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Great Mediastinal Vein Reconstruction Using Autologous Superficial Femoral Vein Superficial Femoral Vein Graft

2008· article· en· W1975167470 on OpenAlexaff
Ehab Eshtaya, Jean‐François Légaré, John A. Sullivan, Camille L. Hancock Friesen

Bibliographic record

VenueJournal of Cardiac Surgery · 2008
Typearticle
Languageen
FieldMedicine
TopicVenous Thromboembolism Diagnosis and Management
Canadian institutionsDalhousie University
Fundersnot available
KeywordsMedicineFemoral veinVeinRadiologyElectrical conduitSuperior vena cavaSurgeryMagnetic resonance imagingInferior vena cava

Abstract

fetched live from OpenAlex

BACKGROUND AND AIM: Great mediastinal veins may be reconstructed using autologous, synthetic, or allograft conduits. Autologous conduits have been found superior to other conduit options. The superficial femoral vein (SFV) offers excellent early patency, minimal lower limb morbidity, and ease of harvest without accessory suture lines. Although rarely used, the SFV provides an acceptable alternative for conduit in large vein reconstructions. METHODS: Two recent cases using SFV for great mediastinal vein reconstruction were reviewed and operative technique of vein harvest detailed. RESULTS: This is the first report of successful reconstruction of a left superior vena cava using SFV conduit. Both superior vena cava (SVC) reconstructions reported were perfectly patent at intermediate term follow-up (20 and 14 months) as determined by computed tomography angiogram or magnetic resonance imaging. CONCLUSIONS: Successful and durable reconstruction of the SVC or a persistent left subclavian vein is possible with minimal morbidity using the SFV.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0020.000

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 head0.049
GPT teacher head0.277
Teacher spread0.227 · 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

Citations6
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Cardiac SurgerySame topicVenous Thromboembolism Diagnosis and ManagementFrench-language works237,207