Limbal stem cell deficiency (LSCD) is an eye disorder in which the stem cells responsible for forming the surface skin of the cornea are destroyed by disease. This results in pain, loss of vision, and a cosmetically unpleasant appearance. Many new treatments, including stem cell therapies, are emerging for the treatment of this condition, but assessment of these new technologies is severely hampered by the lack of biomarkers for this disease or validated tools for assessing its severity. The aims of this study were to design and test the reliability of a tool for grading LSCD, to define a set of core outcome measures for use in evaluating treatments for this condition, and to demonstrate their utility. This was achieved by using our defined outcome set (which included the Clinical Outcome Assessment in Surgical Trials of Limbal stem cell deficiency [COASTL] tool) to evaluate the 3-year outcomes for allogeneic ex vivo cultivated limbal epithelial transplantation (allo-CLET) in patients who had bilateral total LSCD secondary to aniridia or Stevens-Johnson syndrome. The results demonstrate that our new grading tool for LSCD, the COASTL tool, is reliable and repeatable, and that improvements in the biomarkers used in this tool correlate positively with improvements in visual acuity. The COASTL tool showed that following allo-CLET there was a decrease in LSCD severity and an increase in visual acuity up to 12 months post-treatment, but thereafter LSCD severity and visual acuity progressively deteriorated.
AimCrowdsourcing is the process of simplifying and outsourcing numerous tasks to many untrained individuals. Our aim was to assess the performance and repeatability of crowdsourcing in the classification of normal and glaucomatous discs from optic disc images.MethodsOptic disc images (N = 127) with pre-determined disease status were selected by consensus agreement from grading experts from a large cohort study. After reading brief illustrative instructions, we requested that knowledge workers (KWs) from a crowdsourcing platform (Amazon MTurk) classified each image as normal or abnormal. Each image was classified 20 times by different KWs. Two study designs were examined to assess the effect of varying KW experience and both study designs were conducted twice for consistency. Performance was assessed by comparing the sensitivity, specificity and area under the receiver operating characteristic curve (AUC).ResultsOverall, 2,540 classifications were received in under 24 hours at minimal cost. The sensitivity ranged between 83–88% across both trials and study designs, however the specificity was poor, ranging between 35–43%. In trial 1, the highest AUC (95%CI) was 0.64(0.62–0.66) and in trial 2 it was 0.63(0.61–0.65). There were no significant differences between study design or trials conducted.ConclusionsCrowdsourcing represents a cost-effective method of image analysis which demonstrates good repeatability and a high sensitivity. Optimisation of variables such as reward schemes, mode of image presentation, expanded response options and incorporation of training modules should be examined to determine their effect on the accuracy and reliability of this technique in retinal image analysis.
A genetic contribution to refractive error has been confirmed by the discovery of more than 150 associated variants in genome-wide association studies (GWAS). Environmental factors such as education and time outdoors also demonstrate strong associations. Currently however, the extent of gene-environment or gene-gene interactions in myopia is unknown. We tested the hypothesis that refractive error-associated variants exhibit effect size heterogeneity, a hallmark feature of genetic interactions. Of 146 variants tested, evidence of non-uniform, non-linear effects were observed for 66 (45%) at Bonferroni-corrected significance ( P < 1.1 × 10 −4 ) and 128 (88%) at nominal significance ( P < 0.05). LAMA2 variant rs12193446, for example, had an effect size varying from −0.20 diopters (95% CI −0.18 to −0.23) to −0.89 diopters (95% CI −0.71 to −1.07) in different individuals. SNP effects were strongest at the phenotype extremes and weaker in emmetropes. A parsimonious explanation for these findings is that gene-environment or gene-gene interactions in myopia are pervasive.
BackgroundThe epidemic rise of diabetes carries major negative public health and economic consequences particularly for low and middle-income countries. The highest predicted percentage growth in diabetes is in the sub-Saharan Africa (SSA) region where to date there has been no data on the incidence of diabetic retinopathy from population-based cohort studies and minimal data on incident diabetes. The primary aims of this study were to estimate the cumulative six-year incidence of Diabetes Mellitus (DM) and DR (Diabetic Retinopathy), respectively, among people aged ≥50 years in Kenya.MethodsRandom cluster sampling with probability proportionate to size were used to select a representative cross-sectional sample of adults aged ≥50 years in 2007-8 in Nakuru District, Kenya. A six-year follow-up was undertaken in 2013–14. On both occasions a comprehensive ophthalmic examination was performed including LogMAR visual acuity, digital retinal photography and independent grading of images. Data were collected on general health and risk factors. The primary outcomes were the incidence of diabetes mellitus and the incidence of diabetic retinopathy, which were calculated by dividing the number of events identified at 6-year follow-up by the number of people at risk at the beginning of follow-up. Age-adjusted risk ratios of the outcomes (DM and DR respectively) were estimated for each covariate using a Poisson regression model with robust error variance to allow for the clustered design and including inverse-probability weighting.ResultsAt baseline, 4414 participants aged ≥50 years underwent complete examination. Of the 4104 non-diabetic participants, 2059 were followed-up at six-years (50 · 2%). The cumulative incidence of DM was estimated at 61 · 0 per 1000 (95% CI: 50 · 3–73 · 7) in people aged ≥50 years. The cumulative incidence of DR in the sample population was estimated at 15 · 8 per 1000 (95% CI: 9 · 5–26 · 3) among those without DM at baseline, and 224 · 7 per 1000 (116.9–388.2) among participants with known DM at baseline. A multivariable risk factor analysis demonstrated increasing age and higher body mass index to be associated with incident DM. DR incidence was strongly associated with increasing age, and with higher BMI, urban dwelling and higher socioeconomic status.ConclusionsDiabetes Mellitus is a growing public health concern with a major complication of diabetic retinopathy. In a population of 1 · 6 million, of whom 150,000 are ≥50 years, we estimated that 1650 people aged ≥50 develop DM per year, and 450 develop DR. Strengthening of health systems is necessary to reduce incident diabetes and its complications in this and similar settings.
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