Intraocular Pressure Control after Trabeculectomy: A Comparison of Mitomycin C and Bevacizumab
Bibliographic record
Abstract
Objective: To analyze and compare the role of mitomycin C and bevacizumab in reducing the intraocular pressure post trabeculectomy. Study Design: Comparative analytical study Place and Duration of Study: Department of Ophthalmology, Indus Medical College, Tando Mohammad Khan from 1st October 2021 to 31st March 2022. Methodology: Sixty patients were enrolled. Patients were divided equally in two groups. Thirty patients were given mitomycin C in Group A while Group B were those 30 patients who were given bevacizumab in a randomized manner. All the cases underwent trabeculectomy and followed upto a year and results were compared. An examination using slit lamp biomicroscope was performed for thorough examination of anterior segments with intraocular pressure recording. Gonioscopy through Goldman-two mirror lens was conducted. Results: The mean age of the patients was 50.23±7.7 years with 41.6 % females and 58.3% males. The intraocular pressure was seen to be controlled in 23 patients at day 1 in Group A and 23 patients in group B. The comparative analysis of pre and post intraocular pressure after trabeculectomy has presented the significant reduction in Group A than Group B at day 1, 6th week as well as at 3rd month or 6th moth to a year. Conclusion: Mitomycin C as well as bevacizumab are highly effective in reducing intraocular pressure post trabeculectomy with mitomycin C being slightly better in efficacy than bevacizumab. Keywords: Intraocular pressure, Trabeculectomy, Effective, Efficacy
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.001 | 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".