Long-Term Outcomes of Femtosecond Laser–Assisted Mushroom Configuration Deep Anterior Lamellar Keratoplasty
Bibliographic record
Abstract
PURPOSE: To review the long-term outcomes after femtosecond laser (FSL)-assisted mushroom configuration deep anterior lamellar keratoplasty (DALK). METHODS: Noncomparative case series of 19 eyes from 19 patients who underwent FSL-assisted mushroom configuration DALK. RESULTS: Data were available for 14 eyes at 1 month, for 14 at 3 months, for 16 at 6 months, for 10 at 9 months, and for 8 at 1 year. Preoperative mean best-corrected visual acuity was 20/108 (range: 20/30-20/400). At 3 months, the mean best-corrected visual acuity was 20/46 (range: 20/25-20/250), and at a mean final follow-up of 13 months (range: 6-29) it was 20/35 (range: 20/15-20/200). The greatest change in mean spherical equivalent was at 3 months [-2.29 diopters (D), range: -7.38 to +3.38 D; from -9.54 D, range: -20.00 to +3.38 D, preoperatively]. There was 56% reduction in mean keratometric cylinder at 6 months (4.00 D, range: 1.04-8.75 D; from 9.13 D, range: 0.50-18.75 D, preoperatively). Complications included 3 cases (15.8%) of small Descemet membrane perforation, none of which required conversion to penetrating keratoplasty; 3 cases (15.8%) of stromal rejection that resolved with topical steroids; and 6 cases (31.6%) of steroid-related intraocular pressure rise that were treated with topical medications. Selective suture removal was initiated a mean of 3.5 months (range: 1.5-6 months) after surgery. CONCLUSIONS: The use of the FSL to perform corneal cuts in a mushroom configuration for DALK is reliable and reproducible. Earlier visual rehabilitation may be possible because of the mechanical stability and wound healing advantages of stepped corneal wounds.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".