Pathophysiology of Secondary Macular Hole in Rhegmatogenous Retinal Detachment
Bibliographic record
Abstract
Purpose: To describe the pathophysiology of secondary macular hole (MH) in rhegmatogenous retinal detachment (RRD). Methods: A retrospective cohort of 360 consecutive primary fovea-off RRDs presenting to St. Michael's Hospital, Toronto, from January 2012 to September 2022 were included. Preoperative OCT was assessed for bacillary layer detachment (BALAD) abnormalities. Histological sections of normal eyes were assessed to inform OCT interpretations. Primary outcome measure was the progression of BALAD to full-thickness MH (FTMH). Results: Of the 360 patients, 22.5% (n = 81) had BALAD abnormalities at presentation. Eight percent (29/360) had associated MH, of which 79.3% (23/29) were a BALAD-lamellar hole and 20.7% (6/29) were FTMH. After reattachment, 62% of MHs persisted (18/29), of which 83% (15/18) had BALAD-lamellar holes that subsequently progressed to FTMH in a mean of 8.1 ± 3.2 days. BALAD-lamellar holes had significantly worse postoperative visual acuity (P < 0.001) when compared with other BALAD abnormalities (58/81) or with the rest of the cohort (279/360). OCT spectrum from BALAD to FTMH includes (1) cleavage planes extending from Henle fiber layer into the BALAD; (2) central outer nuclear layer thinning; (3) Müller cell cone loss with tissue remnants at the foveal walls; (4) retinal tissue operculum close to BALAD-MH; and (5) progressive thinning or degradation of the posterior band of BALAD-lamellar hole leading to FTMH. Histological specimens identified foveal regions of low mechanical stability. Conclusions: BALAD plays a crucial role in the pathophysiology of MH in RRDs, which forms owing to sequential changes in four critical areas: RPE-photoreceptor interface, myoid zone, Henle fiber layer, and Müller cell cone with surrounding tissue. Timely management of fovea-off RRD with BALAD may be prudent to avoid the progression to BALAD-lamellar hole, subsequent FTMH, and worse functional outcomes.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".