94% classification accuracy, respectively. Furthermore, the developed approach outperformed the state-of-the-art approaches in terms of sensitivity and specificity for microaneurysms detection.

scholarly journals Association between sociodemographic variables and awareness of diabetic retinopathy among type 2 diabetic patients

2020 ◽  
Vol 8 (1) ◽  
pp. 63
Author(s):  
Kasim Yasar Kannappillil Muhammedali ◽  
V. Sahasranamam ◽  
Saji Nair Ambika
Keyword(s):  
Diabetic Retinopathy ◽  
Early Detection ◽  
Positive Association ◽  
Demographic Variables ◽  
Diabetic Patients ◽  
Type 2 Diabetic Patients ◽  
Significant Positive Association ◽  
Cross Sectional ◽  
Screening Programs ◽  
Duration Of Diabetes

Background: Early detection of diabetic retinopathy (DR) is the most important factor in reducing the blinding complications due to diabetes. Study of the various socio-demographic factors affecting awareness of DR will help us to formulate effective screening programs for early detection. Objectives of the study were to find the sociodemographic determinants associated with awareness of DR and to evaluate the association of stage of DR with awareness about diabetic retinopathy.Methods: A cross sectional study was conducted among 384 patients who had been diagnosed with diabetes mellitus in various medical camps and diabetic clinics at Thiruvananthapuram. Socio demographic variables and awareness were assessed using structured self-administered questionnaire. Dilated fundus evaluation was done and retinopathy classified. Data entered to excel sheet and analysis done using statistical software (SPSS version 20).Results: Among the 384 patients, 44.9% were diagnosed to have diabetic retinopathy. Among the diagnosed 41.6% had mild non proliferative DR (NPDR), 33.0% had moderate NPDR, 11.45% had severe NPDR. 13.4% of subjects were diagnosed to have proliferative DR. 53.1% of the subjects with diabetic retinopathy had clinically significant macular edema. There was no statistically significant association between the stage of DR to awareness. Among the socio demographic variables, significant positive association with level of awareness was obtained for duration of diabetes (OR=10.96; p=0.004)Conclusions: Duration of diabetes was significantly associated with level of awareness. There was no statistically significant association between the stage of diabetic retinopathy to awareness. This signifies the urgent need to intensify our diabetic retinopathy awareness programs.

scholarly journals Risk Factors for Diabetic Retinopathy

2021 ◽  
Vol 3 (2) ◽  
pp. 66-74
Author(s):  
Naufallah Dinda Harumi ◽  
Ramzi Amin
Keyword(s):  
Risk Factors ◽  
Diabetic Retinopathy ◽  
Total Cholesterol ◽  
Vision Loss ◽  
Significant Risk ◽  
Sampling Technique ◽  
P Value ◽  
Cross Sectional ◽  
Chronic Hyperglycemia ◽  
Hba1c Levels

Abstract Introduction.Diabetic retinopathy is a progressive microangiopathy characterized by damage and occlusion of small blood vessels. The earliest pathologic changes are thickening of the capillary endothelial basement membrane and a reduction in the number of pericits. Diabetic retinopathy is the main cause of vision loss in type 1 of DM patients and has various risk factors such as chronic hyperglycemia, hypertension, hypercholesterolemia, and elevated HbA1C levels. Methods.This research was conducted using a descriptive observational analytic method with a cross sectional approach at The Eye Polyclinic (RSUP) Dr. Mohammad Hoesin Palembang used secondary data on diabetic retinopathy patients. The sample consisted of 64 patients with a total sampling technique, there were 50 patients who met the inclusion criteria. Results.There was a significant relationship between HbA1C levels (p value = 0.050) with a PR value = 1.463 and total cholesterol (p value = 0.038) with a PR value = 1.667 for diabetic retinopathy. Conclusion.HbA1C levels and total cholesterol are significant risk factors for diabetic retinopathy.

scholarly journals Diabetic Retinopathy Screening in Patients with Diabetes Using a Handheld Fundus Camera: The Experience from the South-Eastern Region in Hungary

