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Arteriovenous fistulas for microvascular head and neck reconstruction

2015· article· en· W2266130889 on OpenAlexaff
Sami P. Moubayed, Jean Philippe Giot, Andrei Odobescu, Louis Guertin, Patrick G. Harris, Michel Alain Danino

Bibliographic record

VenuePlastic Surgery · 2015
Typearticle
Languageen
FieldMedicine
TopicReconstructive Surgery and Microvascular Techniques
Canadian institutionsUniversité de MontréalCentre Hospitalier de l’Université de Montréal
Fundersnot available
KeywordsMedicineArteriovenous fistulaHead and neckSurgeryFistulaHematomaRadiology

Abstract

fetched live from OpenAlex

BACKGROUND: In head and neck cancer patients, multiple surgeries and radiation can leave the neck depleted of recipient vessels appropriate for microvascular reconstruction. The creation of temporary arteriovenous fistulas using venous interposition for subsequent microvascular reconstruction has rarely been reported in the head and neck. The authors report the largest series of temporary arteriovenous loops for head and neck reconstruction in vessel-depleted necks. METHODS: The authors performed a case series of major head and neck reconstructions using temporary arteriovenous fistulas with a saphenous vein graft. A subclavian surgical approach was used. All reconstructions were performed at least two weeks after the creation of the initial fistula. RESULTS: The authors have performed nine reconstructive cases for malignancy using five different free flaps. The subclavian and transerve cervical arteries were used, and the subclavian, internal jugular and cephalic veins were used for microanastomosis. Two cases of flap hematoma and one case of venous pedicle compression were recorded. No cases of flap failure were reported. CONCLUSIONS: Reconstruction using temporary arteriovenous fistulas is a reliable technique that can be used in the vessel-depleted neck, with excellent outcomes in experienced hands.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.513
Threshold uncertainty score0.711

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.038
GPT teacher head0.260
Teacher spread0.222 · 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

Citations8
Published2015
Admission routes1
Has abstractyes

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