Long-Term Visual Outcomes and Clinical Course of Patients With Peters Anomaly
Bibliographic record
Abstract
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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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".