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Dóra Júlia Eszes ◽  
Dóra Júlia Szabó ◽  
Greg Russell ◽  
Csaba Lengyel ◽  
Tamás Várkonyi ◽  
...  
Keyword(s):  
Diabetic Retinopathy ◽  
Health Behavior ◽  
Vision Loss ◽  
Significant Proportion ◽  
Eastern Region ◽  
Related Factors ◽  
Cross Sectional ◽  
Screening Programs ◽  
Fundus Camera ◽  
South Eastern

Purpose. Diabetic retinopathy (DR) is the leading cause of vision loss among active adults in industrialized countries. We aimed to investigate the prevalence of diabetes mellitus (DM), DR and its different grades, in patients with DM in the Csongrád County, South-Eastern region, Hungary. Furthermore, we aimed to detect the risk factors for developing DR and the diabetology/ophthalmology screening patterns and frequencies, as well as the effect of socioeconomic status- (SES-) related factors on the health and behavior of DM patients. Methods. A cross-sectional study was conducted on adults (>18 years) involving handheld fundus camera screening (Smartscope Pro Optomed, Finland) and image assessment using the Spectra DR software (Health Intelligence, England). Self-completed questionnaires on self-perceived health status (SPHS) and health behavior, as well as visual acuity, HbA1c level, type of DM, and attendance at healthcare services were also recorded. Results. 787 participants with fundus camera images and full self-administered questionnaires were included in the study; 46.2% of the images were unassessable. T1D and T2D were present in 13.5% and 86.5% of the participants, respectively. Among the T1D and T2D patients, 25.0% and 33.5% had DR, respectively. The SES showed significant proportion differences in the T1D group. Lower education was associated with a lower DR rate compared to non-DR (7.7% vs. 40.5%), while bad/very bad perceived financial status was associated with significantly higher DR proportion compared to non-DR (63.6% vs. 22.2%). Neither the SPHS nor the health behavior showed a significant relationship with the disease for both DM groups. Mild nonproliferative retinopathy without maculopathy (R1M0) was detected in 6% and 23% of the T1D and T2D patients having DR, respectively; R1 with maculopathy (R1M1) was present in 82% and 66% of the T1D and T2D groups, respectively. Both moderate nonproliferative retinopathy with maculopathy (R2M1) and active proliferative retinopathy with maculopathy (R3M1) were detected in 6% and 7% of the T1D and T2D patients having DR, respectively. The level of HbA1c affected the attendance at the diabetology screening ( HbA 1 c > 7 % associated with >50% of all quarter-yearly attendance in DM patients, and with 10% of the diabetology screening nonattendance). Conclusion. The prevalence of DM and DR in the studied population in Hungary followed the country trend, with a slightly higher sight-threatening DR than the previously reported national average. SES appears to affect the DR rate, in particular, for T1D. Although DR screening using handheld cameras seems to be simple and dynamic, much training and experience, as well as overcoming the issue of decreased optic clarity is needed to achieve a proper level of image assessability, and in particular, for use in future telemedicine or artificial intelligence screening programs.

scholarly journals Early detection of diabetic retinopathy among type one diabetic patients

2017 ◽  
Vol 1 (1) ◽  
pp. 17
Author(s):  
Mohammad Alkot
Keyword(s):  
Diabetes Mellitus ◽  
Diabetic Retinopathy ◽  
Early Detection ◽  
Family Health ◽  
Diabetic Patients ◽  
Fundus Examination ◽  
Cross Sectional ◽  
The Family ◽  
The World ◽  
Type One Diabetes

Background: Diabetic retinopathy (DR) is one of the leading causes of blindness in the world. It develops in nearly all individuals with type one diabetes and in more than 75% of individuals with type two who survive for over twenty years with the disease. Objective: To clarify the importance of early detection of DR, and specifically to determine its prevalence among type one diabetic patients. Methods: A cross-sectional comparative study was conducted on all registered type one diabetic patients attending Al-Shohada family health center (FHC); during the period from June to August 2015. The study included 105 patients with type one diabetes mellitus. They were subjected to a predesigned questionnaire, and their data were retrieved by checking their files. They were referred for fundus examination by an ophthalmologist. Results: The prevalence of DR among type one diabetic patients was 51.3%, and it was 62.8% among the patients who had never undergone fundus examination before. In 57% of the patients, the barrier for DR screening was negligence and lack of awareness about its importance. Prevalence of DR depends on the duration in addition to the degree diabetes control. Conclusion: Most of type one diabetic patients are aware of its complications; however, there is little awareness about the importance of screening for DR, which together with negligence constitutes the main barriers to its screening. Therefore, the family physician plays an important role in dealing with these problems for early detection and management of diabetic retinopathy.

