MétaCan
Menu
Back to cohort
Record W4407079120 · doi:10.14740/jmc4339

Long-Term Outcomes and Management of Atypical Carotid Web in Nonagenarian

2025· article· en· W4407079120 on OpenAlexvenueno aff
Daniel Burke, Aldin Malkoc, Iden Andacheh

Bibliographic record

VenueJournal of Medical Cases · 2025
Typearticle
Languageen
FieldMedicine
TopicRenal and Vascular Pathologies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineFibromuscular dysplasiaCarotid endarterectomyThrombusStenosisEndarterectomyInternal carotid arteryStroke (engine)EmbolismCarotid stentingRadiologyCulpritCardiologyInternal medicine

Abstract

fetched live from OpenAlex

Internal carotid artery webs (ICAWs) have been described as noninflammatory, nonatherosclerotic shelf-like projections of intimal fibrous tissue which may be the culprit for embolic stroke of unknown origin. Carotid webs are an atypical form of intimal fibromuscular dysplasia (FMD) and internal carotid webs create areas of stagnation and recirculation distal to the web that favor thrombus formation and embolism. Symptomatic carotid webs are conventionally associated with young women presenting with few vascular risk factors and < 50% stenosis in the affected ICA. ICAWs are being described more and more in the vascular literature, but the management of this pathology remains unclear. We describe a rare case of a 90-year-old male who presented with a significantly sclerosed symptomatic right ICAW without evidence of comorbid atherosclerotic disease. The clinical management, intraoperative findings, and postoperative course are described herein. At the age of 90, this patient is the oldest case of symptomatic carotid web recorded in the literature. Successful management with a carotid endarterectomy is an appropriate strategy for treatment even in a nonagenarian. We would favor carotid endarterectomy over carotid artery stenting given the circumferential, fibrotic nature of these lesions.

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)0.001
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 score0.026
Threshold uncertainty score0.193

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.038
GPT teacher head0.349
Teacher spread0.312 · 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

Explore more

Same venueJournal of Medical CasesSame topicRenal and Vascular PathologiesFrench-language works237,207