Paediatric reproducibility limits for the forced expiratory volume in 1 s
Bibliographic record
Abstract
BACKGROUND: Current reproducibility standards for spirometry were derived using a small adult dataset and may not be optimal for interpretation of repeated measurements of lung function in children. OBJECTIVE: ) change that represent the normal within-subject between-visit variability in healthy children and evaluate these limits as a tool to monitor children with cystic fibrosis (CF). METHODS: measurements (3 months to 5 years apart) from healthy children from the Global Lung Function Initiative data repository were used to derive a conditional change score. Spirometry and clinical data from a CF clinical database was used to verify utility in clinical practice. RESULTS: measures from 7885 healthy children 6-18 years of age. The simple algorithm, which is conditional on the initial measurement, also accounts for age and time interval between measurements. The change score limits of reproducibility were much narrower than currently used cut-offs. Specifically, changes, considered as improvements using either a 12% or 10% relative change from baseline, are too wide for children. In CF, there was overall agreement between different approaches, with the distinct advantage that the change score was not biased by regression to the mean. CONCLUSIONS: Compared with current approaches to interpretation of repeated lung function measurements, the proposed change score was less biased and provides a simple alternative to reduce misinterpretation.
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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 | 0.064 | 0.114 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".