Combined Mitomycin C Application and Free Flap Conjunctival Autograft in Pterygium Surgery
Bibliographic record
Abstract
Purpose To evaluate the long-term postoperative outcome and complication rate of combined intraoperative low-dose mitomycin C application and free conjunctival autograft for the treatment of pterygium. Methods In a prospective, consecutive, noncomparative case series, a series of 46 consecutive patients (50 eyes) with primary pterygium (43 eyes) or recurrent pterygium (7 eyes) were studied. The patients' ages ranged from 23.0 to 80.0 years (mean, 53.4 years). All patients underwent pterygium excision combined with intraoperative low-dose mitomycin C application (0.02% for 2 minutes) and free conjunctival autograft. The mean follow-up period was 29.2 months (range 12 to 41 months). The main outcome measures were recurrence of pterygium and postoperative complications. Results Pterygium recurred to a small extent (0.5 mm) in one eye (2%) of a patient with recurrent pterygium. There were no intraoperative complications. Subconjunctival graft hematoma appeared soon after surgery and resolved spontaneously in five eyes (10%). One eye developed transient high intraocular pressure without optic nerve or visual field defect, and one eye developed mild symblepharon. There were no sight-threatening complications or serious side effects. Conclusions By applying a single low dose of mitomycin C combined with free conjunctival autograft during pterygium excision, the recurrence rate of pterygium can be markedly reduced.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".