Clinical Relevance of Fixed Ratio vs Lower Limit of Normal of FEV1/FVC in COPD: Patient-Reported Outcomes From the CanCOLD Cohort
Bibliographic record
Abstract
PURPOSE: The way in which spirometry is interpreted can lead to misdiagnosis of chronic obstructive pulmonary disease (COPD) resulting in inappropriate treatment. We compared the clinical relevance of 2 criteria for defining a low ratio of forced expiratory volume in 1 second to forced vital capacity (FEV1/FVC): the fixed ratio and the lower limit of normal. METHODS: We analyzed data from the cross-sectional phase of the population-based Canadian Cohort of Obstructive Lung Disease (CanCOLD) study. We determined associations of the spirometric criteria for airflow limitation with patient-reported adverse outcomes, including respiratory symptoms, disability, health status, exacerbations, and cardiovascular disease. Sensitivity analyses were used to explore the impact of age and severity of airflow limitation on these associations. RESULTS: We analyzed data from 4,882 patients aged 40 years and older. The prevalence of airflow limitation was 17% by fixed ratio and 11% by lower limit of normal. Patients classified as having airflow limitation by fixed ratio only had generally small, nonsignificant increases in the odds of adverse outcomes. Patients having airflow limitation based on both fixed ratio and lower limit of normal had larger, significant increases in odds. But strongest associations were seen for patients who had airflow limitation by both fixed ratio and lower limit of normal and also had a low FEV1, defined as one less than 80% of the predicted value. CONCLUSIONS: Our results suggest that use of the fixed ratio alone may lead to misdiagnosis of COPD. A diagnosis established by both a low FEV1/FVC (according to fixed ratio and/or lower limit of normal) and a low FEV1 is strongly associated with clinical outcomes. Guidelines should be reconsidered to require both spirometry abnormalities so as to reduce overdiagnosis of COPD.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".