Lung aerosol deposition in suckling infants
Bibliographic record
Abstract
INTRODUCTION: Aerosol therapy in infants may be greatly compromised by face mask rejection due to squirming and crying. Lung aerosol deposition in crying infants may thereby be greatly reduced. Since 'suckling' on a pacifier calms infants, they should more readily accept a face mask that incorporates a pacifier. However, since infants must breathe nasally while suckling, lung aerosol deposition may be reduced due to impaction in the nose. The aim of the present pilot study was to compare lung aerosol deposition while suckling on a pacifier incorporated into a mask with that obtained while inhaling from a conventional mask. METHODS: Twelve infants <12 months old and who regularly used pacifiers participated as their own controls. Lung aerosol deposition was measured scintigraphically (technetium-(99m)DTPA-labelled normal saline aerosol, MMAD (Mass Median Aerodynamic Diameter) 3 um and GSD (Geometric Standard Deviation) of 2) via jet nebuliser using a conventional mask versus 'suckling' on their pacifier incorporated into a unique mask. RESULTS: Mean lung deposition (± SD) while suckling using a mask with attached pacifier (1.6 ± 0.5% in the right lung) was similar to that with a conventional mask (1.7 ± 0.9%, p=0.81). CONCLUSIONS: Lung aerosol deposition during nasal breathing while suckling on a pacifier-equipped mask is similar to that in infants breathing quietly using a conventional mask, and results comparable with previous data in infants and in nasal breathing models of an infant's upper respiratory tract. Using a pacifier during aerosol treatment in infants may be as efficient as conventional treatment without a pacifier.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".