Relationship between macular perfusion and lesion distribution in diabetic retinopathy.

BACKGROUND/OBJECTIVES: To assess the relationship between macular vessel density metrics and foveal avascular zone (FAZ) characteristics on optical coherence tomography angiography (OCTA) and lesion distribution in eyes with diabetic retinopathy (DR). SUBJECTS/METHODS: Patients with DR who underwent both Optos ultrawidefield (UWF) pseudocolor imaging and macular OCTA (Cirrus Angioplex, 6 × 6 mm) were included in this cross-sectional observational study. The distribution of DR lesions was assessed by comparing each of the peripheral ETDRS extended fields (3-7) against their corresponding ETDRS field, hence eyes were defined as either having predominantly peripheral lesions (PPL) or predominantly central lesions (PCL). En face OCTA images from the superficial and deep capillary plexuses (SCP and DCP) were then analysed using Image J software. Perfusion density (PD), vessel length density (VLD), and fractal dimensions (FD) were calculated following binarization and skeletonization of the images. RESULTS: Out of 344 eyes, 116 (33.72%) eyes had PPL and 228 (66.28%) eyes had PCL. For all DRSS levels, VLD, PD, and FD were not significantly different between eyes with PPL and PCL. The FAZ in eyes with PPL, however, was found to be more circular in shape compared to eyes with PCL (p = 0.037). CONCLUSION: Although the presence of PPL has been associated with a higher risk for diabetic retinopathy progression, the macular perfusion is similar in eyes with PPL and PCL. The FAZ is more circular in eyes with PPL, but the clinical relevance of this difference remains to be defined.

Cataract surgery outcomes in children and adolescents with type 1 diabetes mellitus.

PURPOSE: To report the outcomes of cataract surgery in children and adolescents with type 1 diabetes mellitus. METHODS: The medical records of all pediatric patients (<18 years of age) with a diagnosis of type 1 diabetes mellitus who had undergone surgery for cataract between January 2000 and December 2019 at a tertiary care center were reviewed retrospectively. RESULTS: A total of 27 eyes of 15 patients who met the inclusion criteria were included. Median age at cataract surgery was 13 (IQR, 9.5-16) years, and median follow-up was 3.8 (IQR, 1.25-7.2) years, with 11 eyes followed for more than 5 years. Visual acuity improved from a median preoperative value of 0.8 (IQR, 0.55-1.3) logMAR to 0.15 (IQR, 0-0.45) logMAR at final follow-up. Posterior capsular visual axis opacification in 40.7% and diabetic retinopathy in 14.8% were the common complications requiring additional intervention, including laser capsulotomy and panretinal photocoagulation, respectively. CONCLUSIONS: Cataract surgery in children and adolescents with type 1 diabetes leads to improvement in visual acuity. Proliferative diabetic retinopathy can lead to poor visual outcomes in these children. Visual axis opacification occurs at similar rates with or without primary posterior capsulorhexis.

Diagnostic Utility of Swept-Source OCT-Based Biometry and Fundus Photographs Compared to Spectral Domain OCT in Center-Involving Diabetic Macular Edema.

PURPOSE: This study was aimed to evaluate the agreement between the swept-source optical coherence tomography (SS-OCT)-based biometry, fundus photographs, and their combination, in comparison to the gold standard spectral-domain optical coherence tomography (SD-OCT) for the detection of center-involving diabetic macular edema (CI-DME). METHODS: We conducted a retrospective cross-sectional study involving 55 subjects (78 eyes) diagnosed with diabetic macular edema (DME) detected clinically and on SD-OCT (Carl Zeiss Meditec AG). Post-mydriatic 45-degree color fundus photograph (Crystal-Vue NFC-700), 1 mm macular scan obtained from SS-OCT-based biometry (IOL-Master 700), and macula cube scan obtained from SD-OCT was used to detect and grade DME into CI-DME and NCI-DME. RESULTS: Our findings revealed that SS-OCT-based biometry was noted to have a high sensitivity of 1 (0.94-1.00) and a specificity of 0.63 (0.31-0.89) in detecting CI-DME compared to the gold standard (SD-OCT). When combined with data from fundus photographs, specificity decreased to 0.32 (0.15-0.53). Fundus photographs alone exhibited a low sensitivity of 0.52 (0.38-0.64) and a specificity of 0.45 (0.16-0.76) in CI-DME detection. CONCLUSION: In conclusion, SS-OCT-based biometry can be used as an effective tool for the detection of CI-DME in diabetic patients undergoing cataract surgery and can serve as a screening tool in centers without SD-OCT facilities.

