Outer retinal features in OCT predict visual recovery after primary macula-involving retinal detachment repair.

Hänsli, Christof; Lavan, Suijana; Pfister, Isabel B; Schild, Christin; Garweg, Justus G (2022). Outer retinal features in OCT predict visual recovery after primary macula-involving retinal detachment repair. PLoS ONE, 17(5), e0268028. Public Library of Science 10.1371/journal.pone.0268028

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PURPOSE

To find predictive markers for the visual potential in optical coherence tomography (OCT) one month after surgical repair of macula-involving rhegmatogenous retinal detachment (miRD) with and without internal limiting membrane (ILM) peeling.

METHODS

This retrospective single-center, single-surgeon cohort study included 74 patients who underwent pars plana vitrectomy (PPV) for primary miRD between January 2013 and August 2020 with follow-up examinations for at least 6 months. Patients developing recurrent detachments, media opacities, or with an axial length over 27 mm were excluded from the analysis. LogMAR visual (VA) and LogRAD reading acuity (RA) ± standard deviation (SD), and OCT measurements 6 months after surgery were compared to OCT and VA measurements one month after surgery using multiple linear regression analysis for predictions.

RESULTS

VA increased from 0.34 ± 0.25 at one month to 0.22 ± 0.21 after 6 months [p < 0.001; effect size = -0.662, 95% confidence interval (CI): -(0.99-0.33)]. The continuity of the external limiting membrane (ELM) and ellipsoid zone (EZ) increased between 1 and 6 months. Subfoveal ELM integrity after one month predicted VA [adjusted R2 of 8.0%, F(2, 71) = 4.17, p = 0.018] and RA [adjusted R2 of 29%, F(2, 27) = 6.81, p = 0.002] after 6 months. EZ integrity had a less pronounced predictive effect on VA and RA. ELM integrity after 1 month correlated with better reading acuity after 6 months (p = 0.016).

CONCLUSION

VA and morphological OCT parameters improve between 1 and 6 months after surgery for miRD. The grade of ELM is a better predictor for RA than for VA, explaining more variance.

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