Diffuse corneal haze: a rare presentation of fish-eye disease
Bibliographic record
Abstract
Introduction Fish-eye disease (FED) is a rare, autosomal recessive genetic disorder that can present at any age, from as early as the second decade of life to late adulthood. The hallmark clinical manifestation of FED is dyslipidemia and slowly progressive bilateral corneal opacification, which can impair vision quality due to highly elevated straylight. Here, we report the ophthalmic findings observed in FED by presenting a case that had been misdiagnosed for years until genetic testing was performed.Methods Case report.Results A 50-year-old patient presented with a 30-year history of subnormalvision, which had progressively worsened over the past two years, accompanied by intermittent episodes of bilateral ocular dryness. Ophthalmic examination revealed diffuse corneal haze despiterelatively well-preserved visual acuity. Anterior segment-opticalcoherence tomography (AS-OCT) imaging showed multiple areas of hyperreflective opacities bilaterally throughout the corneal stroma. A lipid panel revealed very low plasma high-density lipoproteincholesterol (HDL-C) levels. Subsequent genetic testing provided an explanation, identifying two novel variants in the LCAT gene, c.840_862dup, p.(Val288Alafs *130) and c.115A > T, p(Lys39*).Conclusion Ultimately, FED should be considered in the differential diagnosis of corneal clouding combined with low plasma HDL-C, which can be investigated using AS-OCT and confirmed through genetic interrogation of the LCAT gene.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".