Acute Annular Outer Retinopathy: Literature Review and a Report of 2 Cases
Bibliographic record
Abstract
Purpose: Acute annular outer retinopathy (AAOR) is an uncommon disease. We present 2 illustrative cases and demonstrate disease evolution using multimodal imaging. The 18 previously reported cases in the peer-reviewed English literature are also reviewed. Methods: We conducted a case series and literature review. Results: We observed complete structural resolution by spectral-domain optical coherence tomography (SD-OCT) and ultra-widefield fundus autofluorescence in 1 case. In the literature review, 20 cases of AAOR were identified, including the 2 we have presented. Fifteen cases were unilateral and 5 bilateral, resulting in a total of 25 eyes with AAOR. Presenting symptoms included visual field defects (72%), decreased vision (48%), and photopsia (36%). Sixty-eight percent had a final visual acuity better than or equal to 20/40, while a minority (14%) were 20/200 or worse. Clinically, all eyes had a peripapillary annular band of gray-white opacification of the deep retina. Conclusions: We have reviewed and summarized the 18 previously reported cases of AAOR in the English literature and have shown for the first time that AAOR may undergo complete recovery of the external limiting membrane and ellipsoid zone on SD-OCT with resolution of disease. There is still much to be understood regarding the pathogenesis of and optimal management of AAOR.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".