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Record W4400760535 · doi:10.1159/000539147

Submacular and Intraretinal Fluid Associated with Arteritic Anterior Ischemic Optic Neuropathy

2024· article· en· W4400760535 on OpenAlexaff
Danielle Solish, Jonathan A. Micieli

Bibliographic record

VenueCase Reports in Ophthalmology · 2024
Typearticle
Languageen
FieldMedicine
TopicIntraoperative Neuromonitoring and Anesthetic Effects
Canadian institutionsKensington HealthQueen's University
Fundersnot available
KeywordsAnterior ischemic optic neuropathyMedicineOphthalmologyOptic nerveOptic neuropathyIschemic optic neuropathyEdemaSurgery

Abstract

fetched live from OpenAlex

Introduction: Anterior ischemic optic neuropathy (AION) is an ischemic disorder of the optic nerve and a common cause of acute, painless, permanent vision loss. It is divided into two types: arteritic AION (AAION) and non-arteritic anterior ischemic optic neuropathy (NAION). Although subretinal fluid associated with optic disc edema has been reported in cases of NAION, it is rarely described in AAION. Case Presentation: An 86-year-old female with a history of polymyalgia rheumatica presented with sudden vision loss in the left eye. Initial examination revealed left pallid optic disc edema with peripapillary hemorrhages. Optical coherence tomography (OCT) of the left macula showed intraretinal and submacular fluid. The patient was started on 50 mg of oral prednisone daily. The diagnosis of giant cell arteritis (GCA) was later confirmed with a positive temporal artery biopsy. Three weeks after presentation, an OCT was completed which demonstrated complete resolution of the intraretinal and submacular fluid. Although the presence of both intraretinal and subretinal fluid has been previously documented in cases of NAION, it is rarely reported in a patient with GCA. Conclusion: This is a newly described case of subretinal and intraretinal fluid in a patient with AAION. We postulate that the pathophysiology behind this is mediated by associated choroidal ischemia leading to altered permeability. OCT is an important imaging modality allowing for signs of GCA to be better characterized.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.036
Threshold uncertainty score0.649

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.012
GPT teacher head0.282
Teacher spread0.270 · 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 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

Citations1
Published2024
Admission routes1
Has abstractyes

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