The Cloverleaf Internal Limiting Membrane Flap Technique for Repair of Challenging Macular Holes
Bibliographic record
Abstract
PURPOSE: This study introduces the cloverleaf internal limiting membrane (ILM) flap technique for managing challenging macular holes, aiming to enhance ILM flap placement and improve functional and anatomical outcomes. METHODS: A retrospective review of cases undergoing the cloverleaf ILM flap technique was conducted at a single center. This technique involves creating multiple ILM flaps in a cloverleaf configuration to enhance the stability and coverage of the macular hole. Clinical characteristics, surgical details, and outcomes were analyzed. Visual acuity measurements were converted to logMAR values. RESULTS: The study included 29 eyes of 29 patients with a mean age of 65.3 years, and 58.6% females. Macular hole aperture and base sizes were 423.7 (±264.9) µ m and 1017.5 (±229.0) µ m, respectively. Preoperatively, 62.1% of cases were phakic and 37.9% were pseudophakic. The median duration of symptoms was 90 (interquartile range: 60-300) days, with surgery performed approximately 34 (interquartile range: 28-69) days after presentation. Anatomical closure was achieved in 93.1% of cases. Patients had a mean 4.5 (±4.4) Snellen lines of improvement in their visual acuity. The median duration of follow-up was 118 (interquartile range: 36-1,491) days. CONCLUSION: The cloverleaf ILM flap technique may serve as a promising approach for challenging macular holes. By creating a cloverleaf configuration of quadratic ILM flaps folded over the macular hole, this technique enhances flap stability, potentially improving macular hole closure success.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".