Pending clinical study aims to determine if IVMED-80 can effectively treat keratoconus without complementary laser or surgical intervention—and for how long.

With the emergence of unmanned plane, autonomous vehicles, face recognition, and language processing, the artificial intelligence (AI) has remarkably revolutionized our lifestyle. Recent studies indicate that AI has astounding potential to perform much better than human beings in some tasks, especially in the image recognition field. As the amount of image data in imaging center of ophthalmology is increasing dramatically, analyzing and processing these data is in urgent need. AI has been tried to apply to decipher medical data and has made extraordinary progress in intelligent diagnosis. In this paper, we presented the basic workflow for building an AI model and systematically reviewed applications of AI in the diagnosis of eye diseases. Future work should focus on setting up systematic AI platforms to diagnose general eye diseases based on multimodal data in the real world.

Age-related macular degeneration (AMD) is a well-characterized and extensively studied disease. It is currently considered the leading cause of visual disability among patients over 60 years. The hallmark of early AMD is the formation of drusen, pigmentary changes at the macula, and mild to moderate vision loss. There are two forms of AMD: the “dry” and the “wet” form that is less frequent but is responsible for 90% of acute blindness due to AMD. Risk factors have been associated with AMD progression, and they are taking relevance to understand how AMD develops: (1) advanced age and the exposition to environmental factors inducing high levels of oxidative stress damaging the macula and (2) this damage, which causes inflammation inducing a vicious cycle, altogether causing central vision loss. There is neither a cure nor treatment to prevent AMD. However, there are some treatments available for the wet form of AMD. This article will review some molecular and cellular mechanisms associated with the onset of AMD focusing on feasible treatments for each related factor in the development of this pathology such as vascular endothelial growth factor, oxidative stress, failure of the clearance of proteins and organelles, and glial cell dysfunction in AMD.

In the management of glaucoma, recent and upcoming innovations have the potential to contribute to both the efficacy of intraocular pressure (IOP) monitoring and the number of available treatment...

Consensus on the management of astigmatism in cataract surgery

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Introduction. Timing of retinal detachment (RD) following cataract surgery is of importance for both diagnostic and prognostic factors. However, results on RD onset-time following cataract surgery have been conflicting. Method. A systematic pooled analysis of the literature regarding timing of retinal detachment following cataract surgery. Outcomes were verified against an independent dataset. Results. Twenty-one studies, reporting on rates of RD in 3,352,094 eyes of 2,458,561 patients, met our inclusion criteria and were included in the analysis. The mean pooled time to RD following surgery was 23.12 months (95% CI: 17.79–28.45 months) with high heterogeneity between studies (,). Meta-analytic pooling for the risk of retinal detachment revealed a risk of 1.167% (95% CI: 0.900 to 1.468, ,). A retrospective chart review identified 54 pseudophakic RD cases (mean age 65.5, 59.3% males). The 95% confidence interval for the mean time to RD was 3.1–6.75 years. Conclusions. The interval between cataract surgery and RD in a pooled analysis revealed a mean time of approximately 1.5–2.3 years. However, there was high variability between studies. Validation based on our local results showed similar yet slightly longer time frames. Timing of pseudophakic retinal detachment might direct appropriate follow-up, assisting in earlier detection.

A substantial number of epidemiological studies have investigated the possible associations between sunlight exposure and Age-related Macular Degeneration (AMD), but the results from studies are inconsistent. The aim of this meta-analysis was to evaluate the association between sunlight exposure and the risk of AMD. Relevant studies were searched using databases including PubMed, EMBASE, and Web of Science database. Two authors independently extracted data and assessed study quality. The random-effects model was used to calculate the pooled covariates-adjusted odds ratio (OR). Subgroup analyses based on study design, stage of AMD, method of exposure assessment, and study latitude were carried out. The heterogeneity across the studies was tested, as was publication bias. Fourteen eligible studies including 43,934 individuals based on the inclusion criteria were analyzed. The pooled OR for sunlight exposure and AMD was 1.10 (95% CI = 0.98–1.23). In addition, similar insignificant results were observed in further subgroup analyses based on stage of AMD, method of exposure assessment, and study latitude. Sun-avoidance behavior did not decrease the risk of AMD (OR = 1.12, 95% CI = 0.76–1.67). Moderate heterogeneity was observed in most of analyses. The results indicate that sunlight exposure may not be associated with increased risk of AMD based on current published data.