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Record W4399249228 · doi:10.5853/jos.2023.02264

Prevalence and Associations of Dural Arteriovenous Fistulae in Cerebral Venous Thrombosis: Analysis of ACTION-CVT

2024· article· en· W4399249228 on OpenAlexaff
Aaron Shoskes, Liqi Shu, Thanh N. Nguyen, Mohamad Abdalkader, James Giles, Jordan Amar, James E. Siegler, Nils Henninger, Marwa Elnazeir, Sami Al Kasab, Piers Klein, Mirjam R. Heldner, Kateryna Antonenko, Marios Psychogios, David S Liebeskind, Thalia S. Field, Ava L. Liberman, Charles Esenwa, Alexis N. Simpkins, Grace Li, Jennifer Frontera, Lindsey Kuohn, Aaron Rothstein, Ossama Khazaal, Yasmin Aziz, Eva Mistry, Pooja Khatri, Setareh Salehi Omran, Adeel Zubair, Richa Sharma, Robert M. Starke, Jacques J. Morcos, José G. Romano, Shadi Yaghi, Negar Asdaghi

Bibliographic record

VenueJournal of Stroke · 2024
Typearticle
Languageen
FieldMedicine
TopicCerebral Venous Sinus Thrombosis
Canadian institutionsUniversity of British Columbia
FundersNational Center for Advancing Translational Sciences
KeywordsMedicineThrombosisVenous thrombosisThrombophiliaIncidence (geometry)Arteriovenous malformationVitamin K antagonistIntracranial ThrombosisRadiologySurgeryInternal medicineWarfarin

Abstract

fetched live from OpenAlex

Dural arteriovenous fistulae (DAVFs) represent approximately 10% of all intracranial vascular malformations 1 with an incidence of 0.16-1.04per 100,000 person-years. 2,3Prior studies identified an association between cerebral venous thrombosis (CVT) and DAVF although the direction of causality remains uncertain.In one series, 39% of DAVF patients had a CVT identified within an adjacent or downstream sinus, 4 and patients with DAVF have a higher prevalence of thrombophilia, implicating thrombosis in its pathogenesis. 5We aimed to determine the prevalence and associated factors of DAVF in a large multicenter study of treated CVT.The Anticoagulation in the Treatment of Cerebral Venous Thrombosis (ACTION-CVT) study was a multicenter retrospective study comparing outcomes among CVT patients treated with a vitamin K antagonist versus direct oral anticoagulants. 6The study in-

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 score0.055
Threshold uncertainty score0.447

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
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 head0.035
GPT teacher head0.321
Teacher spread0.286 · 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

Citations3
Published2024
Admission routes1
Has abstractyes

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