Diabetic Macular Edema (DME); Center Involving Diabetic Macular Edema (CI-DME); Non-Center Involving Diabetic Macular Edema (NCI-DME); Swept-Source Optical Coherence Tomography (SS-OCT); Spectral-Domain Optical Coherence Tomography (SD-OCT); Anti-Vascular Endothelial Growth Factor (Anti-VEGF); Central Retinal Thickness (CRT); Intra Retinal Fluid (IRF); Sub Retinal Fluid (SRF); Diabetic Retinopathy (DR); Non Proliferative Diabetic Retinopathy (NPDR); Proliferative Diabetic Retinopathy (PDR); Best Corrected Visual Acuity (BCVA); Glycosylated hemoglobin (HbA1c); Mean Spherical Error (MSE); Standard Deviation (SD); Positive Predictive value (PPV); Predictive value (PPV); Negative predictive value (NPV); Area under the Curve (AUC).

Posterior segment manifestations of Takayasu arteritis: A narrative review.

Ocular symptoms can be the presenting manifestation of Takayasu arteritis (TA) or could be indicative of disease reactivation. A review of published literature related to posterior segment manifestations of TA by using the keywords "Takayasu arteritis," "ophthalmic manifestations," "retina," "retinopathy," "ocular," "optic nerve," and "optic neuropathy" was performed. In total, 62 case reports and 12 case series were included. The majority of the articles were from Asia (n = 47, 64%). Females outnumbered males in the ratio of 7:1. The mean age of patients was 33 years (range: 8-78 years, SD: 13.5 years). In 58% (n = 41 out of 71) cases, ocular symptoms were the presenting manifestation of the underlying disease. Hypotensive retinopathy was found in 70% of eyes, and hypertensive retinopathy was found in 27%. The mean presenting visual acuity (VA) was +1.03 logMAR (range: -0.12 to 3, SD: 1.07), and at the final follow-up was +1.02 logMAR (range: -0.12 to 3, SD 1.17). VA improved in 34% (n = 29/86), remained stable in 45% (39/86), and worsened in 21% (18/86). The mean follow-up was 9 months (range: 0.5-204, SD: 16 months).

National prevalence of vision impairment and blindness and associated risk factors in adults aged 40 years and older with known or undiagnosed diabetes: results from the SMART-India cross-sectional study.

BACKGROUND: National estimates of the prevalence of vision impairment and blindness in people with diabetes are required to inform resource allocation. People with diabetes are more susceptible to conditions such as diabetic retinopathy that can impair vision; however, these are often missed in national studies. This study aims to determine the prevalence and risk factors of vision impairment and blindness in people with diabetes in India. METHODS: Data from the SMART-India study, a cross-sectional survey with national coverage of 42 147 Indian adults aged 40 years and older, collected using a complex sampling design, were used to obtain nationally representative estimates for the prevalence of vision impairment and blindness in people with diabetes in India. Vulnerable adults (primarily those who did not have capacity to provide consent); pregnant and breastfeeding women; anyone deemed too ill to be screened; those who did not provide consent; and people with type 1 diabetes, gestational diabetes, or secondary diabetes were excluded from the study. Vision impairment was defined as presenting visual acuity of 0·4 logMAR or higher and blindness as presenting a visual acuity of 1·0 logMAR or higher in the better-seeing eye. Demographic, anthropometric, and laboratory data along with geographic distribution were analysed in all participants with available data. Non-mydriatic retinal images were used to grade diabetic retinopathy, and risk factors were also assessed. FINDINGS: A total of 7910 people with diabetes were included in the analysis, of whom 5689 had known diabetes and 2221 were undiagnosed. 4387 (55·5%) of 7909 participants with available sex data were female and 3522 (44·5%) participants were male. The estimated national prevalence of vision impairment was 21·1% (95% CI 15·7-27·7) and blindness 2·4% (1·7-3·4). A higher prevalence of any vision impairment (29·2% vs 19·6%; p=0·016) and blindness (6·7% vs 1·6%; p<0·0001) was observed in those with ungradable images. In known diabetes, diabetic retinopathy (adjusted odds ratio [aOR] 3·06 [95% CI 1·25-7·51]), vision-threatening diabetic retinopathy (aOR 7·21 [3·52-14·75]), and diabetic macular oedema (aOR 5·41 [2·20-13·33]) were associated with blindness in adjusted analysis. Common sociodemographic risk factors for vision impairment and blindness include older age, lower educational attainment, and unemployment. INTERPRETATION: Based on the estimated 101 million people with diabetes in 2021 and the interpretation of the data from this study, approximately 21 million people with diabetes have vision impairment in India, of whom 2·4 million are blind. Higher prevalence is observed in those from lower socio-economic strata and policy makers should focus on these groups to reduce inequalities in health care. FUNDING: Global Challenge Research Fund of United Kingdom Research and Innovation through the Medical Research Council.

