An unusual case of acute angle-closure glaucoma following deep anterior lamellar keratoplasty using the “big bubble” technique
Bibliographic record
Abstract
PURPOSE: To report the first case of acute angle closure due to a high-pressure Descemet membrane detachment following deep anterior lamellar keratoplasty (DALK) using the "big bubble" technique. OBSERVATIONS: A 25-year-old man underwent DALK surgery for keratoconus using the "big bubble" technique in which an air bubble is injected in deep stroma to promote dissection of underlying Descemet membrane from stroma. Surgery was uneventful and the patient was discharged home in good conditions. On post-operative day 1, the patient came back with severe periocular pain. Intra-ocular pressure was found to be 38 mmHg. Anterior-segment OCT revealed a "double anterior chamber" created by a high-pressure Descemet detachment that was occluding the pupil and causing secondary acute angle closure glaucoma. The patient was brought back promptly to the operating room where the high-pressure chamber was properly evacuated, allowing Descemet membrane to properly reattach to stroma. CONCLUSIONS AND IMPORTANCE: Inability to recognize stroma from Descemet membrane during the dissection of the "big bubble technique" can result in failure to evacuate the high-pressure Descemet membrane detachment, putting the patient at risk for acute angle closure glaucoma from occlusion of the pupil. Proper dissection of stroma from underlying DM is a challenging and crucial step in the "big bubble" technique. Several methods, such as the injection of small bubbles in the anterior chamber or the use of intra-operative anterior segment OCT could be employed to prevent such a complication.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.005 | 0.003 |
| 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".