Bilateral Corneal Ulceration Caused by Vitamin A Deficiency in Eosinophilic Gastroenteropathy
Bibliographic record
Abstract
PURPOSE: Vitamin A deficiency is a very rare condition in the developed world and can lead to a variety of ocular changes from xerosis and xerophthalmia to corneal ulcer and perforation. The treatment of this devastating disease is simple and inexpensive. It is therefore important to recognize and treat accordingly, especially in the event of ulcers unresponsive to treatment or in the presence of severe malnutrition/malabsorption syndromes. The purpose of this case report is to remind physicians of the potentially devastating effects of vitamin A deficiency on the eyes and to demonstrate outcomes after vitamin A treatment. METHODS: Single observational case report. RESULTS: A 29-year-old male with known eosinophilic gastroenteropathy was treated with oral steroids for peripheral ulcerative keratitis. Two weeks after resolution, the patient suffered from peripheral ulcerative keratitis in his other eye, with a self-sealing perforation. Vitamin A deficiency was confirmed and successfully treated, leading to subsequent resolution of signs and symptoms. CONCLUSIONS: Vitamin A deficiency can be present in patients with malabsorption and malnutrition syndromes and should be considered as cause of corneal ulceration.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".