Actual Visual Acuity Research Articles

Prediction of postoperative visual acuity restoration in macula off rhegmatogenous retinal detachment using artificial intelligence

PurposeTo assess feasibility of automatic segmentation of OCT biomarkers of visual acuity (VA) and the possibility of prediction of postoperative VA after successful reattachment in macula off rhegmatogenous retinal detachment (RRD) eyes using artificial intelligence (AI). Designretrospective case control study MethodsPatients operated of pars plana vitrectomy (PPV) for macula-off non-traumatic RRD with available good quality OCT acquisitions were included. Ellipsoid zone(EZ) foveal damage and reflectivity, external limiting membrane(ELM) foveal damage, foveal flattening, outer nuclear layer(ONL) thickness and the presence of cysts and hyperreflective foci(HRFs) was assessed on preoperative OCT B scan images by both a trained segmenter and human graders. Different machine learning(ML)models were tested for detection of cases with VA>0.4 logMar at 6 months from surgery.Segmentation performance of the model was compared with ground truth segmentation provided by human graders. Postoperative VA prediction based on the segmented OCT biomarkers, preoperative VA and age was compared with actual postoperative VA to assess accuracy of the model. ResultsA total of 58 eyes of 58 patients were included. A significant difference in preoperative VA, foveal flattening, foveal EZ and ELM damage, EZ reflectivity and presence of HRF in the ONL was detected between groups(all p < 0.001).The segmenter showed good agreement with human assessment in both qualitative and quantitative variables. The Optimizable Naïve Bayes model was the best performing ML model and showed an accuracy of 86.2 % in detection of cases with postoperative VA>0.4 logMar. ConclusionsThe results confirm the prognostic relevance of EZ and ELM integrity and reflectivity, foveal flattening, ONL cysts and ONL HRF in macula off RRD, and, for the first time in literature, reports feasibility of the segmentation of these factors in preoperative OCT B scan images. We also report good classification performances of Naïve Bayes models based on OCT biomarkers, preoperative VA and age in distinguishing patients that should expect a postoperative VA>0.4 logMar at 6 months from surgery.

Predicting Visual Acuity Responses to Anti-VEGF Treatment in the Comparison of Age-related Macular Degeneration Treatments Trials Using Machine Learning

To evaluate multiple machine learning (ML) models for predicting 2-year visual acuity (VA) responses to anti-vascular endothelial growth factor (anti-VEGF) treatment in the Comparison of Age-related Macular Degeneration (AMD) Treatments Trials (CATT) for patients with neovascular AMD (nAMD). Secondary analysis of public data from a randomized clinical trial. A total of 1029 CATT participants who completed 2 years of follow-up with untreated active nAMD and baseline VA between 20/25 and 20/320 in the study eye. Five ML models (support vector machine, random forest, extreme gradient boosting, multilayer perceptron neural network, and lasso) were applied to clinical and image data from baseline and weeks 4, 8, and 12 for predicting 4 VA outcomes (≥ 15-letter VA gain, ≥ 15-letter VA loss, VA change from baseline, and actual VA) at 2 years. The CATT data from 1029 participants were randomly split for training (n= 717), from which the models were trained using 10-fold cross-validation, and for final validation on a test data set (n= 312). Performances of ML models were assessed by R2 and mean absolute error (MAE) for predicting VA change from baseline and actual VA at 2 years, by the area under the receiver operating characteristic curve (AUC) for predicting ≥ 15-letter VA gain and loss from baseline. Using training data up to week 12, the ML models from cross-validation achieved mean R2 of 0.24 to 0.29 (MAE= 9.1-9.8 letters) for predicting VA change and 0.37 to 0.41 (MAE= 9.3-10.2 letters) for predicting actual VA at 2 years. The mean AUCs for predicting ≥ 15-letter VA gain and loss at 2 years was 0.84 to 0.85 and 0.58 to 0.73, respectively. In final validation on the test data set up to week 12, the models had an R2 of 0.33 to 0.38 (MAE= 8.9-9.9 letters) for predicting VA change, an R2 of 0.37 to 0.45 (MAE= 8.8-10.2 letters) for predicting actual VA at 2 years, and AUCs of 0.85 to 0.87 and 0.67 to 0.79 for predicting ≥ 15-letter VA gain and loss, respectively. Machine learning models have the potential to predict 2-year VA response to anti-VEGF treatment using clinical and imaging features from the loading dose phase, which can aid in decision-making around treatment protocols for patients with nAMD. The author(s) have no proprietary or commercial interest in any materials discussed in this article.

