Partial Necrosis of Expanding Postauricular Flaps during Auricle Reconstruction: Risk Factors and Effective Management
Bibliographic record
Abstract
BACKGROUND: Tissue expansion has gradually become accepted as a useful adjunct to auricular reconstruction. Necrosis of postauricular flaps during the expansion phase may hinder auricular reconstruction. This study was designed to investigate the risk factors for partial necrosis of expanding postauricular flaps during reconstruction of the auricle and to provide effective management strategies. METHODS: Data were gathered retrospectively for cases of partial necrosis of expanding postauricular flaps from the overall group of patients undergoing auricular reconstruction after preliminary tissue expansion at a treatment center from January of 2002 to January of 2005. Demographic data, ulcer occurrence, treatment procedure, and results were analyzed statistically. RESULTS: The authors observed that 2.5 percent of congenital microtia cases and 13.8 percent of acquired auricular defect cases suffered from partial necrosis of expanding postauricular flaps. Necrosis in more cases occurred during static expansion and was located on the inferior part of the expanded flap. Treatment included the following: (1) auricular reconstruction with autologous costal cartilage or a porous polyethylene framework for a limited term; (2) continuing static expansion, with the postauricular flap extended and fixed in place after expander removal; and (3) removal of the expander and reinsertion of a similar expander more than 6 months after the wound had healed. Each method was applied to different types of cases. Most cases obtained a satisfactory contour and profile of the reconstructed auricle. CONCLUSIONS: Some individual and iatrogenic factors are involved in partial necrosis of expanding postauricular flaps, which can be prevented and minimized. An optimal method can be chosen to treat every case of partial necrosis of the expanding postauricular flap.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".