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The forensic and clinicopathological spectrum of the vertebral artery

2025· article· en· W4413858005 on OpenAlexaff
Michael S. Pollanen, K A Sarathchandra Kodikara, Fabio A Tironi

Bibliographic record

VenueForensic Science International · 2025
Typearticle
Languageen
FieldMedicine
TopicCerebrovascular and Carotid Artery Diseases
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsForensic pathologyVertebral arteryForensic scienceMedicineRadiologyPathologyAutopsyVeterinary medicine

Abstract

fetched live from OpenAlex

We report the forensic and clinicopathological spectrum of 14 postmortem cases involving the vertebral artery. In all cases, there was either pontocerebellar infarction (n = 8) or subarachnoid hemorrhage (n = 6). The underlying pathology of the vertebral artery was segmental mediolytic arteriopathy (n = 5), traumatic rupture of the arterial wall (n = 3), arterial dissection (n = 2), or atherosclerosis (n = 4). Histopathologic changes were often present in both the intracranial and extracranial segments of the vertebral artery. In our case series, the most frequent disease in the vertebral artery was segmental mediolytic arteriopathy which sometimes simultaneously involved the superior mesenteric artery. Our data show that a heterogeneous combination of acquired and genetic cofactors likely played a role in etiopathogenesis. The two main cofactors included sudden neck movements from applied external force (7/14 case, 50 %), and genetics (3/14 case, 21 %). Mutations in structural or regulatory genes of the arterial wall appear to be key risk factors and may interact with trauma or neck motion to result in fatal outcomes. We recommend that the autopsy of all cases with suspected vertebral artery lesions include histologic examination of both the intracranial and extracranial segments of the vertebral artery, histologic sampling of the intra-abdominal (mesenteric) arteries, and genetic testing. This will help clarify the role of injury, genetics, and disease when determining the cause of death in these complex cases.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.005
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.001
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.009
GPT teacher head0.281
Teacher spread0.272 · 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 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".

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Citations0
Published2025
Admission routes1
Has abstractno

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