Prevalence Of Blindness Research Articles

Prevalence and Analysis of Risk Factors for Cataracts in Jember Regency, Indonesia

Introduction: Cataracts are the leading cause of preventable blindness. This study aims to determine the prevalence of cataracts and analyze the risk factors for cataracts in Jember Regency.
 Methods: The research design is observational research with a cross-sectional approach. The study carried out eye examinations on 1000 adults (≥50 years) who were randomly selected in Jember Regency. Risk factors analyzed included age, gender, education, occupation, smoking, and history of diabetes mellitus and hypertension.
 Results: The prevalence of cataracts in Jember Regency is 25.3%. Risk factors associated with the incidence of cataracts are age (OR=1.35; 95%CI: 1.02-1.98), female gender (OR=1.54; 95%CI: 1.12-2.13), low education (OR=1.83; 95%CI: 1.22-2.73), outdoor work (OR=3.72; 95%CI: 1.14-5.58), smoking (OR=1.42; 95%CI: 1.01-2.00), and history of diabetes mellitus (OR=2.15; 95%CI: 1.43-3.24).
 Conclusion: The prevalence of cataracts at ages ≥ 50 years in Jember Regency is quite high. Age, female gender, low education, outdoor work, smoking, and a history of diabetes mellitus are risk factors for cataracts.

Adaptive Tensor-Based Feature Extraction for Pupil Segmentation in Cataract Surgery.

Cataract surgery remains the only definitive treatment for visually significant cataracts, which are a major cause of preventable blindness worldwide. Successful performance of cataract surgery relies on stable dilation of the pupil. Automated pupil segmentation from surgical videos can assist surgeons in detecting risk factors for pupillary instability prior to the development of surgical complications. However, surgical illumination variations, surgical instrument obstruction, and lens material hydration during cataract surgery can limit pupil segmentation accuracy. To address these problems, we propose a novel method named adaptive wavelet tensor feature extraction (AWTFE). AWTFE is designed to enhance the accuracy of deep learning-powered pupil recognition systems. First, we represent the correlations among spatial information, color channels, and wavelet subbands by constructing a third-order tensor. We then utilize higher-order singular value decomposition to eliminate redundant information adaptively and estimate pupil feature information. We evaluated the proposed method by conducting experiments with state-of-the-art deep learning segmentation models on our BigCat dataset consisting of 5,700 annotated intraoperative images from 190 cataract surgeries and a public CaDIS dataset. The experimental results reveal that the AWTFE method effectively identifies features relevant to the pupil region and improved the overall performance of segmentation models by up to 2.26% (BigCat) and 3.31% (CaDIS). Incorporation of the AWTFE method led to statistically significant improvements in segmentation performance (P < 1.29 × 10-10 for each model) and yielded the highest-performing model overall (Dice coefficients of 94.74% and 96.71% for the BigCat and CaDIS datasets, respectively). In performance comparisons, the AWTFE consistently outperformed other feature extraction methods in enhancing model performance. In addition, the proposed AWTFE method significantly improved pupil recognition performance by up to 2.87% in particularly challenging phases of cataract surgery.

Intrabulbar, Intraorbital and Intracranial Perforating Eye Injury with Foreign Body: A Case Report

Ocular trauma is a significant cause of preventable blindness and visual impairment worldwide. Eye globe perforation can happen due to work with sharp tools or different particles that are spread during work with metals, wood, and other solid substances.We present the case of a 14-year-old male patient admitted as an urgent case at the Ophthalmology Department in 2014 due to a perforating eye injury with a foreign body – a 7 cm rusty metallic nail in the right eye. The X-ray of the orbit revealed that the foreign body had penetrated the eyelid, the eye eyeball, and through the orbit and its posterior wall, penetrated the skull and 2 cm in the brain. Under general anesthesia, we performed the anterior chamber lavage, excision of the prolapsed iris, and pupilloplasty. The anterior chamber was reconstructed using a saline solution (0.9% NaCl) and air. The patient was treated conservatively with antibiotics and steroids for 10 days; there were no signs of wound filtration, hypotonia, or endophthalmitis. Due to the limited resources for the posterior segment surgery, the patient was referred to another center for pars plana vitrectomy (PPV) after 10 days of hospitalization in the Department of Ophthalmology at the University Clinical Center of Kosovo. After PPV with silicon oil and cataract surgery, the patient could see the light and its projections (BCVA = L+P+). We followed up on the patient until September 2022, there were no signs of bulbus atrophy, and the visual acuity remained the same, BCVA = L+P+. The correct diagnosis and treatment at the right time play a leading role in achieving one of the main goals of surgical treatment of perforating eye injuries, which is the preservation of the anatomical structure and the physiology of the eye.

