Pectoralis major myofascial flap in head and neck reconstruction: indications and outcomes.
Bibliographic record
Abstract
OBJECTIVE: To review the pectoralis major myofascial (PMMF) flap in head and neck reconstruction. METHOD: Twenty-seven consecutive patients who underwent a PMMF reconstruction between March 1, 2001, and October 1, 2004, were retrospectively reviewed, which, to date, has generated the largest documented series among the world literature. Data acquisition centred on indications for use, tumour staging, defect location, type of wound, and complications (major and minor). RESULTS: Thirteen patients had resections of the primary tumour, whereas 13 others had recurrent disease. Stages varied from T0 to rN3. A variety of defects were filled, but the majority of defects were in the oral cavity (13; 48%). Indications ranged from pure soft tissue filling to salvage of previously failed reconstructions. The outcomes were evaluated as 24 (89%) successes and 6 (22%) major and 6 (22%) minor complications overall, but when only considering cases done for reconstructive salvage, the failure rate is high (3; 50%). CONCLUSION: The PMMF flap remains a successful reconstructive option; however, when used in the context of previously failed reconstructive efforts, the morbidity of the PMMF flap is much higher.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".