A Study on the Nonsurgical Correction Treatment Age Window and Long-Term Follow-Up of Infants With Congenital Ear Anomalies in China
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVES: To evaluate the efficacy of ear molding across various initial ages and analyze challenges encountered by infants beyond the optimal treatment age window. METHODS: A retrospective review of 331 infants (527 ears) treated with EarWell was conducted over 5 years from January 2017 to March 2022 at a single center. The treatment duration of the ear molding, success rate, recurrence rate, and complication rate were analyzed among the 3 age groups. Concentrate on evaluating treatment outcomes for infants with an initial age exceeding 42 days. RESULTS: The mean age at initial treatment was 25±28 days. In addition, it includes a child with cryptotia who is 3.5 years old (1278 d). The mean duration of treatment was 7±5 weeks. In the long-term follow-up, the overall treatment success rate was 92%, with 467 ears (88.6%) showing improvement without recurrence, 30 ears (5.7%) experiencing varying degrees of recurrence, and 30 ears (5.7%) showing no improvement or complete recurrence. A total of 20 infants (3%) developed mild skin complications during treatment. CONCLUSIONS: Ear molding is a safe and effective option for the treatment of congenital ear anomalies, with a low recurrence rate during long-term follow-up. For infants with congenital auricular anomalies aged over 42 days, ear molding remains a viable option. Treatment success may be influenced by the age at treatment, the subtype of anomalies, and relies on the assessment of a specialized otologist, expert procedural techniques, as well as thorough understanding and cooperation from parents.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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 it