Association of eGFR with stages of diabetic retinopathy and age-related macular degeneration in Indian population.

PURPOSE: To investigate the influence of glomerular filtration rate in renal disease decline and its association with diabetic retinopathy (DR) and age-related macular degeneration (ARMD) in patients in South India. METHODS: A population-based cross-sectional study was conducted including participants with DR and ARMD recruited from urban and rural populations. The data collection included medical history, anthropometric measurements, and ophthalmic work-up. The estimated glomerular filtration rate (eGFR) was calculated using the equation of chronic kidney disease-epidemiology collaboration (CKD-EPI). The grading of AMD was done by a single experienced (more than 5 years) vitreoretinal surgeon as per the International ARM Epidemiological Study Group and it was staged based on grading in the worsened eye. RESULTS: A decline in eGFR was observed as the severity of DR increased (P < 0.001). Baseline characteristics such as age (P < 0.001), duration of diabetes (P < 0.001), gender (P < 0.001), creatinine (P < 0.001), albumin to creatinine ratio (ACR; P < 0.001), albuminuria (P = 0.023), blood urea (P < 0.001), and high-density lipoprotein (HDL; P = 0.003) were found to be statistically significant. The risk for developing DR with CKD was found to be 5 times higher in male patients compared to female patients. Age and high blood urea level, diastolic blood pressure, mild and moderate DR were the risk factors associated with CKD. A decline in eGFR was observed as the severity of ARMD increased (P < 0.001). The risk factors associated with CKD were age, gender, smoking, alcohol consumed, presence of hypertension, duration of diabetes, systolic and diastolic blood pressure, history of diabetes, body mass index (BMI), serum triglycerides, and serum HDL cholesterol. CONCLUSION: Reduced eGFR values were associated with an increase in the severity of DR and ARMD.

A deep learning system for predicting time to progression of diabetic retinopathy.

Diabetic retinopathy (DR) is the leading cause of preventable blindness worldwide. The risk of DR progression is highly variable among different individuals, making it difficult to predict risk and personalize screening intervals. We developed and validated a deep learning system (DeepDR Plus) to predict time to DR progression within 5 years solely from fundus images. First, we used 717,308 fundus images from 179,327 participants with diabetes to pretrain the system. Subsequently, we trained and validated the system with a multiethnic dataset comprising 118,868 images from 29,868 participants with diabetes. For predicting time to DR progression, the system achieved concordance indexes of 0.754-0.846 and integrated Brier scores of 0.153-0.241 for all times up to 5 years. Furthermore, we validated the system in real-world cohorts of participants with diabetes. The integration with clinical workflow could potentially extend the mean screening interval from 12 months to 31.97 months, and the percentage of participants recommended to be screened at 1-5 years was 30.62%, 20.00%, 19.63%, 11.85% and 17.89%, respectively, while delayed detection of progression to vision-threatening DR was 0.18%. Altogether, the DeepDR Plus system could predict individualized risk and time to DR progression over 5 years, potentially allowing personalized screening intervals.

Automatic Identification and Severity Classification of Retinal Biomarkers in SD-OCT Using Dilated Depthwise Separable Convolution ResNet with SVM Classifier.