Visual Acuity Prediction Based on Different Refraction Types For Patients With Down Syndrome.

The purpose of this study was to determine if control observers can be used as surrogates to predict visual acuity (VA) of patients with Down syndrome (DS). Thirty adults with DS were enrolled in a clinical trial testing three refraction types: clinical refraction and two using wavefront aberration measures to optimize the metrics pupil fraction tessellated (PFSt) and visual Strehl ratio (VSX). Monocular VA was obtained through habitual refractions and each experimental refraction type. Five controls without DS viewed acuity charts simulating the retinal image produced when the corrections for each DS eye are worn, performing VA and scoring image quality of each chart. Group median VA (DS versus controls) were compared for each refraction type, and control image quality scores were compared to corresponding VA across refraction types. Median VA for participants with DS ranged from 0.46 logMAR (interquartile range [IQR] = 0.32 to 0.54) with habitual correction to 0.36 logMAR (IQR = 0.28 to 0.54) with VSX, whereas controls ranged from 0.37 logMAR (IQR = 0.29 to 0.42) with habitual correction to 0.01 logMAR (IQR = -0.02 to 0.05) with VSX. Overall image quality scores were best for PFSt and VSX and showed a strong linear relationship with control VA (r = -0.91, P < 0.001), and a lesser correlation with DS VA (r = -0.33, P < 0.001). Using surrogate observers to judge image quality simulations of eyes with DS did not predict actual VA, suggesting additional, non-optical factors may be limiting VA in individuals with DS. Findings may guide clinical refraction practices for patients with DS.

Wound size and location affect the prognosis of penetrating ocular injury

BackgroundOcular trauma is a leading cause of vision loss. Penetrating ocular injury is a major type of open globe injury(OGI), while its epidemiology and clinical characteristics are still uncertain. The aim of this study is to reveal the prevalence and prognostic factors of penetrating ocular injury in the Shandong province.MethodsA retrospective study of penetrating ocular injury was performed at the Second Hospital of Shandong University, from January 2010 to December 2019. Demographic information, injury causes, ocular trauma types, and initial and final visual acuity(VA) were analyzed. To obtain more precise characteristics of penetrating injury, the eye global was divided into three zones and analyzed.ResultsAmong 210 OGI, there are 83 penetrating injuries which account for 39.5% of all. In addition, the final VA of 59 penetrating injuries recovered to 0.1 or better, which possesses the highest frequency among OGI. In order to research the relationship between the wound location and the final VA, we took 74 cases of penetrating injuries without retina or optic nerve damage for analysis. Results show that 62 were male and 12 were female. The average age was 36.01 ± 14.15. The most frequent occupation is the worker followed by the peasant. Statistics show that there is an obvious deviation in the Ocular trauma score (OTS) predicting the final VA and the actual final VA in the 45–65 score group (p < 0.05). Results suggest that the commonest penetrating injury zone is zone III (32 cases, 43.8%). Zone III, which is farthest from the center of the visual axis, has the largest improvement of the final VA (p = 0.0001). On the contrary, there is no statistical difference in the visual improvement in zone I and zone I + II that involves the injury of the central visual axis.ConclusionThis study describes the epidemiology and clinical characteristics of patients hospitalized for penetrating ocular injury without retina damage in Shandong province. It can be concluded that larger size and closer location to the visual axis of damage are accompanied by worse prognosis improvement. The study provides a better understanding of the disease and enlightenment for the prediction of visual prognosis.

