GOLD Science Committee recommendations for the use of pre- and post-bronchodilator spirometry for the diagnosis of COPD
Bibliographic record
Abstract
The Global Initiative for Chronic Obstructive Lung Disease (GOLD) report states that the diagnosis of COPD should be considered in individuals with chronic respiratory symptoms and/or exposure to risk factors. Forced spirometry demonstrating airflow obstruction after bronchodilation is required to confirm the diagnosis using a threshold of forced expiratory volume in 1 s (FEV 1 )/forced vital capacity (FVC) ratio <0.7. This GOLD Science Committee review weighs the evidence for using pre- or post-bronchodilator (BD) spirometry to diagnose COPD. Cohort studies have shown that pre- and post-BD spirometry give concordant diagnostic results in most cases, although the prevalence of COPD is up to 36% lower with post-BD values. Discordant results may occur in “volume” or “flow” responders. Volume responders have reduced FVC due to gas trapping causing FEV 1 /FVC ≥0.7 pre-BD, but a volume response occurs post-BD with a greater improvement in FVC relative to FEV 1 decreasing the ratio to <0.7. Flow responders show a greater FEV 1 improvement relative to FVC which may increase FEV 1 /FVC from <0.7 pre-BD to ≥0.7 post-BD; these individuals have an increased likelihood of developing post-BD obstruction during follow-up and require monitoring longitudinally. GOLD 2025 recommends using pre-BD spirometry to rule out COPD and post-BD measurements to confirm the diagnosis. This will reduce clinical workload. Post-BD results close to the threshold should be repeated to ensure a correct diagnosis is made. Post-BD measurements ensure that volume responders are not overlooked and limit COPD overdiagnosis.
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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 | 0.073 | 0.138 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.011 |
| Bibliometrics | 0.008 | 0.004 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.012 | 0.004 |
| Research integrity | 0.015 | 0.010 |
| Insufficient payload (model declined to judge) | 0.012 | 0.015 |
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".