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Record W4416747664 · doi:10.1177/15910199251398391

Venous sinus stenting for cerebral venous congestion-induced trigeminal neuralgia: A case report

2025· article· en· W4416747664 on OpenAlexaff
Diego A. Ortega-Moreno, Ibrahim Almulhim, Rodrigo Fellipe Rodrigues, Jerry C. Ku, Nicole M Cancelliere, Thomas R. Marotta, Julian Spears, Adam A. Dmytriw, Vitor Mendes-Pereira

Bibliographic record

VenueInterventional Neuroradiology · 2025
Typearticle
Languageen
FieldMedicine
TopicCerebral Venous Sinus Thrombosis
Canadian institutionsSt. Michael's Hospital
Fundersnot available
KeywordsTrigeminal neuralgiaSinus (botany)Cerebral veinsStenosisVenographyPulsatile flowVein

Abstract

fetched live from OpenAlex

BackgroundUncommon clinical manifestations of cerebral venous congestion syndrome (CVCS) are challenging for clinicians and may result in inappropriate treatment selection and incomplete clinical resolution. Although trigeminal neuralgia (TN) has been reported in association with CVCS, evidence of symptom resolution following venous sinus stenting (VSS) is lacking. We report a case in which VSS effectively alleviated TN.Case PresentationA middle-aged female patient presented with bilateral pulsatile tinnitus, papilledema, pressure headaches, as well as left-sided TN. Initial computerized tomography venography demonstrated bilateral transverse sinus stenosis and a prominent left mastoid emissary vein. Therefore, VSS was offered. Venous pressure measurements for extra- and intracranial veins were acquired, revealing a pressure gradient. Successful bilateral transverse sinus stenting was performed, resulting in a reduction of the pressure gradient in both sinuses. Endovascular stenting proved effective in managing CVCS symptomatology, including CVCS-induced TN. Residual left-sided pulsatile tinnitus due to the left mastoid emissary vein persisted.ConclusionThis case underscores the role of intracranial VSS in managing CVCS-associated symptoms, demonstrating its potential to relieve both typical and less common manifestations, including TN.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.166
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
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 head0.042
GPT teacher head0.339
Teacher spread0.298 · 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.

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

Citations1
Published2025
Admission routes1
Has abstractyes

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