PURPOSE: Diagnosis of Uveitic Macular Edema (UME) using Spectral Domain OCT (SD-OCT) is a promising method for early detection and monitoring of sight-threatening visual impairment. Viewing multiple B-scans and identifying biomarkers is challenging and time-consuming for clinical practitioners. To overcome these challenges, this paper proposes an image classification hybrid framework for predicting the presence of biomarkers such as intraretinal cysts (IRC), hyperreflective foci (HRF), hard exudates (HE) and neurosensory detachment (NSD) in OCT B-scans along with their severity. METHODS: A dataset of 10880 B-scans from 85 Uveitic patients is collected and graded by two board-certified ophthalmologists for the presence of biomarkers. A novel image classification framework, Dilated Depthwise Separable Convolution ResNet (DDSC-RN) with SVM classifier, is developed to achieve network compression with a larger receptive field that captures both low and high-level features of the biomarkers without loss of classification accuracy. The severity level of each biomarker is predicted from the feature map, extracted by the proposed DDSC-RN network. RESULTS: The proposed hybrid model is evaluated using ground truth labels from the hospital. The deep learning model initially, identified the presence of biomarkers in B-scans. It achieved an overall accuracy of 98.64%, which is comparable to the performance of other state-of-the-art models, such as DRN-C-42 and ResNet-34. The SVM classifier then predicted the severity of each biomarker, achieving an overall accuracy of 89.3%. CONCLUSIONS: A new hybrid model accurately identifies four retinal biomarkers on a tissue map and predicts their severity. The model outperforms other methods for identifying multiple biomarkers in complex OCT B-scans. This helps clinicians to screen multiple B-scans of UME more effectively, leading to better treatment outcomes.

Rationale and protocol paper for the Asia Pacific Network for inherited eye diseases.

PURPOSE: There are major gaps in our knowledge of hereditary ocular conditions in the Asia-Pacific population, which comprises approximately 60% of the world's population. Therefore, a concerted regional effort is urgently needed to close this critical knowledge gap and apply precision medicine technology to improve the quality of lives of these patients in the Asia-Pacific region. DESIGN: Multi-national, multi-center collaborative network. METHODS: The Research Standing Committee of the Asia-Pacific Academy of Ophthalmology and the Asia-Pacific Society of Eye Genetics fostered this research collaboration, which brings together renowned institutions and experts for inherited eye diseases in the Asia-Pacific region. The immediate priority of the network will be inherited retinal diseases (IRDs), where there is a lack of detailed characterization of these conditions and in the number of established registries. RESULTS: The network comprises 55 members from 35 centers, spanning 12 countries and regions, including Australia, China, India, Indonesia, Japan, South Korea, Malaysia, Nepal, Philippines, Singapore, Taiwan, and Thailand. The steering committee comprises ophthalmologists with experience in consortia for eye diseases in the Asia-Pacific region, leading ophthalmologists and vision scientists in the field of IRDs internationally, and ophthalmic geneticists. CONCLUSIONS: The Asia Pacific Inherited Eye Disease (APIED) network aims to (1) improve genotyping capabilities and expertise to increase early and accurate genetic diagnosis of IRDs, (2) harmonise deep phenotyping practices and utilization of ontological terms, and (3) establish high-quality, multi-user, federated disease registries that will facilitate patient care, genetic counseling, and research of IRDs regionally and internationally.

Knowledge, attitude, and practice of diabetes in patients with and without sight-threatening diabetic retinopathy from two secondary eye care centres in India.

