Planes for Perforator/Skin Flap Elevation—Definition, Classification, and Techniques
Bibliographic record
Abstract
BACKGROUND: Elevation in different layers achieving thin flaps are becoming relatively common practice for perforator flaps. Although postreconstruction debulking achieves pleasing aesthetic results and is widely practiced, customized approach during elevation to achieve the ideal thickness will increase efficiency while achieving the best possible aesthetic outcome. Multiple planes for elevation have been reported along with different techniques but it is quite confusing and may lack correspondence to the innate anatomy of the skin and subcutaneous tissue. METHODS: This article reviews the different planes of elevation and aims to clarify the definition and classification in accordance to anatomy and present the pros and cons of elevation based on the different layers and provide technical tips for elevation. RESULTS: Five different planes of elevation for perforator flaps are identified: subfascial, suprafacial, superthin, ultrathin, and subdermal (pure skin) layers based on experience, literature, and anatomy. CONCLUSION: These planes all have their unique properties and challenges. Understanding the benefits and limits along with the technical aspect will allow the surgeon to better apply the perforator flaps.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
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".