Abstract
Background. The search for biomarkers and simple mathematical systems for predicting the severity of age-related macular degeneration (AMD) is necessary and relevant.
Aim: to determine prognostic clinical and ophthalmological indicators that determine the severity of AMD.
Material and methods. The study included observational data of 302 eyes (152 patients), in which the stage of AMD was determined according to the recommendations of the AREDS study. The age of the patients was 71.18 years, 59.9% were women, 40.1% were men. Visual acuity, maximum corrected visual acuity (MCVA), the number of drusen of various calibers, the presence of changes in the retinal pigment epithelium, subretinal neovascular membrane (SNM) and geographic atrophy were determined.
Results. By age, patients with a mild course of AMD were younger than those with a severe course by 6.9 years (p<0.001). Smokers accounted for 31.5% of patients, the course of AMD in such patients was more often severe – 37.2% versus 21.9% in non-smokers (p=0.006). Visual acuity and MCVA were significantly worse in patients with severe AMD (p<0.001). There was no significant difference in the number of small and medium-sized drusen (p>0.5). Large drusen, pigmentary changes and SNM were found almost only in patients with severe AMD. Moreover, pigmentary changes were present in almost all patients with severe AMD (92.6%), and SNM and geographic atrophy – in 23.9% and 21.8%, respectively. According to the data of the discriminant analysis, almost all indicators had a clear relationship with the course of AMD, but the F coefficient was the largest for pigmentary changes, MCVA, the number of large drusen and age. These indicators were included in the system of discriminant equations for determining the AMD severity.
Conclusion. With the help of discriminant analysis, the indicators determining the severity of the course of AMD were found.
Publisher
Bogomolets National Medical University
Reference19 articles.
1. Guymer RH, Campbell TG. Age-related macular degeneration. Lancet. 2023 Apr 29;401(10386):1459-1472. DOI: 10.1016/S0140-6736(22)02609-5.
2. Wong WL, Su X, Li X, Cheung CMG, Klein R, Cheng C-Y, Wong TY. Global prevalence of age-related macular degeneration and disease burden projection for 2020 and 2040: a systematic review and meta-analysis. Lancet Global Health. 2014;2(2):106-116 DOI: 10.1016/S2214-109X(13)70145-1
3. Моісеєнко РО, Голубчиков МВ, Слабкий ГО, Риков СО. Офтальмологічна допомога в Україні за 2006–2011 роки. Київ. 2012. 183 с.
4. Безкоровайна ІМ. Фактори ризику виникнення вікової макулярної дегенерації. Таврійський медико-біологічний вісник. 2013;3,2(16):29-31.
5. Різаєв ЖА, Янгієва НР, Локес ЄП. Розробка методу прогнозування ризику виникнення та раннього виявлення вікової макулярної дегенерації сітківки. Вісник проблем біології і медицини. 2020; 1(155):260-264.