Bibliographic record
Abstract
OBJECTIVE: To document the prevalence of secondary airway lesions (SALs) among children with laryngomalacia (LM). STUDY DESIGN: A cross-sectional observational study. SETTING: Single practice in a tertiary care pediatric facility. SUBJECTS AND METHODS: Patients diagnosed with LM were initially identified from a prospectively kept surgical database. Patients with cardiac/large-vessel malformations, prematurity, repeated or prolonged intubations, acute infections, or prior airway surgery were excluded. Only children who had a full examination of the airway were included. Other associated diagnoses along with demographics, surgical intervention, and type of LM were included. RESULTS: Over an 8-year period, 1112 patients underwent laryngoscopy and bronchoscopy. A total of 108 consecutive cases were diagnosed with LM (78 primary diagnosis and 30 secondary diagnosis). After excluding 17 with disorders associated with large airway disease, 91 LM patients were included. The mean age was 553.23 days (ranging between 5 days and 15 years); 60 were boys and 31 were girls. The prevalence of SALs was 7.7% (95% confidence interval, 7.65-7.76; 7 children; 4 subglottic stenosis, 4 tracheomalacia, 1 bronchomalacia, and 1 choanal atresia). Fifty-nine patients underwent supraglottoplasties, while 1 patient had a tracheostomy. CONCLUSIONS: After accounting for conditions known to be associated with large airway lesions, the prevalence of SALs associated with laryngomalacia was much less than previously reported. The authors hypothesize that the upper-end figures are a reflection of highly select cohorts and the inclusion of patients with other pathology known to be associated with subglottic stenosis, tracheomalacia, and bronchomalacia and low thresholds for diagnosing mild subglottic stenosis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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 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".