Surgical Management of Full-Thickness Macular Holes Spontaneously Arising From Lamellar Macular Holes
Bibliographic record
Abstract
Introduction: To review the literature regarding surgical management of full-thickness macular holes (FTMHs) spontaneously arising from lamellar MHs (LMHs). Methods: The literature on surgically managed FTMHs arising from LMHs was reviewed via Ovid MEDLINE and Embase through June 5, 2022. Results: Seventy-six eyes from 16 articles were included. Forty eyes had internal limiting membrane (ILM) peeling, 32 inverted ILM flap techniques, and 4 an unclear surgical technique. The FTMH closure rate was not significantly different between ILM peeling (34/40 [85%]) and the inverted ILM flap techniques (28/32 [88%]) ( P = .761). The mean (±SD) logMAR visual acuity improved from 0.64 ± 0.46 to 0.25 ± 0.22 (Snellen 20/87 to 20/36) with ILM peeling (n = 30); similar data were not available for inverted ILM flap techniques. Conclusions: Foveal tissue loss, flat hole edges, and limited retinal hydration may result in inverted ILM flap techniques having outcomes similar to those of ILM peeling in repairing FTMHs from LMHs. Future studies are needed to compare techniques.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".