Consequences of Changing the GOLD Reports (2007–2011–2017) on the Treatment Regimen of Patients with COPD
Bibliographic record
Abstract
Detailed treatment regimens for patients with chronic obstructive pulmonary disease (COPD) were developed by the Global Initiative for Chronic Obstructive Lung Disease (GOLD). Every few years the method of classification of COPD severity and the treatment recommendations are significantly revised. The aim of this study was to determine the clinical implications of changing GOLD reports (2007–2011–2017) and the impact that these changes would have on pharmacological treatment regimens of patients with COPD. A group of 500 randomly chosen primary care physicians in Poland each provided information on 10 consecutive patients diagnosed with COPD. This data was used to simulate the therapeutic consequences of the update of the GOLD 2007 report to GOLD 2011 and GOLD 2017. Pharmacological treatment algorithms from the GOLD 2007 report prefer the use of inhaled corticosteroids (ICS) and short-acting bronchodilators (60.2% and 50%, respectively). Compared to the GOLD 2007 report, there would be an almost eightfold reduction in the frequency of short-acting bronchodilator using the GOLD 2011 report and over fourfold decrease using the GOLD 2017 report. With each subsequent update of the GOLD report, the frequency of use of ICS would be significantly (p < 0.001) reduced. Pharmacological treatment by the GOLD 2011 and 2017 reports would be dominated by the use of long-acting bronchodilators from the group β2-agonists and muscarinic antagonist groups. Updates from the GOLD 2007 COPD report to GOLD 2011 and 2017 would have a significant impact on everyday clinical practice. Changes would result in a reduction of treatment intensity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.038 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".