Treatment of Diabetic Macular Edema with Aflibercept and Micropulse Laser (DAM Study)
Bibliographic record
Abstract
Purpose: To investigate the safety and efficacy of micropulse (MP) macular laser in combination with intravitreal aflibercept for the treatment of center-involved diabetic macular edema (CI-DME). Methods: A single-blind prospective randomized controlled pilot trial was performed. In total, 30 eyes of 30 patients with CI-DME and best corrected visual acuity (BCVA) between, and including, 20/30 and 20/400 were enrolled. Enrolled eyes were randomized to 2 groups. Group 1 received intravitreal aflibercept injections (IVT-AFL) with sham laser. Group 2 received IVT-AFL with MP laser. Both groups were followed every 4 weeks for 48 weeks and retreatment was performed on pro re nata basis according to preset criteria. The main outcome measure was the average number of intravitreal injections for each group at 48 weeks. Secondary outcome measures included changes in BCVA and central macular thickness (CMT) at 24 and 48 weeks. Results: The average number of intravitreal injections at 48 weeks was similar between the groups (8.5± 3.3 in Group 1 vs 7.9± 3.6 in Group 2, p=0.61). After 48 weeks, both groups demonstrated an improvement in BCVA and CMT. However, the difference in improvement between the groups was not statistically significant (p=0.18 for BCVA and p=0.57 for CMT). Conclusion: Intravitreal injections of aflibercept led to improvements in BCVA and CMT at 24 and 48 weeks. Addition of MP laser to eyes in group 2 did not offer additional benefit in reducing treatment burden or improving CMT. Eyes that received MP laser showed a numerically greater improvement in BCVA, although this was not statistically significant. Clinicaltrials.gov Identifier: NCT03143192 March 8, 2017. Keywords: anti-VEGF, diabetic macular edema, micropulse laser, visual acuity
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".