Assessment of Three Therapeutic Procedures in the Prevention of Diabetic Macular Oedema after Phacoemulsification through Intraocular Lens Implementation
Bibliographic record
Abstract
A cataract is an ocular complication of diabetes mellitus, and the risk of developing diabetic macular oedema (DME) increases in cataract surgery. This randomized, single-blind clinical trial study was conducted on 45 eyes (39 patients) with stable diabetic retinopathy with cataract to compare the efficacy of three therapeutic procedures in the prevention of DME after phacoemulsification through intraocular lens implantation. After cataract surgery by phacoemulsification, the patients were randomly assigned into three groups. The group A received 1.25 mg of intravitreal bevacizumab, and group B received a sub-tenon injection of 40 mg triamcinolone at the end of the surgery. The group C received topical diclofenac drops every 8h for four weeks after the surgery. Results showed there was no significant difference in the demographics and clinical features, central macular thickness, and systemic condition of the three groups at the beginning of the study. There was a significant difference between the preoperative and postoperative periods (i.e., three months after surgery) in the three groups regarding mean macular thickness; however, the difference among the three groups was not significant in the post-operative periods. The DME after cataract surgery occurred in 4 eyes (26.67%) in the diclofenac group and three eyes (20.00%) in the intravitreal bevacizumab and three eyes (20.00%) in sub-tenon triamcinolone groups. According to results, the administration of these three therapeutic procedures can be beneficial in the prevention of DME in patients with cataract and diabetic retinopathy.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".