Habitual visual acuity and visual acuity threshold demands in Nigerian school classrooms

This study was designed to estimate the burden of blindness and vision impairment in school children, and to determine the proportion of students meeting the visual acuity (VA) demand for their classrooms. From 148 primary and secondary school classrooms in Edo State, Nigeria, the habitual distance and near VA of over 2000 students were measured. Values obtained were compared with the calculated distance VA demand and actual near VA demand for their classrooms. Measures used to calculate the VA demand were working distance and smallest text size on learning materials, at both distance and near. We also determined the relationship between age and calculated VA demand and the effect of factors such as school ownership and school type on the VA demand. Habitual distance vision impairment was found in 0.8% of pupils, including 2 (0.10%) who met the WHO criteria for blindness. The average VA demand at the furthest and nearest sitting position to the board was 0.21 ± 0.23 and 0.65 ± 0.33LogMAR, respectively. Near working distance of students ranged from 15.00 to 37.20 cm, and the near VA demand as well as actual near VA demand (using a 2.5 times acuity reserve) was 0.60 ± 0.17 and 0.20 ± 1.7LogMAR, respectively. LogMAR VA demand increased (size of print decreases) with increasing age, at both distance (r = − 0.549, p = 0.070) and near (r = − 0.921, p < 0.0001). The VA demand at maximum distance and the actual near VA demand differed significantly by school ownership and between primary and secondary schools. Most students had VA better, but up to 11% of students per class had VA poorer than their classroom demands. Although the majority of students had better VA than their classroom demands, for students with reduced vision, learning could be negatively impacted. It is important to continually screen students for vision impairment and ensure prompt referral and treatment. These findings have implications for managing vision problems in children, as well as enabling appropriate classroom arrangements for those with vision impairment.

Prediction of postoperative visual acuity after vitrectomy for macular hole using deep learning-based artificial intelligence.

To create a model for prediction of postoperative visual acuity (VA) after vitrectomy for macular hole (MH) treatment using preoperative optical coherence tomography (OCT) images, using deep learning (DL)-based artificial intelligence. This was a retrospective single-center study. We evaluated 259 eyes that underwent vitrectomy for MHs. We divided the eyes into four groups, based on their 6-month postoperative Snellen VA values: (A) ≥ 20/20; (B) 20/25-20/32; (C) 20/32-20/63; and (D) ≤ 20/100. Training data were randomly selected, comprising 20 eyes in each group. Test data were also randomly selected, comprising 52 total eyes in the same proportions as those of each group in the total database. Preoperative OCT images with corresponding postoperative VA values were used to train the original DL network. The final prediction of postoperative VA was subjected to regression analysis based on inferences made with DL network output. We created a model for predicting postoperative VA from preoperative VA, MH size, and age using multivariate linear regression. Precision values were determined, and correlation coefficients between predicted and actual postoperative VA values were calculated in two models. The DL and multivariate models had precision values of 46% and 40%, respectively. The predicted postoperative VA values on the basis of DL and on preoperative VA and MH size were correlated with actual postoperative VA at 6months postoperatively (P < .0001 and P < .0001, r = .62 and r = .55, respectively). Postoperative VA after MH treatment could be predicted via DL using preoperative OCT images with greater accuracy than multivariate linear regression using preoperative VA, MH size, and age.