STUDY OF CLINICAL PROFILE AND RISK FACTORS OF INFECTED CORNEAL ULCERS AT RURAL TERTIARY CARE HOSPITAL

Introduction: A corneal ulcer is a discontinuation in normal epithelial surface of cornea associated with necrosis of the surrounding corneal tissue. It is a major worldwide cause of preventable corneal blindness that is mostly under-reported but can be responsible every year for 1.5–2.0 million new cases of monocular blindness. Detailed studies of severe sight-threatening infectious keratitis are therefore important as they provide valuable information on the detection of etiology, predisposing factors, and visual outcomes to form the development of management strategies and protocols. Aims and Objectives: To study the clinical profile and known risk factors of infected corneal ulcers at rural tertiary care hospital. Materials and Methods: An Observational, Descriptive Cross-Sectional Hospital-based study was conducted after Institutional Ethical Committee (IEC) at the Department of Ophthalmology, DVPRMC, Loni. A total of 70 patients with infected corneal ulcers were screened and evaluated from June 2022 to May 2023 for a duration of 1 year. We studied the infected corneal ulcer patients above 18 years old attending to our hospital OPD. Results: 57% of patients were male and 43% were female. 66% of patients gave a history of trauma. The most common clinically diagnosed ulcer was fungal, representing 53% of all ulcers, followed by bacterial (27%) and viral (13%). There were also 2 cases each of acanthamoeba (3%) and pythium (3%) ulcers. 62.8% of cases were above 50 years old. In our study 73% of suspected fungal corneal ulcers were KOH smear-positive and 70% of suspected bacterial corneal ulcers were gram-positive. All cases were advised medical management. Out of those 43% were also advised therapeutic penetrating keratoplasty. Conclusion: Corneal ulcers are commonly seen in adult male farmers and laborers with ocular trauma in rural areas and fungal ulcer is the most common type of ulcer. Late presentation with corneal perforation requires therapeutic penetrating keratoplasty.

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

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. 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. 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. 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. Global Challenge Research Fund of United Kingdom Research and Innovation through the Medical Research Council.

Clinical vitamin A deficiency among preschool aged children in southwest Ethiopia.

The clinical manifestations of vitamin A deficiency (VAD) involve night blindness, bitot's spots, corneal xerosis, and corneal scars. It is the most important cause of preventable childhood blindness among children and causes morbidity and mortality. Even though Ethiopia implemented high-potency vitamin A supplements, the occurrence of VAD remains significant. This study was to identify determinants of clinical VAD among preschool-aged children (PSC) in southwest Ethiopia. A community-based survey was conducted among 411 randomly selected PSCs. A pretested and structured questionnaire coupled with clinical observation for signs of vitamin A deficiency by a trained ophthalmologist was used to collect the data. An anthropometric measurement of height was taken and analyzed using WHO Anthro to calculate Z-scores for each index. The public health significance of VAD was declared after comparison with international references. A bi-variable and multi-variable logistic analysis was done. We reported the adjusted odds ratio (AOR), 95% confidence interval, and p-value. A total of 411 children were screened for clinical VAD, and the overall prevalence was 2.2% (95% CI: 1.5-2.5). Of which, night blindness affects 1.2%, bitot's spots affects 0.7%, and corneal xerosis affects 0.2%, indicating a major public health problem compared to the international reference. The odds of clinical VAD were 81% lower among children who received vitamin A supplementation (VAS; AOR = 0.19, 95% CI: 0.04-0.92). On the other hand, PSC of mothers who had attended ANC visits were 89% less likely to develop clinical VAD (AOR = 0.11, 95% CI: 0.02-0.53). In addition, the study revealed that the odds of developing clinical VAD are 82% lower among PSC aged 36 to 47 months (AOR = 0.18; 95% CI: 0.03-0.97). The prevalence of clinical VAD among PSC is a public health problem and is associated with ANC visits, VAS status, and the age of the child, which could be used to target interventions to further reduce existing VAD. Further studies using reliable dietary intake and biomarker data could further depict the burden of subclinical VAD.

