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Record W3089045451 · doi:10.1097/icb.0000000000001053

NONARTERITIC ANTERIOR ISCHEMIC OPTIC NEUROPATHY AFTER INTRAVITREAL AFLIBERCEPT FOR AGE-RELATED MACULAR DEGENERATION

2020· article· en· W3089045451 on OpenAlexaff
Andrew B. Paxton, Panos G. Christakis, Jonathan A. Micieli

Bibliographic record

VenueRetinal Cases & Brief Reports · 2020
Typearticle
Languageen
FieldMedicine
TopicIntraoperative Neuromonitoring and Anesthetic Effects
Canadian institutionsKensington HealthUniversity of Toronto
Fundersnot available
KeywordsMedicineAnterior ischemic optic neuropathyOphthalmologyIntraocular pressureAfliberceptMacular degenerationOptic neuropathyOptic nerveIschemic optic neuropathySurgeryBevacizumab

Abstract

fetched live from OpenAlex

PURPOSE: To report a case of nonarteritic anterior ischemic optic neuropathy (NAION) after intravitreal injection in a patient with a history of fellow-eye NAION. METHODS: Observational case report. RESULTS: An 82-year-old woman with a history of fellow eye NAION developed an inferior visual field defect 1 day after an intravitreal aflibercept injection for neovascular age-related macular degeneration. She was found to have optic disk edema and an inferior altitudinal defect, consistent with NAION. The mechanism may have involved compromised perfusion to the optic nerve head related to elevated intraocular pressure or vasoconstriction because of antivascular endothelial growth factor activity. CONCLUSION: Nonarteritic anterior ischemic optic neuropathy is a rare complication of intravitreal injection and may be related to postinjection elevation in intraocular pressure. Monitoring of intraocular pressure postinjection with low-threshold for preinjection aqueous suppression or postinjection anterior chamber paracentesis for persistently elevated intraocular pressure is recommended in patients with a history of NAION.

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 score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.014
GPT teacher head0.264
Teacher spread0.250 · 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

Citations2
Published2020
Admission routes1
Has abstractyes

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