Early Screening For Diabetic Retinopathy Research Articles

N-glycosylation of disease-specific haptoglobin for the early screening of diabetic retinopathy.

Diabetic retinopathy (DR), as one of the microvascular complications of diabetes, is a leading cause of acquired vision loss. Most DR cases are detected in the advanced stage through fundoscopy, making molecular biomarkers urgently needed for early diagnosis of DR. Serum disease-specific haptoglobin-β (Hp-β) chains of 100 patients with type 2 diabetes mellitus (T2DM) and 156 T2DM patients with non-proliferative diabetic retinopathy (NPDR) were separated using polyacrylamide gel electrophoresis. After in-gel digestion and enrichment, the intact N-glycopeptides were detected by mass spectrometry. Fucosylation of Hp-β was significantly increased and sialylation of Hp-β was significantly decreased in background DR (BDR, an early-stage DR) patients compared with non-diabetic retinopathy patients (p<0.05) and yielded area under curves (AUCs) of 0.801 and 0.829 in training and validation groups, respectively, which had an advantage over glycated hemoglobin A1c (AUC ≤ 0.691). Moreover, a significant increase in sialylated Hp-β was found in severe NPDR patients compared with BDR patients and yielded an AUC of 0.828 to distinguish severe NPDR from BDR. Changes in Hp-β glycosylation are closely related to DR, and may be used for early diagnosis and screening of DR.

Assessment of macular findings by OCT angiography in patients without clinical signs of diabetic retinopathy: radiomics features for early screening of diabetic retinopathy

This cross-sectional study aimed to quantitatively analyze the optical coherence tomography angiography (OCTA) images using MATLAB-based software and evaluate the initial changes in macular vascular density and the distortion of the foveal avascular zone (FAZ), before the clinical appearance of diabetic retinopathy. For this purpose, 21 diabetic patients without any clinical features indicating DR, and 21 healthy individuals matched with patients based on their demographic characteristics were included. Macular thickness, macular vascular density, and morphological changes of FAZ were assessed using OCTA. The diagnostic ability of morphological parameters was evaluated by receiver operating curve analysis. The intraclass correlation coefficient (ICCC) index was used to check the consistency of the extracted values. There was no significant difference in age, gender, LogMAR visual acuity, spherical equivalent, and intra-ocular pressure amongst patients and controls. No correlation was found between age and the FAZ area as well as vascular density. The vascular structure of the superficial layer showed FAZ enlargement, reduced vascular density in the macular area, and significant deviations of FAZ shape parameters (convexity and Frequency Domain Irregularity) in patients compared with healthy individuals. Measurements were highly correlated between separate imaging sessions with ICCC of over 0.85 for all parameters. The represented data suggests that radiomics parameters can be applied as both an early screening tool and guidance for better follow-up of diabetic patients who have not had any sign of DR in fundoscopic exams.

Early Screening for Diabetic Retinopathy in Newly Diagnosed Type 2 Diabetes and Its Effectiveness in Terms of Morbidity and Clinical Treatment: A Nationwide Population-Based Cohort.

PurposeTo characterize the association between the frequency of screening for diabetic retinopathy (DR) and the detection of DR in patients with newly diagnosed type 2 diabetes mellitus (T2DM).MethodsThis nationwide population-based cohort study used data from the National Health Insurance Research Database to identify adult patients who were newly diagnosed with T2DM between 2000 and 2004. Data from their follow-up Diabetic retinopathy (DR) treatments over the next 10 years following diagnosis were also analyzed.ResultsThe 41,522 subjects were respectively assigned to a periodic screening group (n = 3850) and nonperiodic screening group (n = 37,672). Significant differences were observed between the two groups in terms of age, Charlson Comorbidity Index (CCI), sex, DR treatment, and the prevalence of DR. The association between periodic screening and DR treatment, only the elderly, female, and patient with severe CCI status showed the significance in the further stratified analysis.ConclusionPeriodic screening (annual or biannual screening in the first 5 years) was more effective than nonperiodic screening in detecting instances of DR in the middle-to-advanced aged group but not among younger patients. Screening pattern did not have a significant effect on the likelihood of DR-related treatment during the 5-year follow-up. It appears that a tight screening schedule for the first 5 years after diagnosis with diabetes is not necessary.

