Predicting Nasopharyngeal Depth in Children Using Body Measurements: A Pilot Study
Bibliographic record
Abstract
Importance A predictive formula for pediatric nasopharyngeal depth (ND) could tailor nasopharyngeal swabbing technique to individual anatomy and reduce the incidence of false negatives. Objective To provide a formula predicting ND based on surface anatomy measurements in children. Study Design Prospective pilot study. Setting British Columbia Children’s Hospital Pediatric Otolaryngology Clinic (Canada) between June 2022 to May 2024. Participants Children receiving flexible nasal endoscopy at a tertiary otolaryngology clinic. Intervention and Main Outcome Measures Predictor variables collected were sex, age, height, weight, curved nasal ala-tragus distance, finger lengths, and history of adenoidectomy. The outcome variable of ND was measured from the nasal nares to the posterior nasopharyngeal wall during routine nasal endoscopy. Relationships between predictor and outcome variables were analyzed. A predictive formula for ND was generated using stepwise linear regression, formula simplification, and model validation. Results Sixty-three pediatric patients were included (67% male, average age 6.4 years, range 3 weeks-18 years). ND differed by age: average ND for age <2 was 5.4 ± 0.8 cm, ages 2 to 10 was 7.4 ± 1.1 cm, and ages >10 was 9 ± 1.1 cm. Stepwise linear regression resulted in the formula: ND (cm) = ⅔ (pinky length) + ⅓ (ala-tragus distance) + 1 (if history of adenoidectomy) + 1. R 2 was .78 with an average error of estimation ±0.81 cm. Conclusion Pediatric ND varies with age and surface anatomy dimensions. ND can be predicted in children using simple bedside measurements of pinky length, curved ala-tragus distance, and history of adenoidectomy using the equation ND (cm) = ⅔ (pinky length) + ⅓ (ala-tragus distance) + 1 (if history of adenoidectomy) + 1. Relevance Future studies are required to further validate the proposed predictive formula to ultimately improve accuracy in procedures involving blind instrumentation of the nasal cavity, such as nasopharyngeal swabs and posterior nasal packing.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| 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".