Actual Visual Acuity Demands in the Classroom

Purpose: To address the knowledge gap regarding the actual acuity requirements needed in typical kindergarten through grade 12 classrooms by determining an actual logarithm of the minimum angle of resolution (logMAR) and contrast sensitivity requirements in a sample of classrooms for kindergarten through grade 12 in New York City. Methods: Measurements of classroom dimensions with specific attention to viewing distances were made in public and private school classrooms, at various grade levels from kindergarten through grade 12, in New York City. The dimensions of typical text shown to students on classroom smartboards and whiteboards was measured and the mean and range of logMAR values were calculated for various seating locations within the classrooms. Contrast between text and background was estimated by comparing digital images of actual classroom text to Pelli-Robson contrast sensitivity charts. Results: Fourteen classrooms in five schools were evaluated. Classroom dimensions varied from 8 × 10 feet to 23 × 23 feet. Mean logMAR values of lower case text on smartboards and whiteboards varied from 0.93 ± 0.29 (range: 0.83 to 1.32) in the center of the front row to 0.46 ± 0.21 (range: 0.10 to 0.79) in the center of the back row ( P &lt; .001). Contrast was also variable, being highest for black markers on whiteboards (0.00) and lowest on smartboards (0.15 to 0.60). Neither logMAR nor contrast sensitivity values varied significantly by grade level or school ( P &gt; .50 for both). Conclusions: The data reveal that logMAR demands and contrast vary substantially from classroom to classroom and within a classroom based on room dimensions and seating. Although generally supporting current acuity-based pediatric vision screening referral guidelines, the data also provide insight into the potential impact of reduced visual acuity and seating location on visual performance in the classroom. These findings suggest the need to develop logMAR and contrast standards that optimize visual content in classrooms while accommodating a wider range of visual capabilities. [ J Pediatr Ophthalmol Strabismus . 2021;58(1):48–54.]

Visual acuity demands of different language mediums in modern primary school classrooms in Malaysia

Background:Good visual acuity is important for children’s learning but the actual visual acuity (VA) demands of classrooms are not well defined.Methods:In total, 61 classrooms from eight primary schools were included in this study. Classrooms were divided into lower and upper primary which reflect different stages of learning. Three types of national schools were included in the study, which were National, National Types Chinese (C) and Tamil (T). Each type of school utilizes different language as the medium of teaching. The measurements conducted in each classroom were: dimensions, maximum distance a student is seated and vertical height of the distance and near target. Near working distance of 28cm was assumed. Distance and near visual acuity demands (VA) were then calculated.Results:The distance and near VA demands were 0.11 ± 0.26 logMAR and 0.24 ± 0.10 logMAR for lower primary, and 0.09 ± 0.20 logMAR and 0.24 ± 0.09 logMAR for upper primary classrooms respectively. Distance and near VA demands between both stages were not significantly different (p&gt;0.05). The distance and near VA demands for National schools were 0.24 ± 0.17 logMAR and 0.31 ± 0.04 logMAR, National Type (C) were 0.16 ± 0.11 logMAR and 0.13 ± 0.03 logMAR, National Type (T) were 0.09 ± 0.10 logMAR and 0.12 ± 0.03 logMAR respectively. There were significant differences for both distance and near VA demands between types of schools, F(2, 58) 42.19, p = 0.00; F (2, 58) 208.35, p = 0.00 respectively.Conclusions:High levels of visual acuity for distance and near are required to meet the demands of modern classroom environments. Both National Types schools require higher VA demand compared to National schools. These findings suggest current vision screening protocols and cut off points for schools might require revision.

Disorganization of Retinal Inner Layers and Ellipsoid Zone Disruption Predict Visual Outcomes in Central Retinal Vein Occlusion

To assess the associations and predictive value of spectral-domain (SD) OCT inner and outer retinal structural parameters and visual acuity (VA) outcomes in macular edema (ME) secondary to central retinal vein occlusion (CRVO). Retrospective, longitudinal cohort study. Eighty-four patients with ME secondary to CRVO receiving pro re nata anti-vascular endothelial growth factor (VEGF) therapy at 3 tertiary-level retina referral centers. In all participants, VA, demographic and clinical parameters, and SD OCT images from baseline, 3 months, and 12 months were reviewed. Spectral-domain OCT-based morphologic features in the 1500-μm foveal zone were analyzed by masked graders for disorganization of the retinal inner layers (DRIL), ellipsoid zone (EZ) and external limiting membrane disruption, cone outer segment tip (COST) visibility, cysts, subretinal and intraretinal fluid, and epiretinal membranes. Spectral-domain OCT-based retinal structural parameters and VA outcomes. In multivariate analyses adjusting for baseline VA, worsening VA over 1 year was associated with 1-year increases in DRIL (point estimate, 0.06 per 100 μm; P < 0.001) and EZ disruption (0.07 per 100 μm; P= 0.023), but decreased COST visibility (-0.09 per 100 μm; P= 0.018). A 3-month increase in DRIL (0.05 per 100 μm; P= 0.003) and EZ disruption (0.10 per 100 μm; P < 0.001) were the only factors predicting VA worsening over 1 year, after controlling for baseline VA. A multivariate model including 3-month evolution in DRIL, EZ disruption, and VA accounted for 86.3% of variability in 1-year VA change. Absolute differences between predicted and actual 1-year VA were within 2 lines in 80.9%. When DRIL increased by 250 μm or more over 3 months, no eyes showed VA improvement of 1 line or more in 1 year. When EZ disruption decreased by 250 μm or more over 3 months, no eyes worsened by 1 line or more over 1 year. Early recovery over 3 months in both DRIL and EZ parameters are key drivers of 1-year VA outcomes. Predictive models incorporating 3-month changes in DRIL and EZ disruption support their usefulness as potential robust determinants of future VA.