scholarly journals Nanomedicine for Treating Diabetic Retinopathy Vascular Degeneration

2021 ◽  
Vol 1 (3) ◽  
pp. 306-322
Author(s):  
Tatiana Borodina ◽  
Dmitry Kostyushev ◽  
Andrey A. Zamyatnin ◽  
Alessandro Parodi
Keyword(s):  
Diabetic Retinopathy ◽  
Vision Loss ◽  
Surface Modifications ◽  
Posterior Segment ◽  
Chronic Hyperglycemia ◽  
Pathological Conditions ◽  
Current Therapies ◽  
Inflammatory Drugs ◽  
Topical Treatments ◽  
Number Of Injections

The incidence of diabetes and the pathological conditions associated with chronic hyperglycemia is increasing worldwide. Among them, diabetic retinopathy represents a leading cause of vision loss, causing a significant structural and functional impairment of the retinal and choroidal capillary network. Current therapies include anti-angiogenic and anti-inflammatory drugs administered through repetitive and invasive intraocular injections, and associated with significant adverse effects. The presence of ocular barriers affects the efficiency of topically administered therapeutics for treating the posterior segment of the eye. In this scenario, nanomedicine could improve current therapies for diabetic retinopathy by providing tools that can decrease the number of injections thanks to their controlled release properties, while some materials showed a natural ability to mitigate pathological neo-angiogenesis. Moreover, specific surface modifications could open new scenarios for the development of topical treatments. This review describes current advances in generating nanomedicine for diabetic retinopathy, focusing on the properties of the different materials tested explicitly for this purpose.

scholarly journals Blood Vessels Detection of Diabetic Retinopathy from Retinal Fundus Image using Image Processing Techniques

2020 ◽  
Vol 18 (44) ◽  
pp. 1-16
Author(s):  
Faleh H. Mahmood
Keyword(s):  
Diabetic Retinopathy ◽  
Early Detection ◽  
Blood Vessel ◽  
Blood Vessels ◽  
Vision Loss ◽  
Digital Camera ◽  
Eye Diseases ◽  
Morphological Operations ◽  
Structuring Element ◽  
Processing Techniques

 abstract Early detection of eye diseases can forestall visual deficiency and vision loss. There are several types of human eye diseases, for example, diabetic retinopathy, glaucoma, arteriosclerosis, and hypertension. Diabetic retinopathy (DR) which is brought about by diabetes causes the retinal vessels harmed and blood leakage in the retina. Retinal blood vessels have a huge job in the detection and treatment of different retinal diseases. Thus, retinal vasculature extraction is significant to help experts for the finding and treatment of systematic diseases. Accordingly, early detection and consequent treatment are fundamental for influenced patients to protect their vision. The aim of this paper is to detect blood vessels from the digital fundus images. In this research, a novel methodology was introduced to separate retinal blood vessel network. The suggested system in this research involves four stages, after image acquisition, the pre-processes of the image to preparing and improving the image quality is the first stage. Morphological operations are used for the detection of blood vessels. In this research, we will use two morphological operations: erosion and dilation. These two operations have two inputs, a binary image, and a structuring element object. We will use two morphological processes (boundary extraction and top, bottom hat transform). Before these operations, we will use applying a canny edge detector technique to obtain the edges of the retina image. The technique is tried on shading retinal pictures acquired from STARE and DRIVE databases which are accessible on the web as well as the samples of retinal images were obtained from the digital camera from Ibn Al-Haytham specialist Hospital for Eye in Baghdad, Iraq. Good results and effective were obtained for blood vessel detected and extract  

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