Serial Optical Coherence Tomography of Subthreshold Diode Laser Micropulse Photocoagulation for Diabetic Macular Edema
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE To use serial optical coherence tomography (OCT) to evaluate low-intensity, high-density subthreshold diode laser micropulse photocoagulation treatment of clinically significant diabetic macular edema. PATIENTS AND METHODS Eighteen consecutive eyes of 14 patients with clinically significant diabetic macular edema and a minimum foveal thickness of 223 µm or greater were prospectively evaluated by OCT preoperatively and 1, 4, and 12 weeks following treatment. RESULTS Overall, estimated macular edema 3 months postoperatively (minimum foveal thickness – 223 µm) was reduced a mean of 24% (P = .02). Eleven eyes treated for recurrent or persistent clinically significant diabetic macular edema following prior treatment more than 3 months before study entry were most improved, with a mean reduction in estimated macular edema 3 months postoperatively of 59%. No treatment complications were observed. No patient demonstrated laser lesions following treatment. CONCLUSIONS Low-intensity, high-density subthreshold diode laser micropulse photocoagulation can reduce or eliminate clinically significant diabetic macular edema measured by OCT. Further study is warranted. [ Ophthalmic Surg Lasers Imaging 2006;37:370-377.] AUTHORS Drs. Luttrull and Spink are in private practice, Ventura, California. Accepted for publication May 17, 2006. Presented in part at the annual meeting of the American Society of Retina Specialists, Montreal, Quebec, Canada, July 16-20, 2005. Address reprint requests to Jeffrey K. Luttrull, MD, 3160 Telegraph Road, Suite 230, Ventura, CA 93003.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 | 0.000 |
| 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".