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Record W4406256369 · doi:10.1101/2025.01.09.25320019

Anatomic and Functional Outcomes of Lamellar Macular Hole Surgery: Predictive Factors and Associated Complications

2025· preprint· en· W4406256369 on OpenAlexaff
Yosra Er‐Reguyeg, Sihame Doukkali, Mélanie Hébert, Eunice You, Serge Bourgault, Mathieu Caissie, Éric Tourville, Ali Dirani

Bibliographic record

VenuemedRxiv · 2025
Typepreprint
Languageen
FieldMedicine
TopicRetinal and Macular Surgery
Canadian institutionsHôpital du Saint-SacrementUniversité Laval
Fundersnot available
KeywordsMedicineLamellar structureOphthalmologyMaterials science

Abstract

fetched live from OpenAlex

ABSTRACT Purpose To analyze the anatomic and functional outcomes of lamellar macular hole (LMH) surgery. Patients and methods This is a retrospective interventional cohort study of ninety patients with unilateral idiopathic LMH who underwent pars plana vitrectomy (PPV) with membrane peeling for LMH between 2014 and 2021. We evaluated the anatomic and functional success of PPV with membrane peeling for treating LMH, compared surgical outcomes between the two LMH subtypes (“true” LMH and epiretinal foveoschisis (ERMF)), and identified predictive factors for anatomical and functional success. Primary outcomes included final postoperative best-corrected visual acuity (BCVA) and LMH closure. Variables associated with final BCVA were assessed using a multiple linear regression model. Results 51 subjects presented with ERMF, while 39 presented with “true” LMH. LMH closure occurred in 80 cases. “True” LMH cases had a lower rate of closure (“true” LMH closure rate: 76.9%, vs. ERMF closure rate: 94.2%, p=0.005) and were more at risk of developing a postoperative macular hole (p=0.008). A significant difference was observed between median [Q1, Q3] preoperative BCVA (0.42 [0.26, 0.61]) and final BCVA (0.31 [0.14, 0.48], p=0.024). “True” LMH without epiretinal proliferation (β=0.194, p=0.040) was associated with worse final BCVA in multivariate analysis. Conclusion Results support the effectiveness of PPV as a treatment for LMH. “True” LMHs had worse anatomic outcomes than ERMFs.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.816

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.031
GPT teacher head0.275
Teacher spread0.244 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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