Validation of multiple breath washout technology in healthy children and children with CF
Bibliographic record
Abstract
Mass spectrometry based technology is considered the “gold standard” for measuring LC, but is not readily available. In this ongoing study we aim to validate a nitrogen washout system for use in CF children. In a cross-over design, healthy and clinically stable CF children performed MBW by mass spectrometry (AMIS 2000; Innovision A/S, Odense, Denmark) using 4% SF6 or by nitrogen washout (Exhalyzer D, Eco Medics AG, Switzerland). Results were independently scored by two operators; Bland-Altman plots were used to assess the agreement between the two systems. To date 24 healthy children (median age 11 years (range 3-17)) and 33 children with CF (median age 11 years (range 3-17) completed MBW measurements using both the mass spectrometry and N 2 washout. There was no systematic bias observed in LCI between the two methods. Overall there was good agreement healthy children (95% of all measurements agreed within –0.44; 0.83); however LCI SF6 was systematically 0.2 (95% CI 0.06; 0.33) units lower than LCI N2 . The mean difference between the two systems was greater in children with CF (0.4 (CI 0.29 to 0.55) and the limits of agreement were wider (-0.33; 1.17). Agreement between the two methods for moment ratios was better for the M1M0 (-0.43; 0.63) than M2M0 (-5.72; 8.60), and greater in healthy children compared with children with CF. Inter-observer agreement for nitrogen washout was high (-0.08; 0.08) for all outcomes. These data suggest that while there is no systematic bias between the two systems, LCI measured by nitrogen washout is higher compared to LCI measured by mass spectrometry. Inter-observer variability is low for nitrogen washout if analyzed by trained operators. Supported by CFF.
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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 | 0.015 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".