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Record W4408532935 · doi:10.2147/opth.s507985

Outcomes in Recurrent Rhegmatogenous Retinal Detachment Repair: Does Scleral Buckling at Primary or Secondary Surgery Impact Results?

2025· article· en· W4408532935 on OpenAlexaff
Mélanie Hébert, Jérôme Garneau, Sihame Doukkali, Serge Bourgault, Mathieu Caissie, Éric Tourville, Ali Dirani

Bibliographic record

VenueClinical ophthalmology · 2025
Typearticle
Languageen
FieldMedicine
TopicRetinal and Macular Surgery
Canadian institutionsHôpital du Saint-Sacrement
Fundersnot available
KeywordsMedicineRetinal detachmentScleral bucklingOphthalmologyRetinal

Abstract

fetched live from OpenAlex

Background/Objectives: To analyze outcomes in recurrent rhegmatogenous retinal detachment (re-RRD) repair using pars plana vitrectomy (PPV) combined with scleral buckle (SB) at the first or second surgery. Subjects/Methods: Patients with primary uncomplicated RRD at initial presentation who were operated for re-RRD between 2014 and 2018 were included in this retrospective cohort study (n = 127). Patients were compared based on first and second surgery sequence: PPV then PPVSB (PPV-PPVSB: n = 51, 40%), or PPVSB then PPV (PPVSB-PPV: n = 76, 60%). Anatomical and functional outcomes were evaluated with second surgery success (2SS) defined as absence of reoperation after the second surgery and final pinhole visual acuity (PHVA) in logarithm of the minimum angle of resolution (logMAR), respectively. Results: Mean age at initial presentation was 65.7 years. There were 78 (61%) men and 56 (44%) pseudophakic patients. Median [Q1, Q3] baseline PHVA in logMAR was 0.70 [0.18, 2.30]. SB at first or second surgery did not significantly alter 2SS (PPV-PPVSB: 38, 75% vs PPVSB-PPV: 57, 75%; p = 1.00) or silicone oil use at second surgery (PPV-PPVSB: 18, 35% vs PPVSB-PPV: 36, 47%; p = 0.40). At final follow-up, PHVA did not significantly differ by sequence (p = 0.16). Conclusion: In re-RRD repair, SB at first or second surgery did not alter 2SS and final PHVA.

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)0.004
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.029
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.070
GPT teacher head0.421
Teacher spread0.352 · 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.

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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