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Record W4413343261 · doi:10.3389/fneur.2025.1631546

Intraocular hemorrhage in patients misdiagnosed with central retinal artery occlusion treated with thrombolysis

2025· article· en· W4413343261 on OpenAlexaff
Daniel V. Adamkiewicz, Christian Leal, Yan Ke, Sruthi Arepalli, Kevin Ferenchak, Blaine Cribbs, Riley J. Lyons, Étienne Bénard-Séguin, Nancy J. Newman, Valérie Biousse

Bibliographic record

VenueFrontiers in Neurology · 2025
Typearticle
Languageen
FieldMedicine
TopicRetinal and Optic Conditions
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsCentral retinal artery occlusionMedicineThrombolysisCentral retinal arteryOphthalmologySurgeryRetinalMyocardial infarctionCardiology

Abstract

fetched live from OpenAlex

Introduction: The diagnosis of acute central retinal artery occlusion (CRAO) is commonly delayed in emergency departments (ED) where ophthalmologists are rarely available for immediate consultation. Thrombolysis is sometimes given empirically for presumed CRAO without confirmation of the diagnosis with ocular funduscopic examination. Methods: We describe one case of severe intraocular hemorrhage following intravenous thrombolysis for a retinal detachment misdiagnosed as a CRAO, and two cases of worsening intraocular hemorrhage following intravenous thrombolysis for misdiagnosed CRAO, and review the literature. Results: We identified 4 cases in the literature were thrombolysis given for RAO resulted in ocular hemorrhage. We identified 12 additional cases where thrombolysis given for any indication resulted in intraocular hemorrhage. Discussion: Ocular hemorrhage is a rare but potentially devastating complication of thrombolysis in patients with underlying retinal disorders other than CRAO. Thrombolysis should never be given for acute vision loss without a funduscopic examination or ocular imaging confirming the diagnosis of CRAO.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.524

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.003
GPT teacher head0.196
Teacher spread0.194 · 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 designObservational
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
Published2025
Admission routes1
Has abstractyes

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