Outcomes and Complications of the Mustardé Otoplasty: A “Good–Fast–Cheap” Technique for the Prominent Ear Deformity
Bibliographic record
Abstract
BACKGROUND: The Mustardé otoplasty is a commonly used procedure for the correction of the prominent ear deformity. Complication rates related to suture extrusion and long-term outcomes are variable in the literature. The study's purpose was to examine the efficacy and safety of the Mustardé otoplasty and its resource utilization, using an "iron triangle" methodology incorporating quality, time, and cost. METHODS: Retrospective data were collected on patients under 18 years who underwent primary Mustardé otoplasty between 2009 and 2018. Patient demographics, intraoperative details, complications, follow-up, and satisfaction were collected and analyzed. RESULTS: There were 119 Mustardé otoplasties performed on 68 patients, with a median follow-up of 72 weeks (24-476 weeks). In total, 51 of the 68 patients underwent bilateral procedures. The median operative time was 95 minutes (31-133 minutes), translating to a facility case cost of $2046. A total of 24 complications were reported in 17 patients. Minor complications included the following: suture extrusion (n = 20), hematoma (n = 1), and suture abscess (n = 1). Major complications included reoperation (n = 2). The series had a revision rate of 1.7% (n = 2). No additional procedures were documented at other hospitals in the province. The majority (97%) of ear outcomes demonstrated both patient and surgeon satisfaction. CONCLUSIONS: The Mustardé otoplasty demonstrated a high efficacy in the correction of the prominent ear, with low reoperation rates and high patient and surgeon satisfaction. The procedure demonstrated intriguing results in resource utilization, with brief operative times, a "knife and fork" supply chain, and minimal overall case costs. This technique qualifies as a good, fast, and cheap outpatient otoplasty option.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".