Assessing the feasibility of breath collection from conscious young children to support volatilome analysis: insights into age limitations and breath sampling requirements
Bibliographic record
Abstract
Breath volatile organic compounds (VOCs) are increasingly under consideration as biomarkers of respiratory disease. Although numerous studies have identified VOCs that distinguish patient groups, a lack of standardisation among published studies has impeded translation into clinical diagnostics. Standardised breath collection protocols have been proposed for adults and children aged >4 years, but optimal methods for collecting breath from younger children remain to be determined. The aim of this study was to assess the feasibility and acceptability of breath sampling among a young paediatric cohort. A total of 61 children (age 6 months-12 years) were recruited prospectively to observational studies of chronic cough at two study sites. Mixed expiratory breath was collected into 1 l Tedlar Bags using either a drinking straw, mouthpiece, or mask. After concentrating onto thermal desorption tubes, the breath was analysed using two-dimensional gas chromatography coupled with time-of-flight mass spectrometry. Breath collection via a mouthpiece was highly feasible for children aged >2 years. Mask-based collection was required for younger children but was poorly tolerated. Drinking straw-based collections were unsuitable for some children aged <4 years due to challenges maintaining a sufficient seal. At least 700 ml of breath was sampled from 72.6% of children. The number of peaks per sample, total peak area per sample, and composition of breath VOCs were all consistent with successful breath sampling. The high feasibility of breath collection via a mouthpiece in our study suggests established protocols designed for children aged over 4 years can be used with confidence for children from as young as 2 years of age.
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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 | 0.018 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".