Purpose: The prevalence of keratoconus in the general population is reported to be up to 1 of 84. Over the past 2 decades, diagnosis and management evolved rapidly, but keratoconus screening in clinical practice is still challenging and asks for improving the accuracy of keratoconus detection. Deep learning (DL) offers considerable promise for improving the accuracy and speed of medical imaging interpretation. We establish an inventory of studies conducted with DL algorithms that have attempted to diagnose keratoconus. Methods: This systematic review was conducted according to the recommendations of the PRISMA statement. We searched (Pre-)MEDLINE, Embase, Science Citation Index, Conference Proceedings Citation Index, arXiv document server, and Google Scholar from inception to February 18, 2022. We included studies that evaluated the performance of DL algorithms in the diagnosis of keratoconus. The main outcome was diagnostic performance measured as sensitivity and specificity, and the methodological quality of the included studies was assessed using QUADAS-2. Results: Searches retrieved 4100 nonduplicate records, and we included 19 studies in the qualitative synthesis and 10 studies in the exploratory meta-analysis. The overall study quality was limited because of poor reporting of patient selection and the use of inadequate reference standards. We found a pooled sensitivity of 97.5% (95% confidence interval, 93.6%–99.0%) and a pooled specificity of 97.2% (95% confidence interval, 85.7%–99.5%) for topography images as input. Conclusions: Our systematic review found that the overall diagnostic performance of DL models to detect keratoconus was good, but the methodological quality of included studies was modest.

To compare anti-VEGF treatments for macular disease in terms of costs and clinical outcomes. We identified patients suffering from macular disease and treated either with aflibercept, ranibizumab or both at the largest public eye clinic in Switzerland between January 1st and December 31st 2016 who were insured in one of the two participating health insurance companies. Clinical data were extracted from the electronic health record system. The health insurers provided the health claim costs for the ophthalmologic care and the total health care costs of each patient in the observation period. Using multivariate regression models, we assessed the monthly ophthalmologic and the monthly total costs of patients with no history of switching (ranibizumab vs. aflibercept), patients with a history of switching from ranibizumab to aflibercept, patients switching during the observation period and a miscellaneous group. We examined baseline differences in age, proportion of males, visual acuity (letters), central retinal thickness (CRT) and treatment history before entering the study. We investigated treatment intensity and compared the changes in letters and CRT. The analysis involved 488 eyes (361 patients), 182 on ranibizumab treatment, and 63 on aflibercept treatment, 160 eyes with a history of switching from ranibizumab to aflibercept, and 45 switchers during follow-up and 38 eyes of the miscellaneous group. Compared to ranibizumab, monthly costs of ophthalmologic treatment were slightly higher for aflibercept treatment + 175.0 CHF (95%CI: 1.5 CHF to 348.3 CHF; p = 0.048) as were the total monthly costs + 581.0 CHF (95%CI: 159.5 CHF to 1002.4 CHF; p = 0.007). Compared to ranibizumab, the monthly treatment intensity with aflibercept was similar (+ 0.057 injections/month (95%CI -0.023 to 0.137; p = 0.162), corresponding to a projected annual number of 5.4 injections for ranibizumab vs. 6.1 injections for aflibercept. During follow-up, visus dropped by 0.7 letters with ranibizumab and increased by 0.6 letters with aflibercept (p = 0.243). CRT dropped by − 14.9 μm with ranibizumab and by − 19.5 μm with aflibercept (p = 0.708). The monthly costs of all other groups examined were higher. These real-life data show that aflibercept treatment is equally expensive, and clinical outcomes between the two drugs are similar.

Despite rising global reports of Acanthamoeba keratitis (AK), the incidence of AK in Switzerland remains unknown. This investigator-initiated, retrospective, multicenter study assessed the nationwide incidence of PCR- and/or culture-positive Acanthamoeba results from January 2010 to December 2023. Data were collected from all tertiary care and large ophthalmological facilities in Switzerland, fully anonymized, and aggregated by month and year. We considered all corneal scraping results, whereby the detection method was specific to local standards. We identified 271 PCR- or culture-positive Acanthamoeba cases over 14 years. Applying the population data from the Federal Statistical Office in Switzerland, this corresponds to a mean incidence of 2.29 cases per million people annually. Infections were most common in summer (87 cases, 32.1%), followed by autumn (74 cases, 27.3%), spring (60 cases, 22.1%), and winter (50 cases, 18.5%). We found no significant change in incidence across the investigated period, p = 0.47. This nationwide study reveals a low but stable incidence of AK in Switzerland, in line with other industrialized countries but well below levels reported in tropical or densely populated regions such as India or Egypt. Seasonal variation supports the influence of environmental exposure and underscores the importance of preventive measures during warmer months.