Natural History of Spirometric or Oscillometric Abnormalities in Asymptomatic adults within the general population
Bibliographic record
Abstract
Aims: To assess the relationship of abnormal spirometry/oscillometry in asymptomatic individuals to the development of respiratory symptoms or disease diagnoses four years later. Methods: 2,451 Austrian LEAD study participants (mean age = 48.1±17.1 years, 54% female) without self-reported respiratory symptoms and diagnoses underwent two visits 4.2±0.4 years apart. Subjects were divided according to having normal or abnormal lung mechanics. Normal respiratory mechanics was defined as FVC, FEV1, FEV1/FVC, resistance, reactance (Xrs), inspiratory/expiratory components at 5Hz, and the area above the Xrs curve within the normal limits (GLI and Oostveen et al., 2013) at the first visit. Odds ratios (OR) and 95% confidence intervals (CI) assess the association between abnormal parameters at the first visit and self-reported respiratory conditions at the second. Results: Four years later: a) 1,688(68.9%) subjects remained symptom-free, 686(28.0%) reported symptoms, and 77(3.1%) reported being diagnosed with asthma, COPD, or chronic bronchitis. b) Subjects with normal FEV1/FVC (OR=0.53, 95%CI=0.38-0.75), normal Xrs (OR=0.55, 95%CI=0.34-0.87), were more likely to remain symptom-free. c) Subjects with abnormal Xrs (OR=1.60, 95%CI=1.00-2.57) were more likely to develop respiratory symptoms without a doctor’s diagnosed respiratory condition. d) Subjects with abnormal FEV1/FVC (OR=6.19, 95%CI=3.67-10.43) were more likely to report a doctor’s diagnosed respiratory condition. Conclusions: Spirometric and oscillometric abnormalities in asymptomatic individuals were associated with an increased risk of developing respiratory symptoms or conditions within four years.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 | 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".