Microvascular Free Tissue Transfer of the Trapezius Flap in 20 Dogs and a Wallaby
Bibliographic record
Abstract
OBJECTIVE: To determine the feasibility, complications, and clinical outcome of consecutive free trapezius flap transfers in 20 dogs and a wallaby. STUDY DESIGN: Case series. ANIMALS: Dogs (n = 20) and 1 wallaby METHODS: Medical records of 20 dogs and 1 wallaby that had free trapezius flap transfers were evaluated retrospectively for indications, date of transfer, site of flap relocation, flap composition (myocutaneous, muscular, myoosseus), recipient artery and veins, flap ischemia times, surgery time, antithrombotic strategies used, intra- and postoperative complications related to the flap, hospitalization, in hospital duration after flap transfer, and outcome. RESULTS: Free flap transfers (16 muscle, 4 myocutaneous, 1 myoosseus) were used to treat traumatic soft tissue loss (13), neoplasm excision (2), osteomyelitis (4), and soft palate reconstruction (2); all flaps survived. Anti-thrombotic therapy was used in all cases although strategies varied. Postoperative complications were infrequent, generally of low severity, and primarily included donor site seroma formation and infection. CONCLUSIONS: Free trapezius flap was successfully used in 21 consecutive cases for a wide variety of reconstructive techniques with good, functional long-term outcome.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".