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Record W2940326105 · doi:10.1097/icb.0000000000000875

NOVEL SURGICAL TECHNIQUE TO REMOVE RETAINED SUBFOVEAL PERFLUOROCARBON LIQUID

2019· article· en· W2940326105 on OpenAlexaff
Mostafa Hanout, Rajeev H. Muni

Bibliographic record

VenueRetinal Cases & Brief Reports · 2019
Typearticle
Languageen
FieldMedicine
TopicRetinal and Macular Surgery
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsPars planaVitrectomyCannulaMedicineOptical coherence tomographySurgeryPerforationOphthalmologyVisual acuityMaterials science

Abstract

fetched live from OpenAlex

PURPOSE: To describe a novel surgical technique to remove retained subfoveal perfluorocarbon liquid (PFCL). METHODS: After setting up for 23-G pars plana vitrectomy, a 38-G flexible-tip macular hydrodissection cannula connected to the automated viscous fluid infusion kit was used to create a small retinotomy approximately 700 μm to 800 μm inferior to the fovea and induce macular detachment involving the retained PFCL bubble. The flexible cannula was bent at its junction with the shaft and was carefully advanced through the same retinotomy into the subretinal space to access and directly aspirate the retained subfoveal PFCL bubble. Fluid-air exchange was then performed, and surgery was concluded. RESULTS: The retained subfoveal PFCL bubble was successfully removed with restoration of normal foveal architecture on optical coherence tomography and with objective and subjective improvement of central vision. CONCLUSION: We report a novel surgical technique combining macular detachment with direct aspiration of the retained subfoveal PFCL without direct perforation of the foveal center. This technique may provide an alternative approach to manage this difficult complication.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.013
GPT teacher head0.269
Teacher spread0.256 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
Domainnot available
GenreMethods

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

Citations5
Published2019
Admission routes1
Has abstractyes

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