Predicting Visual Acuity by Using Machine Learning in Patients Treated for Neovascular Age-Related Macular Degeneration

To predict, by using machine learning, visual acuity (VA) at 3 and 12 months in patients with neovascular age-related macular degeneration (AMD) after initial upload of 3 anti-vascular endothelial growth factor (VEGF) injections. Database study. For the 3-month VA forecast, 653 patients (379 female) with 738 eyes and an average age of 74.1 years were included. The baseline VA before the first injection was 0.54 logarithm of the minimum angle of resolution (logMAR) (±0.39). A total of 456 of these patients (270 female, 508 eyes, average age: 74.2 years) had sufficient follow-up data to be included for a 12-month VA prediction. The baseline VA before the first injection was 0.56 logMAR (±0.42). Five different machine-learning algorithms (AdaBoost.R2, Gradient Boosting, Random Forests, Extremely Randomized Trees, and Lasso) were used to predict VA in patients with neovascular AMD after treatment with 3 anti-VEGF injections. Clinical data features came from a data warehouse (DW) containing electronic medical records (41 features, e.g., VA) and measurement features from OCT (124 features, e.g., central retinal thickness). The VA of patient eyes excluded from machine learning was predicted and compared with the ground truth, namely, the actual VA of these patients as recorded in the DW. Difference in logMAR VA after 3 and 12 months upload phase between prediction and ground truth as defined. For the 3-month VA forecast, the difference between the prediction and ground truth was between 0.11 logMAR (5.5 letters) mean absolute error (MAE)/0.14 logMAR (7 letters) root mean square error (RMSE) and 0.18 logMAR (9 letters) MAE/0.2 logMAR (10 letters) RMSE. For the 12-month VA forecast, the difference between the prediction and ground truth was between 0.16 logMAR (8 letters) MAE/0.2 logMAR (10 letters) RMSE and 0.22 logMAR (11 letters) MAE/0.26 logMAR (13 letters) RMSE. The best performing algorithm was the Lasso protocol. Machine learning allowed VA to be predicted for 3 months with a comparable result to VA measurement reliability. For a forecast after 12 months of therapy, VA prediction may help to encourage patients adhering to intravitreal therapy.

Use of a Neural Net to Model the Impact of Optical Coherence Tomography Abnormalities on Vision in Age-related Macular Degeneration

To develop a neural network for the estimation of visual acuity from optical coherence tomography (OCT) images of patients with neovascular age-related macular degeneration (AMD) and to demonstrate its use to model the impact of specific controlled OCT changes on vision. Artificial intelligence (neural network) study. We assessed 1400 OCT scans of patients with neovascular AMD. Fifteen physical features for each eligible OCT, as well as patient age, were used as input data and corresponding recorded visual acuity as the target data to train, validate, and test a supervised neural network. We then applied this network to model the impact on acuity of defined OCT changes in subretinal fluid, subretinal hyperreflective material, and loss of external limiting membrane (ELM) integrity. A total of 1210 eligible OCT scans were analyzed, resulting in 1210 data points, which were each 16-dimensional. A 10-layer feed-forward neural network with 1 hidden layer of 10 neurons was trained to predict acuity and demonstrated a root mean square error of 8.2 letters for predicted compared to actual visual acuity and a mean regression coefficient of 0.85. A virtual model using this network demonstrated the relationship of visual acuity to specific, programmed changes in OCT characteristics. When ELM is intact, there is a shallow decline in acuity with increasing subretinal fluid but a much steeper decline with equivalent increasing subretinal hyperreflective material. When ELM is not intact, all visual acuities are reduced. Increasing subretinal hyperreflective material or subretinal fluid in this circumstance reduces vision further still, but with a smaller gradient than when ELM is intact. The supervised machine learning neural network developed is able to generate an estimated visual acuity value from OCT images in a population of patients with AMD. These findings should be of clinical and research interest in macular degeneration, for example in estimating visual prognosis or highlighting the importance of developing treatments targeting more visually destructive pathologies.

