The utility of moment ratios and abbreviated endpoints of the multiple breath washout test in preschool children with cystic fibrosis
Bibliographic record
Abstract
Abstract Background The multiple breath washout (MBW) test may be most useful in tracking disease progression over time to inform treatment decisions. In the clinical setting, alternative outcomes, which can be obtained quickly and easily, may facilitate interpretation of clinically relevant changes in lung function. Methods In this secondary analysis of data from 78 cystic fibrosis (CF) and 72 healthy control (HC) subjects between the ages of 2.6 and 5.9 years, MBW was performed at enrollment, 1, 3, 6, 9, and 12 months, as well as during symptomatic visits using the Exhalyzer D (EcoMedics AG, Duernten, Switzerland). The lung clearance index, LCI2.5, was compared to moment ratios (M1/M0 and M2/M0) at the standard cutoff (1/40th of starting tracer gas concentration) as well as LCI5 and moment ratios at 1/20th of the starting concentration (M1/M0 at LCI5, and M2/M0 at LCI5). Results All outcomes were able to distinguish between health and disease. LCI5 reduced testing time by 40% and increased feasibility by more than 10%. The limits of biological reproducibility in healthy children were similar between LCI2.5 (15%), LCI5 (12%), M1/M0 at LCI2.5 (14%), and M1/M0 at LCI5 (12%), but markedly larger for M2/M0 at LCI2.5 (30%) and M2/M0 at LCI5 (25%). Each outcome deteriorated significantly with worsening pulmonary symptoms, the magnitude of deterioration was greatest for M2/M0. Conclusions In preschool children with CF, LCI5 was more feasible to obtain and track disease progression. The second moment ratio was most sensitive to pulmonary symptoms, but had the greatest variability both within and between subjects.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".