Length of the Cricoid and Trachea in Children: Predicting Intubation Depth to Prevent Subglottic Stenosis
Bibliographic record
Abstract
Objective Define the length of the subglottis and trachea in children to predict a safe intubation depth. Methods Patients <18 years undergoing rigid bronchoscopy from 2013 to 2020 were included. The carina and inferior borders of the cricoid and true vocal folds were marked on a bronchoscope and distances were measured. Patient age, weight, height, and chest height were recorded. Four styles of cuffed pediatric endotracheal tubes (ETT) were measured and potential positions of each cuff and tip were calculated within each trachea using five depth of intubation scenarios. Multivariate linear regression was performed to identify predictors of subglottic and tracheal length. Results Measurements were obtained from 210 children (141 male, 69 female), mean (SD) age 3.21 (3.66) years. Patient height was the best predictor of subglottic length (R2: 0.418): Lengthsg (mm) = 0.058 * height (cm) + 2.8, and tracheal length (R2: 0.733): Lengtht (mm) = 0.485 * height (cm) + 21.3. None of the depth of intubation scenarios maintained a cuff‐free subglottis for all ETT styles investigated. A formula for depth of intubation: Lengthdi (mm) = 0.06 * height (cm) + 8.8 found that no ETT cuffs would be in the subglottis and all tips would be above the carina. Conclusion Current strategies for determining appropriate depth of intubation pose a high risk of subglottic ETT cuff placement. Placing the inferior border of the vocal cords 0.06 * height (cm) + 8.8 from the superior border of the inflated ETT cuff may prevent subglottic cuff placement and endobronchial intubation. Level of Evidence 4 Laryngoscope, 132:S1–S10, 2022
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".