Do school classrooms meet the visual requirements of children and recommended vision standards?

BackgroundVisual demands of school children tend to vary with diverse classroom environments. The study aimed to evaluate the distance and near Visual Acuity (VA) demand in Indian school classrooms and their comparison with the recommended vision standards.Materials and methodsThe distance and near VA demands were assessed in 33 classrooms (grades 4 to 12) of eight schools. The VA threshold demand relied on the smallest size of distance and near visual task material and viewing distance. The logMAR equivalents of minimum VA demand at specific seating positions (desk) and among different grades were evaluated. The near threshold was converted into actual near VA demand by including the acuity reserve. The existing dimensions of chalkboard and classroom, gross area in a classroom per student and class size in all the measured classrooms were compared to the government recommended standards.ResultsIn 33 classrooms assessed (35±10 students per room), the average distance and near logMAR VA threshold demand was 0.31±0.17 and 0.44±0.14 respectively. The mean distance VA demand (minimum) in front desk position was 0.56±0.18 logMAR. Increased distance threshold demand (logMAR range -0.06, 0.19) was noted in 7 classrooms (21%). The mean VA demand in grades 4 to 8 and grades 9 to 12 was 0.35±0.16 and 0.24±0.16 logMAR respectively and the difference was not statistically significant (p = 0.055). The distance from board to front desk was greater than the recommended standard of 2.2m in 27 classrooms (82%). The other measured parameters were noted to be different from the proposed standards in majority of the classrooms.ConclusionThe study suggests the inclusion of task demand assessment in school vision screening protocol to provide relevant guidance to school authorities. These findings can serve as evidence to accommodate children with mild to moderate visual impairment in the regular classrooms.

The Neovascular Age-Related Macular Degeneration Database: Report 2: Incidence, Management, and Visual Outcomes of Second Treated Eyes

To study the characteristics of second treated eyes in patients with neovascular age-related macular degeneration (nAMD) treated with ranibizumab in the United Kingdom National Health Service. Multicenter national nAMD database study. Twelve thousand nine hundred fifty-one treatment-naïve eyes of 11,135 patients receiving 92,976 ranibizumab injections. Up to 5 years of routinely collected, anonymized data within electronic medical record systems were extracted remotely from 14 centers. Participating centers exclusively used ranibizumab to treat nAMD (loading phase of 3 monthly injections followed by monthly visits and pro re nata re-treatment). The minimum data set included: age, logarithm of the minimum angle of resolution (logMAR) visual acuity (VA) at baseline and at all subsequent visits, and injection episodes. Baseline, change and actual VA over 3 years, and number of treatments and clinic visits. During the study, 1816 (16.3%) of the 11 135 patients received treatment to the fellow eye. Mean baseline and final VA were 0.66 (standard deviation, 0.32) and 0.65 (0.40) for first treated eyes and 0.41 (0.34) and 0.56 (0.40) for second treated eyes. The rate of VA loss after the loading phase was similar in first and second treated eyes (0.03 and 0.05 logMAR units/year). When fellow eyes with baseline VA worse than 20/200 were excluded to restrict analyses to eyes at risk of nAMD, the rate of second-eye involvement was 14.0% per year (42%/3 years). Mean number of injections/visits in years 1, 2, and 3 were similar for first and second treated eyes (5.6/8.2, 3.9/8.0, 3.8/8.2 and 5.5/8.7, 3.6/9.4, and 3.8/9.1, respectively). Second treated eyes with nAMD commence treatment with better baseline VA, do not show significant vision gain but maintain better VA than first treated eyes at all time points for at least 3 years, making them the more important eye functionally. These data highlight the high burden of second eye involvement, with almost half of all eyes at risk requiring bilateral treatment by 3 years, and the need for regular monitoring of fellow eyes for best visual outcomes which theoretically may reduce the benefits of extended monitoring regimens.