AI Can Improve the Economics of Blindness Prevention in Canada.

Diabetic retinopathy is a leading cause of vision loss in Canada and creates significant economic and social burden on patients. Diabetic retinopathy is largely a preventable complication of diabetes mellitus. Yet, hundreds of thousands of Canadians continue to be at risk and thousands go on to develop vision loss and disability. Blindness has a significant impact on the Canadian economy, on families and the quality of life of affected individuals. This paper provides an economic analysis on two potential interventions for preventing blindness and concludes that use of AI to identify high-risk individuals could significantly decrease the costs of identifying, recalling, and screening patients at risk of vision loss, while achieving similar results as a full-fledged screening and recall program. We propose that minimal data interoperability between optometrists and family physicians combined with artificial intelligence to identify and screen those at highest risk of vision loss can lower the costs and increase the feasibility of screening and treating large numbers of patients at risk of going blind in Canada.

Prevalence and causes of blindness and distance visual impairment in Chinese adult population in 2022 during the COVID-19 pandemic: a cross-sectional study

This cross-sectional study aims to investigate the prevalence and causes of visual impairment (VI) and blindness in Jiangsu Province, China in 2022 during the COVID-19 pandemic. Participants (n = 13,208, aged 18–93) underwent comprehensive ocular examinations. The prevalence and causes of binocular VI (presenting visual acuity [VA] ≥ 20/400 and < 20/63 in the better eye) and blindness (presenting VA < 20/400 in the better eye) were assessed according to the World Health Organization (WHO) criteria. The estimation of refractive error prevalence was conducted using the following classification: myopia ≤ − 0.50 diopters (D), high myopia ≤ − 6.00 D, hyperopia ≥ 0.50 D, and anisometropia ≥ 1.00 D. The overall prevalence of binocular VI and blindness was 21.04% (95% confidence interval [CI] 20.35–21.74%) and 0.47% (95% CI 0.37–0.60%). The highest prevalence of binocular VI was in the population aged 18–24 years old (46.29%, [95% CI 44.30–48.28%]), those with education at university and above (43.47%, [95% CI 41.93–45.02%]), students (54.96%, [95% CI 52.73–57.17%]). Uncorrected refractive error (URE) was the leading cause of presenting binocular VI (93.40%) and blindness (50.79%). The prevalence of myopia was 54.75% (95% CI 53.90–55.60%). Actions are needed to control URE and myopia within the adult Chinese population, with a particular emphasis on the younger, well-educated demographic.

Visual-functional impact of people affected by severe ocular trauma during social protests in Chile in 2019.

To determine the impact on the functionality associated with visual loss (VFIP) in people with severe ocular trauma (SOT) caused by kinetic impact projectiles used in police crowd control through a prioritization tool in people admitted to a rehabilitation program in Santiago de Chile from December 02, 2019, to November 13, 2020. Across-sectional descriptive study of SOT victims (N = 85), average age 31.4 ± 11.9. The data were recorded through a new 9-item screening instrument for assessment and prioritization of rehabilitation created for this emergency scenario. The impact of the use of kinetic weapons resulted in monocular blindness in the majority of those affected (n = 68; 80.0%). The highest VFIP observed was among young men from lower social strata. There were extreme difficulties in the performance of productive tasks (occupational and/or educational) (n = 42; 49.4%) and the pursuit of hobbies and pastimes (n = 23; 27.1%), as well as a high difficulty in adapting to changes in brightness (n = 29; 34.1%) and handling objects accurately (n = 22; 25.9%). The use of kinetic weapons for crowd control resulted in high and extreme VFIP and, in most cases, monocular blindness, causing major difficulties in work, study, and development of hobbies and pastimes in the affected population, highlighting the urgent need for effective rehabilitative care, which requires special attention in order to generate an adequate rehabilitation program. The use of kinetic weapons for crowd control contravenes international goals, policies, and plans set by the WHO and the International Agency for the Prevention of Blindness on strategies to prevent avoidable blindness worldwide until 2020. It is essential to ban the use of these weapons in Chile and worldwide, as well as to revise police protocols for crowd control.

