Can we use pre-bronchodilator spirometry to define post-bronchodilator airflow obstruction?
Bibliographic record
Abstract
COPD definition requires post-bronchodilator (BD) spirometry. In epidemiological studies where post-BD spirometry was not performed, COPD is generally defined using pre-BD spirometry. However, the extent of misclassification in this definition is unknown. Using the data of 3,332 subjects who underwent spirometry both in the European Community Respiratory Health Survey II (pre-BD) (1999/2001) and III (pre + post-BD) (2010/2014), we assessed the validity of a definition of pre-BD “chronic” (present at both ECRHS II and III) airflow obstruction, towards post-BD (“fixed”) obstruction at ECRHS III (the gold standard). Airflow obstruction was defined as FEV1/FVC Subjects were 54.1±7.1 year-old at baseline, 53% were women. Chronic and fixed obstruction were present in 163 (4.9%) and 188 (5.6%) individuals, respectively. Subjects who had obstruction according to both definitions (n=136) were more likely to be smokers (73 vs 54%) and to have asthma (62 vs 19%) than subjects without chronic/fixed obstruction (n=3,117) (both p<0.002). The definition of chronic obstruction had sensitivity=83.4% [95%CI] (76.8-88.8%), specificity=98.4% (97.9-98.8%), positive predictive value=72.3% (65.4-78.6%), and negative predictive value=99.1% (98.8-99.4%). Sensitivity was higher in subjects with a history of asthma (92.3 vs 72.2%) than in subjects without, and the opposite was true for specificity (94.8 vs. 99.2%, respectively) (both p<0.001). Predictive values were similar between subjects with/without asthma (p>0.05). In young adults, pre-BD airflow obstruction confirmed at two occasions 9 years apart correctly identified the large majority of subjects with post-BD airflow obstruction.
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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 | 0.106 | 0.233 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.007 | 0.011 |
| Open science | 0.008 | 0.003 |
| Research integrity | 0.008 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".