Which visual acuity measurements define high-quality care for patients with neovascular age-related macular degeneration treated with ranibizumab?

The purpose of this study is to define which visual acuity (VA) measurements are the best indicators of high-quality care for patients receiving intravitreal ranibizumab for neovascular age-related macular degeneration (nAMD). Analysis of prospectively collected data recorded within an electronic medical record system on treatment-naive, first-eligible eyes with nAMD, treated with ranibizumab using an as-needed treatment regimen with a minimum follow-up of 1 year. Data collection included the following: age, gender, laterality, type of nAMD, VA, central 1 mm OCT retinal thickness, number of intravitreal injections, and number of follow-up assessments. Data were available on the first-treated eye from 406 patients with at least 1 year follow-up; of these, 198 had data at 2 years. The mean baseline VA of 54.4 Early Treatment Diabetic Retinopathy Study letters improved to 58.5 letters at 12 months and to 56.8 letters at 24 months. The mean VA changes from baseline to 1 year were +6.5, +7.5, +1.7, and -1.5 letters, respectively, for baseline VA categories of 23-35, 36-55, 56-70, and >70 letters. Change in mean VA from the end of the loading phase to year 1 ranged from -2.9 to +1.4 letters for the different baseline VA categories. The mean number of injections were similar across baseline VA categories ranging from 5.7 to 6.0 injections in year 1 and from 3.3 to 3.8 in year 2. This large, real-world series demonstrates that mean change in VA is largely a function of selection criteria and baseline VA. The quality of a service is therefore better judged by actual VA outcomes and maintenance of vision after the loading phase.

Prevalence of visual impairment among the elderly: can it be corrected?

AbstractPurpose To determine the prevalence of visual impairment,low vision and blindness among the elderly of Sari in north of Iran.Methods Through cluster random sampling, 60 clusters were selected, out of which 20 people were systematically selected for this study. Participants received eye examinations including vision, actual visual acuity (AVA), optimal visual acuity (OVA) and refraction. Non‐cycloplegic refraction was performed with an auto refractometer and the results were checked with retinoscopy and subjective refraction. Visual impairment , low vision and blind were defined as vision worse than 20/60, 20/60 to 20/400 and worse than 20/400 in the better eye respectively.Results In this study, 937 people with mean age of 64.7±7.5 years old (from 55 to 87 years) were investigated. The prevalence of visual impairment, blindness, and low vision, based on actual visual acuity (AVA), were 11.0% (9.0‐13.0 CI 95%), 3.7% (2.5‐5.0 CI 95%), and 7.4% (5.7‐9.0 CI 95%), respectively. These findings were 3.7% (2.3‐5.1 CI 95%), 1% (0.2‐1.7 CI95%), and 2.7% (1.5‐3.9 CI 95%), based on OVA respectively. No significant difference was found between genders, but visual impairment was significantly higher in people over 75 years as compared with 55‐59 years old. The most common reasons for visual impairment based on AVA were refractive errors (68.6%) and cataract (16.7%). After correcting refractive errors, the most common causes of visual impairment were cataract (61.3%) and diabetic retinopathy (25.8%).Conclusion Refractive errors and cataract are the main causes of visual impairment in Iranian elderly. Correcting refractive errors and cataract reduces 85% of visual impairment based on AVA.

