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Abstract #95237 Published in IGR 22-2
Long-Term Visual Outcomes and Clinical Course of Patients With Peters Anomaly
Elbaz U; Strungaru H; Strungaru H; Mireskandari K; Stephens D; Ali ACornea 2021; 40: 822-830
PURPOSE: To present long-term clinical and visual outcomes of patients with Peters anomaly. METHODS: The charts of all patients diagnosed with Peters anomaly from January 2000 to December 2012 were reviewed retrospectively. Peters anomaly was classified as type I (with no lens involvement) or type II (presence of keratolenticular adhesions or cataract), with further severity grading to mild, moderate, and severe disease depending on corneal opacity location and size. Mild cases were observed. Moderate cases were managed with pupillary dilation either pharmacologically or surgically. Penetrating keratoplasty (PKP) was reserved for more severe opacity. The main outcome measures were final best spectacle-corrected visual acuity (BSCVA), incidence of glaucoma, graft survival, and nystagmus rates. RESULTS: Sixty eyes of 40 patients were included in the study. The median age of patients at presentation was 0.5 ± 20.7 months (range, 0.0-111.0 months), with a mean follow-up time of 75.8 ± 52.9 months (range, 12.1-225.3 months). Overall, final best spectacle-corrected visual acuity ranged from 0.1 logMAR to no light perception with 33 eyes (55.9%) achieving vision of 1.0 logMAR or better. Clear grafts at the last follow-up were obtained in 67.6% (25/37) of transplanted eyes, 76.0% (19/25) in Peters type I, and 50.0% (6/12) in Peters type II (P = 0.11). The probability of a clear graft at 10 years was 74.2% and 38.9% for type I and type II, respectively. Glaucoma was diagnosed in 33.3% eyes, 90.0% of which occurred after PKP. Nystagmus was highly associated with PKP intervention, occurring in 81.1% (30/37) of eyes undergoing PKP compared with 34.8% (8/23) of eyes with no PKP (P = 0.0003). CONCLUSIONS: Visual rehabilitation in Peters anomaly remains a challenge, but outcomes can be optimized using a comprehensive clinical management algorithm according to disease severity.
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