Volatile organic breath components and exercise induced bronchoconstriction in asthmatic children
Bibliographic record
Abstract
INTRODUCTION: Asthma is one of the most common chronic diseases in childhood and is generally characterized by exercise induced bronchoconstriction (EIB). Assessing EIB is time consuming and expensive as it requires a fully equipped pulmonary function laboratory. Analysis of volatile organic compounds (VOCs) in breath is a novel technique for examining biomarkers which may associate with asthma features. The aim of this pilot study was to identify potential markers in the relationship between EIB and VOCs. METHODS: Children between four and 14 years old were asked to provide a breath sample prior to undergoing an exercise challenge test to assess for EIB. RESULTS: Breath samples were collected and analyzed in 46 asthmatic children, 21 with EIB and 25 without EIB (NO-EIB). Molecular features (MFs) were not significantly different between EIB and NO-EIB controls. 29 of the 46 children were corticosteroid naïve, 10 with EIB and 13 without. In the corticosteroid naïve group EIB was associated with increased MF23 and MF14 in the lower breath sample (p-value < 0.05). CONCLUSION: This pilot study shows that EIB was related to an increased MF14 and MF23 in corticosteroid naïve children. The tentative identities of these compounds are octanal and dodecane/tetradecane respectively. These candidate biomarkers have a potential to enable non-invasive diagnosis of EIB in steroid-naïve children. Trial registration This study is registered in the Netherlands trial register (trial no. NL6087) at 14 February 2017.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.004 | 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".