Intravitreal Versus Subtenon Triamcinolone Acetonide Injection for Diabetic Macular Edema: A Systematic Review and Meta-analysis
Bibliographic record
Abstract
OBJECTIVE: To compare the efficacy of intravitreal (IV) triamcinolone acetonide (IVTA) versus subtenon (ST) triamcinolone acetonide (STTA) injection for the treatment of diabetic macular edema (DME). METHODS: Searches for randomized clinical trials published between 1 January 1950 and 15 March 2011 were conducted using PubMed, MEDLINE, EMBASE, and the Cochrane Library included in the present meta-analysis are five randomized controlled trials, each with a minimum follow-up of 3 mo. All included studies evaluated the efficacy of TA for the treatment of refractory DME, and compared IVTA with STTA by measuring visual acuity (VA), central macular thickness (CMT), and intraocular pressure (IOP). RESULTS: One mo post-injection, treatment with IVTA had significantly improved VA (MD, -0.14 logMAR; 95% CI = -0.16 to -0.13) and reduced CMT (MD = -174.02 μm; 95% CI = -249.97 to -98.08) compared with STTA. At 3 mo post-injection, treatment with IVTA had significantly improved VA (MD = -0.07 logMAR; 95% CI = -0.09 to -0.05) and reduced CMT (MD = -119.46 μm; 95% CI = -176.55 to -62.36) compared with STTA. The benefits of either treatment were no longer significant at 6 mo, and patients had to be retreated. Compared with STTA, IVTA injections produced no difference in IOPs at 1 mo, higher IOPs at 3 mo, and lower IOP values at 6 months CONCLUSIONS: Within 3 mo, IVTA is more effective than is STTA in improving VA and reducing CMT in patients with refractory DME. However, the benefits of either regimen were no longer evident at 6 mo.
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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 | 0.013 | 0.026 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.025 | 0.038 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".