Diabetic retinopathy screening using MII Ret Cam assisted smartphone-based fundus imaging

BackgroundDiabetes Mellitus is a tremendous health implication and is proposed to be the seventh leading cause of death in 2030 by WHO. Diabetic retinopathy is one of the top complications of diabetes leading to preventable blindness. This investigation highlights the importance of timely screening and counseling using MII Ret cCam-assisted smartphone-based fundus imaging. Our study is a boon for bed-ridden and seriously ill patients who could not be evaluated on a fundus camera. MethodsThis is an observational prospective study conducted at the Ophthalmology unit, wards, and intensive care unit (ICU) of a single tertiary teaching hospital between 1 May to 31 November 2022. A total of 268 subjects with diabetes were included. The fundus of all the diabetic patients during the study period were examined by a single-trained ophthalmologist. Those diagnosed with diabetic retinopathy were taken for acquisition of fundus picture with MII Ret Cam. Images were captured using Apple iPhone 5s and 20D mounted in MII Ret Cam device. ResultsOut of 268 subjects (536 eyes) screened during the study period,86 patients (154 eyes) were found to have DR. Maleto Female ratio was 1.4:1. The mean age was 56.37 ± 15.26 years and the mean duration of diabetes was 10.60 ± 6.97 years. Grading of DR revealed proliferative diabetic retinopathy (PDR) to be the topmost (n=84 eyes, 54.5%), followed by mild non-proliferative diabetic retinopathy (NPDR) in 26 eyes (16%) and moderate NPDR in 24 eyes (15%) while severe NPDR was seen in 10 eyes (6.5%) and very severe NPDR was found in 8 eyes (5.2%) and diabetic papillopathy in 2 eyes. Grading of vitreous hemorrhage revealed Grade 1 in one eye (1.8%); Grade 2 in 19 eyes (34.54%); Grade 3 in 33 eyes (60%) and Grade 4 in 2 eyes (3.63%). Grading of macular edema according to the distribution of hard exudates as Grade 1(No Clinically significant macular edema) in 33 eyes (34.37%) and Grade 2 (Clinically significant macular edema) in 63 eyes (65.62%). The duration of diabetes had a direct association with the occurrence of DR, 13patients (15.1%) had a duration of diabetes less than five years; 31patients(36%) had a duration of diabetes between 6 years to 10 years; 28 patients (32.6%) had a duration between 11 years to 20 years. 14 patients (16.3%) had a duration of more than twenty years. The Mean duration of diabetes in Group I was 11.40+/- 7.09 years and was 9.10+/- 6.48 in Group II. The mean HbA1c in Group I is 7.44+/- 1.24 and 6.54 +/- 1.09 in Group II. The mean fasting blood sugar in Group I was 130.87 +/- 29.57 and 106.62+/- 29.85 in Group II. The mean of random blood sugar was 202.15 +/- 60.84 in Group I and 155.13 +/- 55.95 in Group II. Results are suggestive of the association of DR occurrence with fasting, random blood sugar, duration of diabetes, and HbA1c. ConclusionsDiabetic Retinopathy Screening using MII Ret Cam assisted Smartphone-based fundus imaging may be a useful device to screen for referable and vision-threatening diabetic retinopathy. MII Ret Cam is portable equipment and is easily accessible to counsel patients in resource-limited countries.

HUMAN RESOURCES DEVELOPMENT IN CHILDREN EYE HEALTH SERVICES IN SOUTH SULAWESI

Introduction: Children eye health are one of the most common problems in ophthalmology that are getting attention globally and nationally especially in South Sulawesi. To optimize its services quality and quantity of human resources are required. This study aims to report the human resources development in children eye health services in South Sulawesi.&#x0D; Methods: Surveys were carried out in several districts to assess the availability of human resources in children eye health services. Creating collaborations with several institutes such as Faculty of Medicine, Hasanuddin University and related professional organizations. Conducting several trainings in provinces, districts, subdistricts, village, and urban village.&#x0D; Results: Preparation and dissemination of materials and media on prevention of blindness in children, improvement of human resources in the form of District Trainer training in 24 districts that recruited 98 people who were ready to become trainers. For 2 years conducting tiered training at 24 districts, they produced human resources of 1,395 officers at the Puskesmas, 11,145 posyandu cadres, and 3,826 teachers. The results of this built system revealed that 3,248 paediatric patients were screened with vision problems, 3,528 toddlers in Integrated Health Centre were screened and referred to Health Centre as many as 426 toddlers, and at the School Health Unit it was recorded that 173,778 children were screened and there were 28,845 (17%) children who had visual disturbances.&#x0D; Conclusion: Development of human resources in children eye health in Indonesia was not only the responsibility of the government and the health sector but also need cross-sectoral roles.