Deep Red Lesion Classification for Early Screening of Diabetic Retinopathy

Diabetic retinopathy (DR) is an asymptotic and vision-threatening complication among working-age adults. To prevent blindness, a deep convolutional neural network (CNN) based diagnosis can help to classify less-discriminative and small-sized red lesions in early screening of DR patients. However, training deep models with minimal data is a challenging task. Fine-tuning through transfer learning is a useful alternative, but performance degradation, overfitting, and domain adaptation issues further demand architectural amendments to effectively train deep models. Various pre-trained CNNs are fine-tuned on an augmented set of image patches. The best-performing ResNet50 model is modified by introducing reinforced skip connections, a global max-pooling layer, and the sum-of-squared-error loss function. The performance of the modified model (DR-ResNet50) on five public datasets is found to be better than state-of-the-art methods in terms of well-known metrics. The highest scores (0.9851, 0.991, 0.991, 0.991, 0.991, 0.9939, 0.0029, 0.9879, and 0.9879) for sensitivity, specificity, AUC, accuracy, precision, F1-score, false-positive rate, Matthews’s correlation coefficient, and kappa coefficient are obtained within a 95% confidence interval for unseen test instances from e-Ophtha_MA. This high sensitivity and low false-positive rate demonstrate the worth of a proposed framework. It is suitable for early screening due to its performance, simplicity, and robustness.

Involvement of CircRNA Expression Profile in Diabetic Retinopathy and Its Potential Diagnostic Value.

Background: Circular RNAs (circRNAs), a class of non-coding and undegradable RNAs, play many pathological functions by acting as miRNA sponges, interacting with RNA-binding proteins, and others. The recent literature indicates that circRNAs possess the advanced superiority for the early screening of diabetic retinopathy (DR). Methods: CircRNA sources of peripheral blood mononuclear cells (PBMCs) from healthy controls (n = 4), diabetes mellitus patients (DM) (n = 4), and DR patients (n = 4) were extracted for circular RNA microarray analysis. Enriched biological modules and signaling pathways were analyzed by Gene Ontology Enrichment and Kyoto Encyclopedia of Genes and Genomes analysis, respectively. Real-time quantitative reverse transcription PCR (RT-qPCR) was performed to validate differentiated levels of several circRNAs (fold change ≥2, p < .05) in different groups of healthy control subjects (n = 20), DM patients (n = 60), and DR patients (n = 42). Based on our clinical data from DR, the diagnostic performance of candidate circRNAs was measured by operating characteristic curves (ROCs). Subsequently, their circRNA–miRNA networks were constructed by bioinformatics analysis. Results: Circular RNA microarray analysis was performed, and 2,452 and 289 circRNAs were screened with differential expression in DR patients compared to healthy controls and DM patients, respectively. Enrichment analyses showed that circRNAs in DR patients were enriched in extracellular matrix (ECM)–receptor interaction and focal adhesion pathways. The top 5 differential circRNAs in circRNA microarray analysis were subsequently quantified and verified by RT-qPCR. Consistently, a significant 2.2-fold reduction of hsa_circ_0095008 and 1.7-fold increase in hsa_circ_0001883 were identified in DR patients compared to DM patients. Meanwhile, the area under curves of hsa_circ_0095008 and hsa_circ_0001883 were 0.6710 (95% CI, 0.5646–0.7775) (p = 0.003399) and 0.6071 (95% CI, 0.4953–0.7189) (p = 0.06644), respectively, indicating a good diagnostic value. Conclusion: Our study provided a new sight for the pathological mechanism of DR and revealed the potential value of hsa_circ_0095008 and hsa_circ_0001883 as diagnostic biomarkers for the early diagnosis of DR patients.

Prevalence of diabetic retinopathy among diabetic patients in Northwest Ethiopia-A cross sectional hospital based study.

BackgroundDiabetic retinopathy is the most common microvascular complication of diabetes mellitus on eye and it is the leading cause of visual impairment among productive segment of the population. Globally, the prevalence of diabetic retinopathy is reported to be 27%. In Ethiopia, sufficient data is lacking on the prevalence of diabetic retinopathy as well as information on its predisposing factors. The study was required to assess the prevalence of diabetic retinopathy and its predisposing factors in diabetic patients attending at a General Hospital in Ethiopia.MethodsAn institution based cross sectional study was employed on 331 diabetic patients recruited with a systematic random sampling technique. Data were collected through structured questionnaire, tracing patients’ medical folder and ocular health examination. Data were analyzed with Statistical Package for Social Science Version 20. Logistic regression methods of analysis were used to figure out predisposing factors of diabetic retinopathy. Adjusted odds ratio with 95% confidence interval was used to determine the strength of association.ResultA total of 331 diabetic patients completed the study with a response rate of 99.10%. The median duration of diabetes was 5 years. The prevalence of diabetic retinopathy was 34.1% (95%Confidence Interval (CI): 28.7%-39.3%). Low family monthly income (Adjusted Odds Ratio (AOR) = 7.43, 95% CI: 2.44–22.57), longer duration of diabetes (AOR = 1.44, 95% CI: 1.30–1.58), poor glycemic control (AOR = 4.76, 95%CI: 2.26–10.00), and being on insulin treatment alone (AOR = 3.85, 95%CI: 1.16–12.74) were independently associated with diabetic retinopathy.Conclusion and recommendationThe prevalence of diabetic retinopathy was 34.1%, higher than national and global figures. Low family monthly income, longer duration of diabetes, poor glucose control and being on insulin treatment alone were important risk factors of diabetic retinopathy. Proper diabetes self management and early screening of diabetic retinopathy in all diabetic patients were recommended.