BACKGROUND/AIMS: Good knowledge, Attitude, and Practice (KAP) of diabetes influence its control and complications. We examined the KAP of diabetes in patients with sight-threatening diabetic retinopathy (STDR) and non-sight-threatening diabetic retinopathy (NSTDR) attending two different referral hospitals in India. METHODS: 400 consecutive patients (mean age = 58.5 years ± 10.3) with diabetic retinopathy attending retina referral clinics in Chennai (private) and Darjeeling (public) were recruited. A validated questionnaire on diabetic KAP was administered in English or the local language. Data were analysed using an established scalar-scoring method in which a score of 1 was assigned to the correct answer/healthy lifestyle and 0 to an incorrect answer/unhealthy lifestyle/practice. Clinical data included fasting blood sugar, blood pressure, retinopathy, and visual acuity. Retinopathy was graded as STDR/NSTDR from retinal images using Early Treatment of Diabetic Retinopathy Study criteria. RESULTS: Usable data from 383 participants (95.8%) were analysed. Of these, 83 (21.7%) had STDR, and 300 (78.3%) had NSTDR. The NSTDR group reported a significantly lower total KAP score (mean rank = 183.4) compared to the STDR group (mean rank = 233.1), z = -3.0, p < 0.001. A significantly greater percentage in the NSTDR group reported to being unaware that diabetes could affect eyes, did not know about possible treatment for DR, and checked their blood sugar less frequently than once a month. CONCLUSION: Patients who had not developed STDR had poorer KAP about diabetes and diabetes-related eye diseases. This is an important issue to address as the risk of their progressing to STDR is high unless appropriate steps to improve their knowledge/awareness and lifestyle practice are introduced early.

Global warming impact of fluorinated gases in ophthalmic surgeries at a tertiary eye center in India.

PURPOSE: Global warming is one of the greatest health threats of the 21 st century. The ophthalmic sector contributes to the emission of greenhouse gases, thus altering the natural environment. There is currently no data on global emissions of fluorinated gases in ophthalmic surgery. This retrospective study from 2017 to 2021 aims to report the carbon dioxide (CO 2 ) equivalence of sulfur hexafluoride (SF 6 ), hexafluoroethane (C 2 F 6 ), and octafluoropropane (C 3 F 8 ) at a tertiary eye center. METHODS: Data collected from 1842 surgical procedures that used injections of fluorinated gases were analyzed. Environmental impact (global warming potential over 100 years) was calculated by converting milliliters to grams by using modified ideal gas law at standard temperature and pressure for the canisters and then to their CO 2 equivalence. RESULTS: Though 70% of surgeries used C 3 F 8 , the least greenhouse effect causing fluorinated gas, the total carbon emission was 1.4 metric tons. The most common indication was macular hole surgery (36.86%). CONCLUSION: This study paves a step toward analyzing the problem statement, thus awakening us to contemplate options to make ophthalmic surgeries greener.

Late postoperative vitreous cavity hemorrhage after vitrectomy for proliferative diabetic retinopathy-observation versus intervention.

PURPOSE: To analyze the outcome of intervention versus observation for vitreous cavity hemorrhage occurring after a 2-month period of blood-free cavity (late postoperative vitreous cavity hemorrhage-POVCH) in eyes operated by vitrectomy for complications of proliferative diabetic retinopathy (PDR). METHODS: This study was a 10-year retrospective, observational, multi-center study involving eight major vitreoretinal surgical centers across India from January 2010 to December 2019. The primary objective of the study was to assess the visual and clinical outcomes of various management approaches for late POVCH. The key secondary objective was to determine the best management option that prevented recurrence. Patients with follow-up of less than 6 months of POVCH management were excluded. RESULTS: The occurrence of late POVCH was studied in 261 eyes. The median time to occurrence was 7 months (range: 2-87) postvitrectomy/silicone oil removal. The majority (58%) experienced a single, nonrecurring POVCH event. Visual acuity outcome was independent of all management approaches (P = 0.179; mean follow-up 20.7 ± 14.1 months). With watchful observation, spontaneous resolution was noted in 83% (60/72 eyes) of eyes in 81.5 days (interquartile range, 169.75). Silicone oil injection was most effective in preventing recurrence (P < 0.001). CONCLUSION: The current treatment practice of late POVCH management in PDR suggests that watchful observation for at least 3 months could be as efficacious as any surgical intervention.

Is Kidney Function Associated with Age-Related Macular Degeneration?: Findings from the Asian Eye Epidemiology Consortium.