CHARACTERISTICS AND MANAGEMENT OF PEDIATRIC CATARACT AT UNIVERSITAS TANJUNGPURA HOSPITAL 2019-2021

Abstract&#x0D; Introduction &amp; Objectives : One of the causes of blindness in children that can be treated is cataracts. The prevalence of childhood cataracts in Asia is the highest in the world at 7.43 per 10,000 children. There were 4,270 children in Indonesia who experienced blindness due to cataracts in 2017. Data on childhood cataracts in West Kalimantan is still limited. However, the prevalence of blindness in West Kalimantan is the highest in Indonesia at 1.6%. Characteristics of pediatric cataract patients need to be known to assist in diagnosis and treatment so that the risk of blindness in children can be prevented. This study is to describe cataracts in children at Universitas Tanjungpura Hospital in 2019-2021.&#x0D; Methods : This study used a cross-sectional descriptive design. Data collection was obtained from the medical records of pediatric cataract patients at the Universitas Tanjungpura Hospital during 2019-2021.&#x0D; Results : The total number of pediatric cataract patients obtained from medical records during 2019-2021 was 27 patients, consisting of 8 girls and 19 boys. Congenital cataracts were the most common cataracts (59%) and the most diagnosed age was in the 0-1 year group. Bilateral cataracts (48%) were almost as numerous as unilateral cataracts (52%). The most common visual acuity before and after surgery was fixating and following object (60%).&#x0D; Conclusion : Cataracts in children at Universitas Tanjungpura Hospital in 2019-2021 were dominated by congenital cataracts, diagnosis age was at 0-1 years, bilateral and unilateral, male gender, and visual acuity before and after surgery was fixating and following object.

SCREENING ON CATARACT APPLICATION (SERIOC)

Introduction &amp; Objectives : West Nusa Tenggara is a province that has the second highest prevalence of blindness at the national level according to the results of the 2014 Rapid Assessment of Avoidable Blindness (RAAB) survey. During the covid-19 period the offline cataract screening is not permitted, as a result it’s difficult to reach underprivileged and isolated areas, also people with disabilities. In 2021 West Nusa Tenggara Eye Hospital launched a smartphone-based eye health examination application Screening On Cataract namely SERIOC, while still paying attention to service standards clinically and in management. SERIOC can be used by public health as the nearest public health facility.&#x0D; Methods : The waterfall method is used in the development of this application, The waterfall methodology is a project management approach that emphasizes a linear progression from beginning to end of a project. This methodology, is front-loaded to rely on careful planning, detailed documentation, and consecutive execution.&#x0D; Results : SERIOC has successfully screened 2,713 patients from 2021 with 2117 patients diagnosed cataract and 593 patients diagnosed non-cataract whose data is centralized and directly connected to an ophthalmologist at the West Nusa Tenggara Eye Hospital. Patients diagnosed with cataracts will be referred to the hospital for further action.&#x0D; Conclusion : Based on the information above, it can be concluded that SERIOC application in eye health screening is very effective and efficient method to avoid blindness on West Nusa Tenggara.

RELATIONSHIP OF GESTATION AGE AND WEIGHT IN PREMATURE BIRTH WITH RETINOPATHY OF PREMATURITY IN A TERTIER HOSPITAL

Abstract&#x0D; Introduction &amp; Objectives : Retinopathy of Prematurity (ROP) is the leading cause of preventable blindness in these children and significantly impacts vision. It is estimated that from about 15 million infants born prematurely worldwide, around 53,000 infants are found to have vision-threatening ROP, and 20,000 infants experience severe visual impairment. This study is to determine the relationship between gestational age and body weight in preterm birth with retinopathy of prematurity.&#x0D; Methods : Medical records data with a diagnosis of retinopathy of prematurity were found in 385 infants treated at Dr. Soetomo Hospital from January 2016-December 2020. From 385 premature infants, 45 premature infants were found with ROP. The relevant data is then entered into the recording sheet and Microsoft Excel software and processed using SPSS 22.0 software.&#x0D; Results : Premature infants with ROP who were found 385 infants with 45 infants were found with ROP. Premature infants with ROP in the gestational age group &gt;32 weeks were 10 infants (22.2%). Of 45 premature infants, 23 premature infants with birth weights less than 1500 grams. AP ROP there is also 1 infant in the weight category&#x0D; Conclusion : There is a relationship between gestational age at premature birth and retinopathy of prematurity. Meanwhile, birth weight was not associated with retinopathy of prematurity. In infants with a gestational age of more than 32 weeks, it is still necessary for ROP because there is still a possibility of ROP.

