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Record W3005378034 · doi:10.1097/icb.0000000000000977

VENOUS STASIS RETINOPATHY SECONDARY TO MYELIN OLIGODENDROCYTE GLYCOPROTEIN ANTIBODY-POSITIVE OPTIC NEURITIS

2020· article· en· W3005378034 on OpenAlexaff
Mark K. Lukewich, Jonathan A. Micieli

Bibliographic record

VenueRetinal Cases & Brief Reports · 2020
Typearticle
Languageen
FieldMedicine
TopicPeripheral Neuropathies and Disorders
Canadian institutionsKensington HealthToronto Western HospitalSt. Michael's HospitalUniversity of Toronto
Fundersnot available
KeywordsMedicineOptic neuritisOptic nerveMyelin oligodendrocyte glycoproteinOphthalmologyMyelinEdemaMacular edemaMultiple sclerosisRetinalPathologyImmunologyInternal medicineCentral nervous system

Abstract

fetched live from OpenAlex

PURPOSE: To report a case of a 38-year-old woman with venous stasis retinopathy secondary to myelin oligodendrocyte glycoprotein-IgG optic neuritis. METHODS: Observational case report. RESULTS: We report a unique case of venous stasis retinopathy secondary to myelin oligodendrocyte glycoprotein-IgG optic neuritis with significant optic disc edema, tortuous and dilated retinal venules, and retinal hemorrhages, which resolved promptly with high-dose corticosteroids. The retinal changes were likely secondary to severe inflammation of the optic nerve and optic nerve sheath, which exhibited significant postcontrast enhancement on magnetic resonance imaging. Despite aggressive treatment with high-dose corticosteroids and plasmapheresis, the patient had a significant generalized visual field defect at 6 months. CONCLUSION: Venous stasis retinopathy may be secondary to myelin oligodendrocyte glycoprotein-IgG optic neuritis due to reduced venous outflow from significant optic nerve edema. This may be a poor prognostic factor and a marker for more severe optic nerve inflammation.

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)0.002
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: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.014
GPT teacher head0.269
Teacher spread0.254 · 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
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

Citations12
Published2020
Admission routes1
Has abstractyes

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