PURPOSE: Chronic kidney disease (CKD) may elevate susceptibility to age-related macular degeneration (AMD) because of shared risk factors, pathogenic mechanisms, and genetic polymorphisms. Given the inconclusive findings in prior studies, we investigated this association using extensive datasets in the Asian Eye Epidemiology Consortium. DESIGN: Cross-sectional study. PARTICIPANTS: Fifty-one thousand two hundred fifty-three participants from 10 distinct population-based Asian studies. METHODS: Age-related macular degeneration was defined using the Wisconsin Age-Related Maculopathy Grading System, the International Age-Related Maculopathy Epidemiological Study Group Classification, or the Beckman Clinical Classification. Chronic kidney disease was defined as estimated glomerular filtration rate (eGFR) of less than 60 ml/min per 1.73 m2. A pooled analysis using individual-level participant data was performed to examine the associations between CKD and eGFR with AMD (early and late), adjusting for age, sex, hypertension, diabetes, body mass index, smoking status, total cholesterol, and study groups. MAIN OUTCOME MEASURES: Odds ratio (OR) of early and late AMD. RESULTS: Among 51 253 participants (mean age, 54.1 ± 14.5 years), 5079 had CKD (9.9%). The prevalence of early AMD was 9.0%, and that of late AMD was 0.71%. After adjusting for confounders, individuals with CKD were associated with higher odds of late AMD (OR, 1.46; 95% confidence interval [CI], 1.11-1.93; P = 0.008). Similarly, poorer kidney function (per 10-unit eGFR decrease) was associated with late AMD (OR, 1.12; 95% CI, 1.05-1.19; P = 0.001). Nevertheless, CKD and eGFR were not associated significantly with early AMD (all P ≥ 0.149). CONCLUSIONS: Pooled analysis from 10 distinct Asian population-based studies revealed that CKD and compromised kidney function are associated significantly with late AMD. This finding further underscores the importance of ocular examinations in patients with CKD. FINANCIAL DISCLOSURE(S): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Natural course of non-center-involving diabetic macular edema progression in patients under initial observation.

PURPOSE: We aim to report the natural course of non-center involving diabetic macular edema (NCIDME) progression to center involving diabetic macular edema (CIDME) and associated risk factors. METHODS: This is a multicenter retrospective comparative study. Data was collected from electronic medical records from 8 centers in India covering. We included patients with type 2 diabetes above 18 years of age with treatment-naïve NCIDME on OCT and best-corrected visual acuity at baseline of 6/12 or better who were under observation for NCIDME and had 2 years follow-up data. RESULTS: Out of 72 patients with NCIDME, 26.38% patients progressed to CI DME by 2 years, and the visit wise proportion was 11.11% at 6 months, 7% at 1st year and 8.3% at 2 years. The change in CST was statistically significant at 2 years in patients who developed CIDME, the mean difference was 137.73 ± 48.56 microns p = 0.045. Duration of diabetes mellitus > 10 years was the only risk factor for conversion to CIDME. CONCLUSION: A quarter of eyes with NCIDME developed CIDME and 15% progressed from NPDR to PDR by 2 years, highlighting the disease burden in these patients with NCIDME.

Population-Based Artificial Intelligence Assessment of Relationship Between the Risk Factors for Diabetic Retinopathy in Indian Population.

PURPOSE: Risk factors (RFs), like 'body mass index (BMI),' 'age,' and 'gender' correlate with Diabetic Retinopathy (DR) diagnosis and have been widely studied. This study examines how these three secondary RFs independently affect the predictive capacity of primary RFs. METHODS: The dataset consisted of four population-based studies on the prevalence of DR and associated RFs in India between 2001 and 2010. An Autoencoder was employed to categorize RFs as primary or secondary. This study evaluated six primary RFs coupled independently with each secondary RF on five machine-learning models. RESULTS: The secondary RF 'gender' gave a maximum increase in Area under the curve (AUC) score to predict DR when combined separately with 'insulin treatment,' 'fasting plasma glucose,' 'hypertension history,' and 'glycosylated hemoglobin' with a maximum increase in AUC for the Naive Bayes model from 0.573 to 0.646, for the Support Vector Machines (SVM) model from 0.644 to 0.691, for the SVM model from 0.487 to 0.607, and for the Decision Tree model from 0.8 to 0.848, respectively. The secondary RFs 'age' and 'BMI' gave a maximum increase in AUC score to predict DR when combined separately with 'diabetes mellitus duration' and 'systolic blood pressure,' with a maximum increase in AUC for the SVM model from 0.389 to 0.621, and for the Decision Tree model from 0.617 to 0.713, respectively. CONCLUSION: The risk factor 'gender' was the best secondary RF in predicting DR compared to 'age' and 'BMI,' increasing the predictive power of four primary RFs.