Nonsurgical correction of congenital ear abnormalities in the newborn: Case series
Bibliographic record
Abstract
OBJECTIVE: To determine whether a simple, nonsurgical treatment for congenital ear abnormalities (lop-ear, Stahl's ear, protruding ear, cryptotia) improved the appearance of ear abnormalities in newborns at six weeks of age. METHODS: This is a descriptive case series. All newborns with identified abnormalities were referred by their family physician to one paediatrician (WGS) in a small level 2 perinatal centre. The ears were waxed and taped in a standard manner within 10 days of birth. Pictures were taken before taping and at the end of taping (one month). All patients and pictures were assessed by one plastic surgeon (JWT) at six weeks of age and scored using a standard scoring system. A telephone survey of the nontreatment group was conducted. RESULTS: The total number of ears assessed was 90. Of this total, 69 ears were taped and fully evaluated in the study (77%). The refusal rate was 23%. In the treatment group, 59% had lop-ear, 19% had Stahl's ear, 17% had protruding ear and 3% had cryptotia. Overall correction (excellent/improved) for the treatment group was 90% (100% for lop-ear, 100% for Stahl's ear, 67% for protruding ear and 0% for cryptotia). In the nontreatment (refusal) group, 67% of the ears failed to correct spontaneously. No complications were recognized by the authors or parents by six weeks. The percentage of newborns in one year in the perinatal centre with recognized ear abnormalities was 6% (90 of 1600). CONCLUSIONS: A simple, nonsurgical treatment in a Caucasian population appeared to be very effective in correcting congenital ear abnormalities with no complications and high patient/parent satisfaction.
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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 | 0.000 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".