Validation of WINROP algorithm as screening tool of retinopathy of prematurity among Egyptian preterm neonates

BackgroundRetinopathy of prematurity (ROP) is a leading cause of preventable childhood blindness worldwide. Proper screening for ROP can prevent loss of vision. WINROP (weight, insulin-like growth factor 1, neonatal, retinopathy of prematurity) is an online surveillance system based on gestational age, birth weight and weekly weight gain that can predict infants at risk of sight-threatening retinopathy of prematurity.AimsTo evaluate the diagnostic accuracy of WINROP algorithm in detecting sight-threatening ROP in Egyptian preterm neonates.MethodsBirth weight (BW), gestational age (GA) and weekly weight measurement of 365 preterm infants were prospectively entered into WINROP algorithm. Based on these inputs, the algorithm would output and a screening was performed as is standard. Sensitivity, specificity, and predictive values were calculated by comparing WINROP outcomes with ROP screening outcomes.ResultsOf the infants included in the study the mean GA was ±31.24 and mean BW was ±1508.78. A high risk WINROP alarm was triggered in 62 infants of whom 16 infants develop type 1 or type 2 ROP. These infants had associated comorbidities including sepsis, Intraventricular hemorrhage (IVH), Necrotizing enterocolitis (NEC), history of transfusion of packed red blood cells (RBCS) and history of platelet transfusion. A low risk WINROP alarm was triggered in 303 infants of whom 15 infants developed type 1 or type 2ROP. WINROP showed a sensitivity of 51.6%, a specificity of 86.2%, a positive predictive value (PPV) of 52.8% and a negative predictive value (NPV) of 95% for detection of type 1 or type 2 ROP.ConclusionWINROP has low sensitivity and high specificity for detection of ROP. It may help in ROP prediction but can’t be used alone. Modification of WINROP algorithm taking into account other risk factors may improve sensitivity and reduce number for ROP examination.

An Extensive-Form Game Paradigm for Visual Field Testing via Deep Reinforcement Learning.

Glaucoma is the leading cause of irreversible but preventable blindness worldwide, and visual field testing is an important tool for its diagnosis and monitoring. Testing using standard visual field thresholding procedures is time-consuming, and prolonged test duration leads to patient fatigue and decreased test reliability. Different visual field testing algorithms have been developed to shorten testing time while maintaining accuracy. However, the performance of these algorithms depends heavily on prior knowledge and manually crafted rules that determine the intensity of each light stimulus as well as the termination criteria, which is suboptimal. We leverage deep reinforcement learning to find improved decision strategies for visual field testing. In our proposed algorithms, multiple intelligent agents are employed to interact with the patient in an extensive-form game fashion, with each agent controlling the test on one of the testing locations in the patient's visual field. Through training, each agent learns an optimized policy that determines the intensities of light stimuli and the termination criteria, which minimizes the error in sensitivity estimation and test duration at the same time. In simulation experiments, we compare the performance of our algorithms against baseline visual field testing algorithms and show that our algorithms achieve a better trade-off between estimation accuracy and test duration. By retaining testing accuracy with reduced test duration, our algorithms improve test reliability, clinic efficiency, and patient satisfaction, and translationally affect clinical outcomes.

Application of the Support Vector Machine (SVM) Algorithm for the Diagnosis of Diabetic Retinopathy

Diabetic Retinopathy (DR) is a disease whose main cause is complications of diabetes mellitus. High levels of sugar in the blood (glucose) are caused by the pancreas' inability to produce insulin. Prevention of diabetic retinopathy and blindness by carrying out examinations at an early stage and doing them regularly. Currently, doctors still carry out examinations manually so they are prone to errors in examinations. This research aims to build an application to diagnose Diabetic Retinopathy in order to facilitate the work of the medical team and doctors at the eye clinic. In the application creation process, MATLAB is used, while feature extraction uses GLCM and for classification, SVM is used. The results of the research are that doctors and medical teams are helped in carrying out manual patient diagnoses and reduce the occurrence of human error.

