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Record W3201509284 · doi:10.1097/gox.0000000000003816

Head and Neck Reconstruction with Venous Flap: A Case Report

2021· article· en· W3201509284 on OpenAlexaff
Ali R. Abtahi, Catherine Coyne, Andrei Odobescu

Bibliographic record

VenuePlastic & Reconstructive Surgery Global Open · 2021
Typearticle
Languageen
FieldMedicine
TopicReconstructive Surgery and Microvascular Techniques
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsMedicineSurgeryPerfusionHead and neckShunt (medical)ForeheadFree flapBasal cell carcinomaVenous return curveBasal cellRadiologyHemodynamicsCardiologyInternal medicine

Abstract

fetched live from OpenAlex

Summary: Venous flaps are nonphysiologic flaps in which the venous system replaces the vascular circuit found in conventional flaps, serving as inflow as well as outflow. Although a main concern with venous flaps has been their reliability, this can be improved by manipulating their physiology using shunt restriction. The soft, pliable tissue provided by venous flaps coupled with the low donor site morbidity and ease of flap harvest make them ideal for coverage of moderate-sized facial defects, which may be too large for local options yet too small for conventional free flaps. We report the use of a large, 70 cm2 arterialized venous free flap to reconstruct a complex forehead deficit after basal cell carcinoma resection. Furthermore, we present the first report of the successful use of valvulotomes in the case of a large, reverse flow arterialized venous flap where several in-series valves were found to prevent adequate perfusion of the flap. Upon removal of the valves, complete perfusion of the flap was achieved.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.009
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0040.002
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0030.002
Science and technology studies0.0040.003
Scholarly communication0.0030.003
Open science0.0020.003
Research integrity0.0090.005
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 head0.021
GPT teacher head0.284
Teacher spread0.263 · 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
Published2021
Admission routes1
Has abstractyes

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