<p>Two-year analysis of changes in the optic nerve and retina following anti-VEGF treatments in diabetic macular edema patients</p>
Bibliographic record
Abstract
Purpose: To evaluate long-term structural and functional changes that happen to the optic nerve and retina following ranibizumab (Lucentis) injections in diabetic macular edema (DME) patients. Methods: Patients with clinically significant DME requiring anti-VEGF injections underwent pre-injection baseline, 6, 12, and 24 month follow-up tests. The tests performed were optical coherence tomography (OCT), best-corrected visual acuity (BCVA), and visual field (VF). Wide-field fluorescein angiogram (IVFA) was performed to monitor the progression of diabetic ischemia. Results: A total of 30 patients requiring anti-VEGF injections and 21 control patients not requiring anti-VEGF injections were enrolled in the study. From baseline, the average macular thickness significantly decreased ( p <0.0002) over the 24-month time period. Mean perfused ratio significantly increased ( p <0.0005) at 6, 12, and 24 months. Cup volume and vertical cup-to-disk ratio significantly increased ( p <0.0014) over the study period. This was verified by masked independent grading of patient optic nerve stereo-photographs by glaucoma specialists. BCVA significantly ( p <0.0006) improved over the study period. VFs showed a non-significant trend of deteriorating peripheral vision at 12 and 24 months. Conclusion: Clinically, anti-VEGF therapy appears to affect the optic nerve by increasing cup volume and increasing vertical cup/disk ratio over time. The results provide a cautionary note to monitor both the retina and optic nerve status in patients undergoing frequent injections. Keywords: diabetic macular edema, retina, optic nerve, anti-VEGF, lucentis, ranibizumab
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".