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Recent developments in the use of artificial intelligence in the diagnosis and monitoring of glaucoma are discussed. To set the context and fix terminology, a brief historic overview of artificial intelligence is provided, along with some fundamentals of statistical modeling. Next, recent applications of artificial intelligence techniques in glaucoma diagnosis and the monitoring of glaucoma progression are reviewed, including the classification of visual field images and the detection of glaucomatous change in retinal nerve fiber layer thickness. Current challenges in the direct application of artificial intelligence to further our understating of this disease are also outlined. The article also discusses how the combined use of mathematical modeling and artificial intelligence may help to address these challenges, along with stronger communication between data scientists and clinicians. 

Altitude affects intraocular pressure (IOP); however, the underlying mechanisms involved and its relationship with ocular hemodynamics remain unknown. Herein, a validated mathematical modeling approach was used for a physiology-enhanced (pe-) analysis of the Mont Blanc study (MBS), estimating the effects of altitude on IOP, blood pressure (BP), and retinal hemodynamics. In the MBS, IOP and BP were measured in 33 healthy volunteers at 77 and 3466 m above sea level. Pe-retinal hemodynamics analysis predicted a statistically significant increase (p < 0.001) in the model predicted blood flow and pressure within the retinal vasculature following increases in systemic BP with altitude measured in the MBS. Decreased IOP with altitude led to a non-monotonic behavior of the model predicted retinal vascular resistances, with significant decreases in the resistance of the central retinal artery (p < 0.001) and retinal venules (p = 0.003) and a non-significant increase in the resistance in the central retinal vein (p = 0.253). Pe-aqueous humor analysis showed that a decrease in osmotic pressure difference (OPD) may underlie the difference in IOP measured at different altitudes in the MBS. Our analysis suggests that venules bear the significant portion of the IOP pressure load within the ocular vasculature, and that OPD plays an important role in regulating IOP with changes in altitude. 

This study investigated the agreement of intraocular pressure measurements using rebound tonometry and applanation tonometry in response to atmospheric changes in a hyperbaric chamber. Twelve eyes of 12 healthy subjects were included in this prospective, comparative, single-masked study. Intraocular pressure measurements were performed by rebound tonometry followed by applanation tonometry in a multiplace hyperbaric chamber at 1 Bar, followed by 2, 3 and 4 Bar during compression and again at 3 and 2 Bar during decompression. Mean differences between rebound and applanation intraocular pressure measurements were 1.6, 1.7, and 2.1 mmHg at 2, 3, and 4 Bar respectively during compression and 2.6 and 2.2 mmHg at 3 and 2 Bar during decompression. Lower limits of agreement ranged from -3.7 to -5.9 mmHg and upper limits ranged from -0.3 to 1.9 mmHg. Multivariate analysis showed that the differences between rebound and applanation intraocular pressure measurements were independent of atmospheric pressure changes (p = 0.79). Intraocular pressure measured by rebound tonometry shows a systematic difference compared to intraocular measured by applanation tonometry, but this difference is not influenced by changes of atmospheric pressure up to 4 Bar in a hyperbaric chamber. Agreement in magnitude of change between devices suggests rebound tonometry is viable for assessing intraocular pressure during atmospheric changes. Future studies should be designed in consideration of expected differences in IOP values provided by the two devices. 

Glaucoma is a multifactorial disease and a leading cause of irreversible blindness worldwide. Current data has demonstrated the approximate distribution of primary openangle glaucoma (POAG) in patients of European, African, Hispanic, and Eastern Asian descent. However, a significant gap in the literature exists regarding the prevalence of POAG in Middle Eastern (ME) populations. Current studies estimate ME POAG prevalence based on a European model. Herein we screened 65 total publications on ME prevalence of POAG and specific risk factors using keywords: “glaucoma”, “prevalence”, “incidence”, “risk factor”, “Middle East”, “Mideast”, “Persian”, “Far East”, as well as searching by individual ME countries through PubMed, Embase, Ovid, Scopus, and Trip searches with additional reference list searches from relevant articles published up to and including March 1, 2021. Fifty qualifying records were included after 15 studies identified with low statistical power, confounding co-morbid ophthalmic diseases, and funding bias were excluded. Studies of ME glaucoma risk factors that identify chromosomes, familial trend, age/gender, socioeconomic status, lifestyle, intraocular pressure, vascular influences, optic disc hemorrhage, cup-to-disc ratio, blood pressure, obstructive sleep apnea, and diabetes mellitus were included in this systematic review. We conclude that the prevalence of POAG in the ME is likely higher than the prevalence rate that European models suggest, with ME specific risk factors likely playing a role. However, these findings are severely limited by the paucity of population-level data in the ME. Well-designed, longitudinal population-based studies with rigorous inclusion and exclusion criteria are ultimately needed to accurately assess the epidemiology and specific mechanistic risk factors of glaucoma in ME populations. 

Glaucoma, the world’s leading cause of irreversible blindness, is a complex disease, with differential presentation as well as ethnic and geographic disparities. The multifactorial nature of glaucoma complicates the study of genetics and genetic involvement in the disease process. This review synthesizes the current literature on glaucoma and genetics, as stratified by glaucoma subtype and ethnicity. Primary open-angle glaucoma (POAG) is the most common cause of glaucoma worldwide, with the only treatable risk factor (RF) being the reduction of intraocular pressure (IOP). Genes associated with elevated IOP or POAG risk include: ABCA1, AFAP1, ARHGEF12, ATXN2, CAV1, CDKN2B-AS1, FOXC1, GAS7, GMDS, SIX1/SIX6, TMCO1, and TXNRD2. However, there are variations in RF and genetic factors based on ethnic and geographic differences; it is clear that unified molecular pathways accounting for POAG pathogenesis remain uncertain, although inflammation and senescence likely play an important role. There are similar ethnic and geographic complexities in primary angle closure glaucoma (PACG), but several genes have been associated with this disorder, including MMP9, HGF, HSP70, MFRP, and eNOS. In exfoliation glaucoma (XFG), genes implicated include LOXL1, CACNA1A, POMP, TMEM136, AGPAT1, RBMS3, and SEMA6A. Despite tremendous progress, major gaps remain in resolving the genetic architecture for the various glaucoma subtypes across ancestries. Large scale carefully designed studies are required to advance understanding of genetic loci as RF in glaucoma pathophysiology and to improve diagnosis and treatment options.