Respiratory impedance in children with cystic fibrosis using forced oscillations in clinic
Bibliographic record
Abstract
Measurement of lung function is an important component of clinical management in cystic fibrosis (CF), but has been difficult in young children. The present study aimed to characterise the utility of the forced oscillation technique for measurement of lung function in preschool-aged children with CF in a routine clinical setting. Lung function was assessed in 56 young children (aged 2-7 yrs) with CF. Respiratory system resistance (R(rs)) and reactance (X(rs)) at 6, 8 and 10 Hz were measured and expressed as Z-scores. Children were classified as asymptomatic or symptomatic based on an administered respiratory questionnaire and physical examination at the time of testing. Between-test repeatability was assessed in 25 children. Measurement of lung function using the forced oscillation technique was feasible in the CF clinic. The children with CF, as a group, had Z-scores for R(rs) at 6 Hz (R(rs,6)) R(rs,8), R(rs,10), X(rs) at 6 Hz (X(rs,6)) and X(rs,8) that were significantly different from zero. Children with current symptoms showed significantly decreased X(rs) and increased R(rs,6) compared with asymptomatic children. Measurement of lung function using the forced oscillation technique is feasible in young children with cystic fibrosis in a clinical setting. The technique has the potential to improve knowledge concerning early cystic fibrosis lung disease.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.001 | 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".