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Record W4407426755 · doi:10.1177/19160216241307547

Efficiency of Cephalic Vein Only Anastomosis During Radial Forearm Free Flap

2025· article· en· W4407426755 on OpenAlexaff
Dorsa Mousadoust, Khanh Linh Tran, Anat Bahat-Dinur, Jae Young Kwon, Emily C. Deane, Donald W. Anderson, J. Scott Durham, Eitan Prisman

Bibliographic record

VenueJournal of Otolaryngology - Head and Neck Surgery · 2025
Typearticle
Languageen
FieldMedicine
TopicReconstructive Surgery and Microvascular Techniques
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMedicineSurgeryCephalic veinForearmHead and neckAnastomosisVeinPopulation

Abstract

fetched live from OpenAlex

IMPORTANCE: The closure technique for the radial forearm free flap (RFFF), a commonly utilized flap in head and neck reconstruction, remains a debated topic as there are unique advantages and drawbacks to each technique. OBJECTIVE: The present study aims to report on the outcomes of the closure of the RFFF with the superficial cephalic vein (CV)-only system in terms of venous compromise and flap survival. METHODS (DESIGN, SETTING, PARTICIPANTS, INTERVENTION, MEASURES): A retrospective review of patients who underwent head and neck reconstruction with RFFF between January 2015 and May 2021 at the authors' institution was performed. Cases were categorized as superficial, dual, and deep systems. Multiple population and operative variables were collected for the study group. RESULTS: In total, 221 cases of RFFF were included, of which 169 (76.5%) cases were performed using the CV alone, whereas the remaining 52 (22.5%) cases utilized either the dual or the deep system alone. The operative time in the superficial group was 265 minutes. There were 9 venous complications in the CV group, of which 5 required re-exploration in the operating room and 4 were treated conservatively. All venous-related flap complications were salvaged. CONCLUSION AND RELEVANCE: A majority of the RFFF cases could successfully be completed using the CV as the sole venous drainage, with high rates of flap survival, low complications, and low operative time.

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)0.000
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 score0.038
Threshold uncertainty score0.615

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
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 head0.260
Teacher spread0.249 · 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

Citations3
Published2025
Admission routes1
Has abstractyes

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