Reliability and clinical relevance of impulse oscillometry in smokers with and without airflow obstruction
Bibliographic record
Abstract
Background: The test-retest reliability of impulse oscillometry (IOS) as a measure of small airway function and its link with clinical outcomes in smokers with mild COPD is unknown. Aims: 1) Assess the test-retest reliability of IOS, and 2) Test the associations of IOS and other key pulmonary function tests (PFTs) with peak oxygen uptake (V̇O2peak) and activity-related dyspnea (modified Medical Research Council (mMRC) dyspnea scale). Methods: Tri-centre, observational study where non-smoking healthy controls (n=27), smokers without airflow obstruction (n=21), and those with spirometric GOLD Stage 1 COPD (n=37) repeated IOS and standard PFTs over 2 visits (interval=35±56 days) and completed an incremental cycle exercise test. IOS test-retest reliability was assessed by intraclass correlation coefficient (ICC). Results: Controls (FEV1=112±16%pr), smokers without airflow obstruction (FEV1=101±14%pr), GOLD 1A (FEV1=93±11%pr), and GOLD 1B (FEV1=87±9%pr) were matched for age, height, and body mass index. All IOS parameters had excellent test-retest reliability (ICC>0.9). IOS metrics of frequency dependence of resistance (R5-R20; a measure of small airway function) (r=-0.20, p=0.04), and reactance at 5Hz (X5; an index of lung stiffness) (r=0.25, p=0.02) weakly correlated with V̇O2peak. No IOS metrics correlated with mMRC (all p>0.05). Of all PFTs, diffusing capacity for carbon monoxide was the only metric that had a strong correlation with both V̇O2peak (r=0.27, p=0.01) and mMRC (r=0.55, p<0.01). Conclusions: IOS components had excellent test-retest reliability, but were only weakly associated with exercise limitation in smokers with minor spirometric abnormalities.
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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 | 0.005 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".