Siesky Brent, Harris Alon, Vercellin Alice C Verticchio, Guidoboni Giovanna, Tsai James C
Icahn School of Medicine at Mount Sinai, New York, NY, United States.
Department of Ophthalmology, University of Pavia, Pavia, Italy.
Adv Ophthalmol Optom. 2021 Aug;6:245-262. doi: 10.1016/j.yaoo.2021.04.016. Epub 2021 Jul 12.
Glaucoma is a multifactorial progressive and degenerative optic neuropathy representing one of the world's leading cause of irreversible blindness. Currently, reduction of intraocular pressure remains the only universally approved therapy, yet a wealth of studies has identified significant vascular contributions to the disease process in certain individuals. Population-based studies have identified important racial disparities and differential risk factors in glaucoma prevalence, incidence, and progression. A more significant vascular component has been identified in persons of African descent. Elucidating risk modifiers, including genetic and racial influence, is important when considering individually tailored clinical management of glaucoma. The application of artificial intelligence and mathematical modeling inclusive of demographic considerations, vascular health, and clinical biomarkers may help reduce disease disparities, advance personalized medicine, and provide a comprehensive model of glaucoma.
青光眼是一种多因素的进行性和退行性视神经病变,是全球不可逆性失明的主要原因之一。目前,降低眼压仍然是唯一普遍认可的治疗方法,但大量研究已经确定在某些个体中血管因素对疾病进程有重要影响。基于人群的研究已经确定了青光眼患病率、发病率和进展方面重要的种族差异和不同的危险因素。在非洲裔人群中已发现更显著的血管因素。在考虑针对青光眼进行个体化临床管理时,阐明包括遗传和种族影响在内的风险调节因素很重要。人工智能和数学模型的应用,包括人口统计学因素、血管健康和临床生物标志物,可能有助于减少疾病差异,推进个性化医疗,并提供一个全面的青光眼模型。