A Randomized Controlled Trial Comparing Femtosecond-Enabled Deep Anterior Lamellar Keratoplasty and Standard Deep Anterior Lamellar Keratoplasty (FEDS Study)
Bibliographic record
Abstract
Abstract Objectives To compare outcomes of femtosecond-enabled deep anterior lamellar keratoplasty (FE-DALK) and standard deep anterior lamellar keratoplasty (S-DALK). Methods An open-label, randomized controlled trial (Kensington Eye Institute, Toronto, Ontario, Canada) including 100 eyes of 97 participants with either keratoconus or corneal scarring, randomized to either FE-DALK (n = 48) or S-DALK (n = 49). Primary outcomes: postoperative astigmatism and surgically induced corneal astigmatism (SIA) – both at 15 months. Secondary outcomes: 6-, 12- and 15-month postoperative uncorrected- and best spectacle-corrected visual acuity, steep and flat keratometry, manifest sphere and astigmatism, rate of conversion to penetrating keratoplasty (PK), big-bubble success, central corneal thickness, endothelial cell count and complications. Results In intention-to-treat analysis, mean postoperative astigmatism in the FE-DALK (n = 30) and S-DALK (n = 30) groups at 15 months was 7.8±4.4 D and 6.3±5.0 D, respectively (p = 0.282) with an adjusted mean difference of 1.3 D (95% CI -1.08,+3.65). Mean SIA (arithmetic) was 9.2±7.8 and 8.8±5.4 D, respectively (p = 0.838) with a mean difference of 0.4 D (95% CI -3.13,+3.85). In an analysis of successful DALK cases only, mean postoperative astigmatism in the FE-DALK (n = 24) and S-DALK (n = 20) groups at 15 months (after excluding 4 eyes with AEs) was 7.3±4.4 and 6.2±4.9 D, respectively (p = 0.531) with an adjusted mean difference of 0.9 D (95% CI -1.94,+3.71). Mean SIA (arithmetic) was 9.1±7.8 and 7.9±4.6 D, respectively (p = 0.547) with a mean difference of 1.2 D (95% CI -2.70,+5.02). Comparison of secondary outcomes showed only weak statistical evidence. Conclusions In this randomized controlled trial, FE-DALK and S-DALK showed comparable functional and anatomical outcomes.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.001 | 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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".