[Analysis of choroidal thickness in AP-ROP, threshold disease and ROP without laser photocoagulation]
G Gökgöz-Özisik1, Imren Akkoyun2, S Oto1
1Faculty of Medicine, Department of Ophthalmology, Baskent University, Ankara, Turkey.
Background:
Enhanced depth imaging (EDI) and spectral domain optical coherence tomography (SD-OCT) provide high-definition cross-sectional images of the choroid. Information on alterations in choroidal thickness (CT) after laser photocoagulation (LC) in aggressive posterior retinopathy of prematurity (APROP) and threshold disease (TD) is rare.
Patients And Methods:
A total of 75 eyes were retrospectively analyzed in 4 groups. Groups 1 and 2 included patients with APROP and TD, respectively, who underwent LC. Group 3 included ROP children who did not undergo LC and group 4 included full-term children. Infants aged ≥4 < 7, who had examination of subfoveal (SF) CT with SD-EDI-OCT, visual acuity (VA), spherical equivalent (SE), anterior segment and fundus examination, axial lenght (AXL) were included. The results of SFCT, VA and SE at the age of ≥ 4 < 7 years, AXL, gestational age (GA), birth weight (BW) and age at examination were compared between the groups. Potential risk factors (GA, BW, SE, AXL and SFCT) influencing visual acuity were evaluated by using multivariate linear regression analysis.
Results:
The results of SFCT and AXL were not significantly different between groups 2 and 3 or between groups 3 and 4. There was a significant difference between the other groups for SFCT and AXL and VA was significantly different between all groups. The SE was not significantly different between groups 3 and 4 but there was a significant difference for SE, BW and GA between the groups. Age at examination was not significantly different between the groups. Multivariate linear regression analysis revealed SFCT for groups 1 and 2, GA for group 3 and GA, SFCT and AXL for group 4 as independent risk factors influencing visual acuity.
Conclusion:
The regression model used for groups 1-4 explains the variation of the dependent risk factor LogMar VA for groups 1-4 with 31.2 %, 43.5 %, 9.6 % and 69.4 %, respectively. These values expressed in percentage demonstrate that even more predictors may influence the dependent factor LogMar VA than evaluated in the study.
