Effect of Local Anesthesia on Trabeculectomy Success
Bibliographic record
Abstract
PURPOSE: To compare the long-term results of trabeculectomy surgery with subconjunctival anesthesia versus topical lidocaine 2% jelly. METHODS: A retrospective review of the long-term intraocular pressure (IOP) of 57 trabeculectomies previously enrolled in a prospective study comparing subconjunctival anesthesia to topical lidocaine 2% jelly. Baseline data included patient demographics, diagnosis, and ophthalmic history. Postoperative data included IOP, glaucoma therapy, and any interventions. Follow-up was conducted by reviewing the medical charts from July 2002 to August 2007. Differences between the groups were statistically assessed by the Student t test, chi(2) test, Fisher exact test, and Kaplan-Meier survival analysis. RESULTS: Data were available for 57 of the 58 original study patients, with a median age of 65 years. The median follow-up time was 4.2 years for both groups (range: 0.1 to 4.8). There were no statistically significant differences in baseline characteristics and follow-up observations. At the 4-year follow-up, 29.5% of the subconjunctival anesthesia patients versus 39.5% of the topical lidocaine 2% jelly patients were complete success (IOP between 6 to 21 mm Hg and 20% reduction without glaucoma therapy or repeat filtration surgery, P=0.15) and 82.7% of the subconjunctival anesthesia patients versus 95.8% for the topical lidocaine 2% jelly patients were qualified success (above with or without glaucoma therapy, P=0.39). CONCLUSIONS: Though small numbers observed, the 2 anesthetic techniques did not seem to influence the long-term success of trabeculectomy surgery. Further studies with more patients are warranted.
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How this classification was reachedexpand
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".