Locust based genetic classifier for the diagnosis of diabetic retinopathy

Due to the ongoing advancement in detection of critical diseases, there is a need in revamping the accurate diagnosis of diabetic retinopathy (DR). In this current study, locust based genetic classifier plays a crucial role in early screening of DR and to determine the exact location of the affected region of retina. Initially, preprocessing is performed to remove the obnoxious information such as noise present in the image and helps to transform the RGB format to gray scale image. It is done by applying wiener filter technique. After removing the obnoxious information, exudate segmentation is performed. After splitting out the image into samples, feature extraction is applied by Gabor based region covariance matrix. It helps to reduce the feature in the DIARETDB1 dataset by obtaining a new feature. After obtaining the feature, whale optimization is performed to pick out the best features such as mean, exudate area, optic distance and standard deviation and finally locust based genetic classifier is used to analogize between trained and test set data and it provides infallible information to the ophthalmologist to provide timely treatments. Comparative analysis is performed. It reveals the significant performance of the current approach over other existing SVM and CNN classifier. The results obtained from the current study shows a promising future and it achieves an accuracy of 98.9%.

Prevalence of Diabetic Retinopathy and Associated Risk Factors among Adult Diabetes Attending at Debre Tabor General Hospital, Northwest Ethiopia

Aim: To assess the prevalence of diabetic retinopathy and its associated risk factors among adult diabetes at Debre Tabor General Hospital, Debre Tabor, Northwest, Ethiopia. Methodology: A cross sectional study was conducted at Debre Tabor General Hospital from June 29-August 28, 2020. A systematic random sampling technique was employed to select study participants. Interviewer based semistructured questioner, document review and physical examination were applied to collect the data. Labeling of diabetic retinopathy was done based on the Proposed International Clinical Diabetic Retinopathy and Severity Scale. Only the eye with the higher grade of retinopathy for each participant was included. Result: A total of 306 participants completed the study with a response rate of 97.7%. The median duration of diabetes was 4 (Range=7) years. The prevalence of diabetic retinopathy was 31.4% (95% Confidence Interval: 26.1%-36.3%). Low family monthly income (Adjusted Odds Ratio=7.4, 95% Confidence Interval 2.4-22.9), longer duration of diabetes (Adjusted Odds Ratio=27, 95% Confidence Interval 11.5-63.6) and poor glycemic control (Adjusted Odds Ratio=3.2, 95%Confidence Interval 1.5-6.7) were significantly associated with diabetic retinopathy. Conclusion and Recommendation: The prevalence of diabetic retinopathy washigh. Coordinated early screening of diabetic retinopathy in all adult diabetes was recommended.

Role of early screening for diabetic retinopathy in patients with diabetes mellitus: an overview.

Diabetes has emerged as a major public health problem in India. It is estimated that there were 40 million persons with diabetes in India in 2007 and this number is predicted to rise to almost 70 million by 2025. The impact of rapid urbanization, industrialization and lifestyle changes has led to an increasing trend in prevalence of diabetes and its associated complications such as neuropathy, nephropathy, vascular diseases (cardiac, cerebral and peripheral) and retinopathy. Diabetic retinopathy is a important cause of avoidable blindness in India. Treatment interventions at early stages of diabetic retinopathy can reduce burden of blindness due to diabetic retinopathy. With the available cost-effective methods of early screening, appropriate strategies/models need to be developed. Such models need to have a well-developed mode for screening, diagnosis and referral at each hierarchal level beginning from primary health centers to specialized institutes for eye care. The National Program for Control of Blindness of India recommends opportunistic screening for identification of diabetic retinopathy. Every opportunity of contact with high-risk cases for diabetes and/or diabetic retinopathy should be utilized for screening, diagnosis and referral. All the stakeholders including the private sector will need to play a role. Along with this, awareness generation and behavior change amongst the diabetics and care support systems should also be part of the overall model. A major role can be played by community participation and improving the health seeking behavior among diabetics in order to reach a larger population and increasing the compliance for continued care.