Automatic Detection and Classification of Hypertensive Retinopathy with Improved Convolution Neural Network and Improved SVM.

Hypertensive retinopathy (HR) results from the microvascular retinal changes triggered by hypertension, which is the most common leading cause of preventable blindness worldwide. Therefore, it is necessary to develop an automated system for HR detection and evaluation using retinal images. We aimed to propose an automated approach to identify and categorize the various degrees of HR severity. A new network called the spatial convolution module (SCM) combines cross-channel and spatial information, and the convolution operations extract helpful features. The present model is evaluated using publicly accessible datasets ODIR, INSPIREVR, and VICAVR. We applied the augmentation to artificially increase the dataset of 1200 fundus images. The different HR severity levels of normal, mild, moderate, severe, and malignant are finally classified with the reduced time when compared to the existing models because in the proposed model, convolutional layers run only once on the input fundus images, which leads to a speedup and reduces the processing time in detecting the abnormalities in the vascular structure. According to the findings, the improved SVM had the highest detection and classification accuracy rate in the vessel classification with an accuracy of 98.99% and completed the task in 160.4 s. The ten-fold classification achieved the highest accuracy of 98.99%, i.e., 0.27 higher than the five-fold classification accuracy and the improved KNN classifier achieved an accuracy of 98.72%. When computation efficiency is a priority, the proposed model's ability to quickly recognize different HR severity levels is significant.

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.

Associations of antidiabetic drugs with diabetic retinopathy in people with type 2 diabetes: an umbrella review and meta-analysis.

Diabetic retinopathy (DR) is the most frequent complication of type 2 diabetes and remains the leading cause of preventable blindness. Current clinical decisions regarding the administration of antidiabetic drugs do not sufficiently incorporate the risk of DR due to the inconclusive evidence from preceding meta-analyses. This umbrella review aimed to systematically evaluate the effects of antidiabetic drugs on DR in people with type 2 diabetes. A systematic literature search was undertaken in Medline, Embase, and the Cochrane Library (from inception till 17th May 2022) without language restrictions to identify systematic reviews and meta-analyses of randomized controlled trials or longitudinal studies that examined the association between antidiabetic drugs and DR in people with type 2 diabetes. Two authors independently extracted data and assessed the quality of included studies using the AMSTAR-2 (A MeaSurement Tool to Assess Systematic Reviews) checklist, and evidence assessment was performed using the GRADE (Grading of recommendations, Assessment, Development and Evaluation). Random-effects models were applied to calculate relative risk (RR) or odds ratios (OR) with 95% confidence intervals (CI). This study was registered with PROSPERO (CRD42022332052). With trial evidence from 11 systematic reviews and meta-analyses, we found that the use of glucagon-like peptide-1 receptor agonists (GLP-1 RA), sodium-glucose cotransporter-2 inhibitors (SGLT-2i), or dipeptidyl peptidase-4 inhibitors (DPP-4i) was not statistically associated with the risk of DR, compared to either placebo (RR: GLP-1 RA, 0.98, 0.89-1.08; SGLT-2i, 1.00, 95% CI 0.79-1.27; DPP-4i, 1.17, 0.99-1.39) or other antidiabetic drugs. Compared to other antidiabetic drugs, meglitinides (0.34, 0.01-8.25), SGLT-2i (0.73, 0.10-5.16), thiazolidinediones (0.92, 0.67-1.26), metformin (1.15, 0.81-1.63), sulphonylureas (1.24, 0.93-1.65), and acarbose (4.21, 0.44-40.43) were not statistically associated with the risk of DR. With evidence from longitudinal studies only, insulin was found to have a higher risk of DR than other antidiabetic drugs (OR: 2.47, 95% CI: 2.04-2.99). Our results indicate that antidiabetic drugs are generally safe to prescribe regarding the risk of DR among people with type 2 diabetes. Further robust and large-scale trials investigating the effects of insulin, meglitinides, and acarbose on DR are warranted. https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=332052, identifier CRD42022332052.