Predictors of uveitic macular edema and functional prognostic outcomes: real-life data from the international AIDA Network uveitis registry - Sota, Jurgen; Mejía-Salgado, Germán; Guerriero, Silvana; Ragab, Gaafar; Costi, Stefania; Paroli, Maria Pia; Hinojosa-Azaola, Andrea; Lopalco, Giuseppe; Breda, Luciana; Giardini, Henrique Ayres Mayrink; Fonollosa, Alex; Chimenti, Maria Sole; et al. (Frontiers in Medicine, 2025)
ObjectivesTo detect factors capable of predicting the development of macular edema (ME) throughout the disease course in patients affected by non-infectious uveitis (NIU).MethodsPredictive factors leading to the development of ME were analyzed through regression analysis. The functional impact of ME on best corrected visual acuity (BCVA) was also examined.ResultsA total of 1,160 NIU patients (1,857 eyes) were analyzed. ME was observed in 148 (12.76%), affecting 211 eyes. It was significantly more frequent in patients with non-anterior NIU (p < 0.0001, RR = 4.01), retinal vasculitis (p < 0.0001), and other structural complications (p = 0.0005). Gender, HLA-B*27 and/or HLA-B*51 positivity, and ethnicity did not show any significant impact on the prevalence of ME (p = 0.635, p = 0.372, p = 0.193, respectively). Four variables were associated with ME development during NIU course: the non–anterior anatomical pattern (p < 0.0001, OR = 4.01), the presence of retinal vasculitis (p = 0.028, OR = 1.68), complications other than ME (p = 0.044, OR = 1.51) and immunosuppressive treatment (p = 0.010, OR 1.69) while the diagnosis of Behçet disease-related uveitis was less likely to be associated with ME development (p = 0.24, OR 0.545). Mean ± SD BCVA was significantly lower in eyes with ME (0.82 ± 0.30) compared to eyes without ME (0.71 ± 0.33).ConclusionME can develop across all NIU types, but is more likely in cases involving the posterior segment and retinal vasculitis. Regular and focused monitoring is recommended for these high-risk patients. The study also highlights the limited predictive value of demographic and HLA-related factors, helping refine clinical risk stratification and predictive modeling in NIU.