Characterising patients with COPD by baseline short-acting β2-agonist (SABA) use: a post hoc analysis of the EMAX trial
Bibliographic record
Abstract
Claus Vogelmeier is presenting the data in German on behalf of all the authors with their permissions. The abstract was originally presented at the European Respiratory Society 2020 Virtual Meeting. Sep 5 – 9, 2020. European Respiratory Journal. 2020;56 : 982. Background: Patients with COPD vary in their use of SABA medication; but it is not clear which patient characteristics are associated with high or low baseline SABA use. The aim is to investigate patient characteristics associated with high and low baseline SABA use in the EMAX trial. Methods: This post hoc analysis compared baseline characteristics for patients with high (≥ 4 puffs/day) versus low (< 4 puffs/day) baseline SABA use using a t -test for continuous variables and Fisherʼs exact test for categorical variables. Results: Aside from sex (p = 0.181) and exacerbation history in the prior year (p = 0.284), all assessed baseline characteristics were significantly different between the high and low SABA user subgroups (p < 0.001). A greater proportion of high SABA users were maintenance naïve and had more severe disease, higher symptom burden and more severe airflow limitation than low SABA users ([ Table 1 ]). Tab. 1 Characteristic SABA use < 4 puffs/day (N = 1975) SABA use ≥ 4 puffs/day (N = 443) p-value Age (years), means (SD) 65.1 (8.5) 62.7 (8.2) < 0.001 Female, n (%) 790 (40) 193 (44) 0.181 Duration COPD (years), mean (SD) 8.1 (6.6) 9.2 (6.3) < 0.001 Maintenance naive, n (%) 539 (27) 209 (47) < 0.001 Trough FEV 1 (mL), mean (SD) 1520 (516) 1362 (502) < 0.001 Post-BD % predicted FEV 1 , mean (SD) 56.3 (12.6) 51.7 (12.8) < 0.001 GOLD grade, n (%) Grade 2 (moderate) 1336 (68) 229 (52) < 0.001 Grade 3 (severe) 634 (32) 214 (48) < 0.001 CAT score, mean (SD) 18.5 (5.8) 22.3 (6.7) < 0.001 SAC BDI focal score, mean (SD) 7.1 (1.8) 6.4 (2.1) < 0.001 E-RS total score, mean (SD) 9.8 (5.3) 14.2 (6.0) < 0.001 SGRQ total score, mean (SD) 43.0 (15.5) 52.1 (16.8) < 0.001 1 moderate COPD exacerbation history in prior year, n (%) 311 (16) 79 (18) 0.284 Conclusion: High SABA use is a marker of worse lung function, symptom severity and health status compared with low SABA use. Publication History Article published online: 30 April 2021 © 2021. Thieme. All rights reserved. Georg Thieme Verlag KG Rüdigerstraße 14, 70469 Stuttgart, Germany
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".