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Record W4310086137 · doi:10.1136/bcr-2022-252266

Acute retinal ischaemia associated with paracentral acute middle maculopathy detected on multimodal imaging: a premonitory sign of severe carotid occlusive disease

2022· article· en· W4310086137 on OpenAlexaff
Fares Antaki, Daniel Milad, Thierry Hamel

Bibliographic record

VenueBMJ Case Reports · 2022
Typearticle
Languageen
FieldMedicine
TopicRetinal and Optic Conditions
Canadian institutionsUniversité de MontréalClinique Neuro-OutaouaisCentre Hospitalier de l’Université de Montréal
Fundersnot available
KeywordsMedicineMaculopathyVisual acuityOphthalmologyRetinalStroke (engine)Fundus (uterus)Fluorescein angiographyRetinopathyDiabetes mellitus

Abstract

fetched live from OpenAlex

A man in his 60s presented with a subacute paracentral scotoma and preserved visual acuity in the left eye. He was found to have a very subtle area of deep retinal whitening at the macula and multiple retinal cholesterol emboli. Optical coherence tomography (OCT) with En face imaging revealed globular paracentral acute middle maculopathy (PAMM). A diagnosis of PAMM associated with branch artery occlusion was made and the patient was immediately transferred to the nearest stroke centre. Investigations revealed severe carotid occlusive disease for which the patient underwent carotid endarterectomy. Paracentral scotomas in patients with little clinical findings on fundus examination should raise the suspicion for PAMM, which is easily identifiable on OCT. Eye care professionals must recognise PAMM as a possible sign of acute retinal arterial ischaemia-an ocular and systemic emergency that requires immediate referral to specialised stroke centres.

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)0.003
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 score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0030.002
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 head0.270
Teacher spread0.258 · 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

Citations9
Published2022
Admission routes1
Has abstractyes

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