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Record W3103799249 · doi:10.1097/scs.0000000000007131

Gaining Access to the Superior Ophthalmic Vein for Endovascular Embolization of Indirect Carotid-Cavernous Fistulas

2020· article· en· W3103799249 on OpenAlexaff
Patrick Daigle, Connor T. A. Brenna, Leodante da Costa, Victor X. D. Yang, Harmeet Gill

Bibliographic record

VenueJournal of Craniofacial Surgery · 2020
Typearticle
Languageen
FieldMedicine
TopicVascular Malformations Diagnosis and Treatment
Canadian institutionsUniversity of TorontoHealth Sciences CentreSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineSuperior ophthalmic veinEmbolizationCavernous sinusSurgeryCarotid-cavernous fistulaCannulaRadiology

Abstract

fetched live from OpenAlex

ABSTRACT: Carotid-cavernous fistulas (CCFs) are abnormal connections between the carotid arterial system and the cavernous sinus. These acquired vascular malformations may result in severe orbital congestion and sight-threatening complications. The authors present their experience in gaining access to the superior ophthalmic vein to embolize indirect CCFs in three different patients. Surgical exposure and cannulation of the SOV were successful in all 3 cases. One patient developed an orbital compartment syndrome towards the end of the embolization process, after the irrigation cannula was inadvertently dislodged from the SOV. He required a lateral canthotomy and inferior cantholysis but did not suffer from any related sequelae. Signs and symptoms resolved gradually in all patients and cosmetic results were excellent. In our experience, the SOV offers a reliable access to indirect CCFs, but patients should be monitored closely during the embolization process to prevent ophthalmic complications.

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.077
GPT teacher head0.309
Teacher spread0.232 · 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 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

Citations2
Published2020
Admission routes1
Has abstractyes

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