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AGGRESSIVE INTRACRANIAL DURAL ARTERIOVENOUS FISTULA PRESENTING WITH CEREBROSPINAL FLUID RHINORRHEA

2009· article· en· W2077551399 on OpenAlexaff
Peter W. A. Willems, Robert A. Willinsky, Yoram Segev, Ronit Agid

Bibliographic record

VenueNeurosurgery · 2009
Typearticle
Languageen
FieldMedicine
TopicVascular Malformations Diagnosis and Treatment
Canadian institutionsToronto Western Hospital
Fundersnot available
KeywordsMedicineArteriovenous fistularhinorrheaFistulaCerebrospinal Fluid RhinorrheaSurgeryDural venous sinusesRadiologyCerebrospinal fluid leakDura materCerebrospinal fluidMagnetic resonance imagingInternal medicineThrombosis

Abstract

fetched live from OpenAlex

OBJECTIVE: This is the first report of an aggressive dural arteriovenous fistula presenting with rhinorrhea. It demonstrates the importance of recognizing increased intracranial pressure, and its underlying cause, as the predisposing factor to a spontaneous cerebrospinal fluid leak because this carries implications for management. CLINICAL PRESENTATION: Ten years after minor trauma and directly after an intercontinental flight, a 43-year-old woman presented with rhinorrhea. Right-sided pulsatile tinnitus had been present for the past 9 years. Imaging demonstrated an intracranial dural arteriovenous fistula of the right transverse sinus with cortical venous reflux. Magnetic resonance imaging findings indicated long-standing increased intracranial pressure. INTERVENTION: The fistula was treated by endovascular means, using both transvenous and transarterial approaches, which led to immediate relief of the tinnitus and resolution of the rhinorrhea within 4 days. CONCLUSION: A dural arteriovenous fistula should be included in the differential diagnosis of underlying causes of increased intracranial pressure when examining a patient with a cerebrospinal fluid leak. Treatment of the fistula should precede attempts to treat the rhinorrhea, especially if the fistula has cortical venous reflux.

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 score0.124
Threshold uncertainty score0.615

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.011
GPT teacher head0.239
Teacher spread0.228 · 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

Citations10
Published2009
Admission routes1
Has abstractyes

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