Late subsequent ocular morbidity in retinopathy of prematurity patients, with emphasis on visual loss caused by insidious ‘involutive’ pathology: an observational series

This paper discusses late complications in eyes of surviving premature infants typically occurring years into the steady state attained after the initial ophthalmic events associated with preterm birth. The study focuses on insidious visual loss, as well as eventual vitreoretinal and anterior segment disorders. We carried out a retrospective uncontrolled study of a case series (n = 31) of late complications to early ocular changes associated with very preterm delivery. The birth years of our subjects extended back to 1941, but only 15 more recent cases fulfilled contemporary criteria for a diagnosis of retinopathy of prematurity (ROP). Fourteen cases involved vitreoretinal pathology (median observation time 14 years, range 6-46 years) with late detachment and/or vitreous haemorrhage. Twelve cases primarily involved anterior segment pathology (median observation time 37 years, range 7-58 years). Eyes in the latter category often showed features of early arrested growth and anterior traction, which, in four eyes, eventually led to enucleation or exenteration as a result of a blind and painful terminal state. The last five cases (observation periods 22-38 years) were labelled 'miscellaneous'. Among the 31 patients, we identified a subgroup in which insidious visual loss was a common feature (n = 20). Initially, some of these cases showed evidence of cicatricial ROP and low vision from early in life. Others retained useful vision and did not present obvious ocular incidents related to the actual visual acuity decline. Based on a variety of clinical ophthalmic preterm appearances, we propose the hypothesis that, in addition to increased structural vulnerability, a reduced functional reserve may pave the way for further abiotrophy or involution over time. This may manifest as reduced resistance to later ophthalmic events, such as disease or trauma, or simply the impact of age.

Relationship Between Visual Acuity and Foveation Window in Infantile Nystagmus by Analyzing Nystagmus Waveforms

Purpose: To report herein on Nystagmus Acuity Estimator Function (NAEF) based on the foveation time, obtained by analyzing waveforms of infantile nystagmus patients and comparing the results with the patients' actual visual acuity. Methods: Electro-oculographic data of 27 patients with infantile nystagmus were reviewed. Data of patients only with jerk type nystagmus and reliable visual acuity were analyzed. The foveation time was measured, and NAEF was calculated and compared with the patients' actual best corrected visual acuity. Results: A correlation analysis of the patients' best corrected visual acuity with NAEF was performed, and the retrieved coefficient was 0.4266. The p-value calculated using the Pearson correlation coefficient was 0.0282, implying that high NAEF correlates positively with visual acuity. Conclusions: Estimated visual acuity, calculated based on the waveforms, positively correlates with the patients' actual visual acuity with statistical significance. However, since the foveation time can be measured only in the patients with jerk-type nystagmus waveforms, further study should be performed on the measurement of the foveation time with other waveforms. Furthermore, the present study shows that such analysis is possible with electrooculogram settings in most general hospitals.

Comparing Estimated and Actual Visual Acuity at High and Low Luminance

How much insight do individuals have into their own visual abilities? This study investigated the extent to which individuals from 18 to 78 years old can accurately predict their own acuity under a broad range of luminances. New psychophysically based methods were developed to facilitate direct comparisons between individuals' estimates of their own visual acuity and their actual acuity. While all age groups appreciate that reductions in luminance have negative consequences on acuity, both younger and middle-age adults underestimated their ability to see in dim conditions. Older adults, however, overestimated their ability to see. These results fail to support the hypothesis that seniors would be the most aware of their limited visual abilities at night. Future research should explore why some seniors are comfortable driving at night while others are not.

Laserkoagulation der altersabhängigen, feuchten Makuladegeneration

Age-related macular degeneration (AMD) is a common disease in ophthalmology. The current status of knowledge in subretinal neovascularisations concerning epidemiology and treatment based on the findings of the macular photocoagulation study is shown. Most important parameters in treatment of subretinal neovascularisations in AMD are exact localization of the membrane in fluorescein angiography, its size and the visual acuity. The treatment of extra-foveal, well demarcated membranes can be recommended. Moreover recent results in the treatment of subfoveal, well demarcated membranes show some benefit for the patient as long as the size of the membrane is lower than 2 discs areas and the actual visual acuity is taken into account. Indocyanin-Green-(ICG)-angiography is recommended in occult subretinal membranes. Guidelines for the treatment are given.