Presurgical Presentation of Columellar Features, Nostril Anatomy, and Alveolar Alignment in Bilateral Cleft Lip and Palate after Infant Orthopedics with and without Nasoalveolar Molding
Bibliographic record
Abstract
OBJECTIVES: (1) To evaluate quantitative differences in presurgical presentations of alveolar alignment and nostril anatomy of infants with BCLP treated with nasoalveolar molding (NAM) from those treated with maxillary infant orthopedics only (IO) and (2) to detect interrelationships between presurgical nasoalveolar anatomy, age at lip surgery, age of commencing, and durations of alveolar and nasal molding. METHODS: A retrospective analysis was conducted on nasal-alveolar measurements and presurgical treatment records of infants with BCLP who received lip repair by a single surgeon in a tertiary-care, referral teaching hospital consecutively from 2000 to 2009 after undergoing NAM (n = 29; 51 nostrils) or IO (n = 17; 32 nostrils). Paired t tests analyzed nostril and alveolar symmetry in each group. Intergroup comparisons were made by linear mixed-model regression analyses. Pearson's correlation tests were conducted to detect significant interrelationships within groups. RESULTS: Significant between-group differences were noted in alveolar irregularity (NAM: 3.58 ± 1.02 mm; IO: 7.31 ± 1.28 mm; p < .01), columellar length (NAM: 2.88 ± 0.27 mm; IO: 1.48 ± 0.34 mm; p < .001), columellar width (NAM: 6.10 ± 0.21 mm; IO: 6.88 ± 0.26 mm; p < .01), columellar length/width ratio (NAM: 0.48 ± 0.05; IO: 0.20 ± 0.07; p < .05), and columellar angle (NAM: 0.98 ± 1.1°; IO: 3.69 ± 1.37°; p < .05). Differences in age of commencing presurgical orthopedics, lip surgery, and treatment durations were not significant. Better-aligned alveolar segments in the NAM group did not statistically correlate with nostril dimensions. Alveolar irregularity and nostril height in the IO group strongly correlated. CONCLUSIONS: Infants who received NAM had longer columellae and better-aligned alveolar segments than those who received only IO. Other nostril dimensions were not significantly different.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.001 | 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".