Surgeon Preference for Keratoplasty Techniques and Barriers to Performing Deep Anterior Lamellar Keratoplasty
Why this work is in the frame
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Bibliographic record
Abstract
PURPOSE: To identify barriers and facilitators to adopting deep anterior lamellar keratoplasty (DALK) for nonendothelial corneal pathology. METHODS: An anonymous survey consisting of 22 multiple choice and free text questions was designed to gather information on demographic factors of surgeons and DALK surgical practices. The survey was emailed to members of the kera-net, a global online corneal surgeon/surgery platform. RESULTS: A total of 100 surgeons completed the survey, most of whom practice in the United States (73%). Most surgeons (89%) reported performing DALK. Surgeons who did not learn DALK during fellowship (34%) tended to be in practice for higher numbers of years (P < 0.001). Surgeons in private practice are more likely to perform DALK versus those in other settings (92.7% vs. 80.8%, P = 0.087). Surgeons performing more corneal surgeries (at least 100 per year) are more likely to perform DALK than those who perform fewer than 100 per year (52% vs. 14%, P = 0.01). Surgeons who perform Descemet membrane endothelial keratoplasty are more likely to perform DALK than those who do not (81.7% vs. 18.3%, P = 0.014). There was also a positive correlation between PK and DALK surgical volumes (Spearman rank correlation coefficient = 0.57, P < 0.001). The main reasons for surgeon preference for DALK over PK were a desire to preserve the endothelium, intraoperative safety, and decreased complications. Longer surgical time and low patient volume were cited as barriers to adoption of DALK. CONCLUSIONS: Alterations in DALK technique that reduce surgical time and providing more learning opportunities for DALK might improve adoption.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 it