Electromyography in Children's Laryngeal Mobility Disorders
Bibliographic record
Abstract
OBJECTIVES: To describe a consecutive series of children with laryngeal mobility disorders assessed by laryngeal electromyography (LEMG), to propose a grading system for LEMG findings, and to determine whether the LEMG grades correlate with requirement for tracheostomy. DESIGN: Retrospective, observational, uncontrolled study. SETTING: A single pediatric otolaryngology practice. PATIENTS: Children who had LEMG performed and a minimum follow-up of 3 months. MAIN OUTCOME MEASURES: Demographic characteristics, diagnoses, surgical procedures, number of LEMG procedures, and complications were obtained. The LEMG results from the thyroarytenoid and posterior cricoarytenoid muscles were graded 0 to 4 according to amplitude and relation to the phase of respiration. A correlation analysis between the need for tracheostomy and the baseline LEMG score as well as a multivariable analysis to determine the predictors of requirement for tracheostomy were performed. RESULTS: Between April 28, 2008, and November 2, 2011, 43 LEMG procedures were performed on 23 patients (13 girls; mean [SD] age, 1.5 [2.85] years). Eight required tracheostomy. Among the 23 patients, 16 had laryngeal paralysis (11 bilateral, 5 unilateral), 4 had laryngeal dyskinesia, and 3 had miscellaneous conditions. Fourteen had secondary large airway lesions, and 14 had a nonairway diagnosis that affected respiration. The overall LEMG results correlated negatively with requirement for tracheostomy (r = -0.4; P < .05) and were 86.36% accurate compared with endoscopy. No predictors for tracheostomy were identified. CONCLUSIONS: The LEMG grading was accurate and correlated with the requirement for tracheostomy. Combined with endoscopy, the grading may help better characterize laryngeal mobility disorders.
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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 | 0.003 |
| 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".