Femtosecond Laser-Assisted Mushroom Configuration Deep Anterior Lamellar Keratoplasty
Bibliographic record
Abstract
PURPOSE: To review patient outcomes after femtosecond laser-assisted mushroom configuration deep anterior lamellar keratoplasty. METHODS: Seven eyes of seven patients with a mean age of 30 years underwent femtosecond laser-assisted mushroom configuration deep anterior lamellar keratoplasty from April 2008 to September 2008. Patients had keratoconus, corneal ectasia or scarring. Set for 100 mum of residual cornea, the femtosecond laser was used to create a mushroom-shaped recipient bed and donor button (having a larger anterior than posterior diameter). The posterior central lamella was manually dissected using Melles technique. RESULTS: Mean follow up was 4 months (range, 3-6.5 months). Preoperative mean best-corrected visual acuity was 20/95 (range, 20/40-20/400). Intraoperative complications included two cases (28.6%) of small Descemet membrane perforation. Postoperatively, there was one case of stromal rejection that resolved with topical steroids and two cases of steroid-related intraocular pressure rise that were treated with a prostaglandin analog. At 3 months, mean best-corrected visual acuity was 20/40 (range, 20/25-20/60), mean spherical equivalent refraction was -3.21 D (range, -6.75 D to plano), mean cylindrical refractive error was 3.57 D (range, 1.5-7 D), and mean keratometric cylinder measured 5.56 D (range, 3.79-7.00 D). Selective suture removal occurred in six patients (86%) at a mean of 3.8 months (range, 2-6 months) postoperatively. CONCLUSIONS: This preliminary series demonstrates that the use of the femtosecond laser to perform corneal cuts in a mushroom configuration for deep anterior lamellar keratoplasty is feasible. The mechanical stability and wound healing advantages for stepped corneal wounds should be considered in lamellar surgery.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".