Role of intravitreal bevacizumab in management of Eale’s Disease
Bibliographic record
Abstract
OBJECTIVE: To investigate the role of Intravitreal Bevacizumab (IVB), in preventing vitreo-retinal complications in patients of Eale's Disease (ED). METHODS: This randomized control trial was conducted at Armed Forces Institute of Ophthalmology (AFIO), Rawalpindi from May 2015 to December 2016. A total of 52 eyes of 26 patients, diagnosed with stage I or II of ED were randomly divided in two groups. Group A received monthly injections of IVB for 3 months, with steroids and laser photocoagulation. Group B received only steroids and laser treatment. Patients were followed for three months, and were analyzed for different clinical parameters. RESULTS: Mean age of study population was 28.5±2.64 years. Difference in frequency of patients requiring PPV and showing regression in neovascularization was statistically significant between both groups (p=0.005 for both). However, difference in frequency of patients showing progression in stage of ED, regression of vasculitis and best corrected visual acuity at 12 weeks between two groups was not statistically significant (p= 0.012, 0.579, 0.046 respectively). CONCLUSION: Intravitreal Bevacizumab injection, given monthly in patients of ED results in significantly more regression in neovascularization, and less requirement for PPV, as compared to those receiving standard steroids and laser photocoagulation treatment.
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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 | 0.000 |
| 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 | 0.001 | 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".