A Guide to High-Density Porous Polyethene Ear Reconstruction
Bibliographic record
Abstract
Auricular reconstruction is essential for restoring facial symmetry and achieving a well-contoured, natural-appearing ear. Traditional methods using autologous costal cartilage often delay reconstruction until around age 10, when sufficient rib cartilage is available, which can pose physical and psychological challenges for pediatric patients. Porous high-density polyethylene (PHDPE) implants offer significant advantages, including the ability to perform reconstruction earlier, reduced morbidity, improved ear definition, and the possibility of a single-stage outpatient procedure. On the basis of over 35 years of experience and more than 2500 cases, we present our preferred operative technique for PHDPE ear reconstruction. Careful patient selection, preservation of vascularized fascia, and meticulous flap design are critical to achieving optimal outcomes. The superficial temporoparietal fascia (TPF) flap, along with full-thickness skin grafts, provides reliable and durable implant coverage. In cases where the TPF is unavailable, regional or free vascularized fascia flaps can be used. Additional considerations include preoperative hearing evaluation and the option for simultaneous hearing rehabilitation. For patients with facial asymmetry, fat grafting is a valuable adjunct to improve facial balance while deferring skeletal surgery until maturity. While alloplastic reconstruction offers several benefits, including early intervention and excellent aesthetic outcomes, it requires meticulous surgical planning to minimize the risk of implant exposure. On the basis of our experience, PHDPE ear reconstruction in young children provides safe, durable, and highly satisfactory results with minimal psychological impact.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".