A weight‐based formula for tracheal tube size in children
Bibliographic record
Abstract
OBJECTIVE: Age (in years) of the child has conventionally been used in formulae to estimate the tracheal tube (TT) size. The objective of this retrospective study was to test a weight-based formula (WBF) for uncuffed oral TT in children and compare it with the conventional age-based formula (ABF). METHODS: The patient's age, weight, and size of TT internal diameter (ID) were recorded. For comparative analysis, the actual TT size used was compared with predicted TT size, calculated using both the standard ABF [ID = age (years)/4 + 4 mm] and the WBF [ID = weight (kg)/10 + 3.5 mm]. RESULTS: The Pearson's correlation coefficient for age and actual TT size used was 0.77 (95% CI: 0.74-0.80) and between weight and actual TT used was 0.70 (95% CI: 0.66-0.74). The ABF correctly predicted 51.3% of TT sizes while the WBF correctly predicted 44.8% of TT sizes (P = 0.01). The measures of agreement between the actual and predicted TT size were 0.35 and 0.27 for the ABF and WBF respectively. The difference between the percentages of paired predictions for the ABF and WBF was statistically significant (P < 0.001) suggesting that, when correctly predicting the actual tube size used, the WBF functions for a different subset of the patient cohort than the ABF. CONCLUSIONS: This study suggests that in this patient cohort, the WBF is statistically inferior to the conventional ABF. However, our findings also suggest that the WBF may correctly predict TT sizes in a subset of patients in whom the ABF is inaccurate.
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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 | 0.003 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".