Pediatric Laryngeal Paralysis: A New Proposed Surgical Therapy
Bibliographic record
Abstract
OBJECTIVES: The cricothyroid muscle (CTM) has a separate innervation from that of intrinsic laryngeal muscles; therefore, its action may contribute to airflow resistance in children with laryngeal paralysis (LP) secondary to recurrent laryngeal nerve (RLN) palsy. We proposed removal of the CTM as a means of indirectly widening the paralyzed neonatal glottis. METHODS: A prospective study was conducted using a piglet animal model to simulate LP and evaluate the proposed treatment's outcome. LP was induced via bilateral RLN sectioning in seven piglets. The CTMs were then removed. Animals acted as their own controls. Outcome measures consisted of serial inspiratory and expiratory airflow resistance measurements taken (1) with no intervention, (2) after RLN sectioning, and (3) after CTM removal. Several animals were awakened to assess their clinical responses to the interventions. The paired Student's t-test was used for statistical analysis. RESULTS: Inspiratory airflow resistance was significantly increased by RLN sectioning (p = .0062) and then significantly decreased after subsequent CTM removal (p = .0005). Clinical responses to the interventions mirrored the measured findings. CONCLUSIONS: Removal of the CTM significantly decreases inspiratory airway resistance in piglets with induced LP. This proposed surgical therapy for pediatric bilateral LP warrants further investigation.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".