β-Blockers in COPD
Bibliographic record
Abstract
Background Cardiovascular disease is a frequent comorbidity in patients with COPD. Many physicians, particularly pulmonologists, are reluctant to use β-adrenoceptor blocking agents (β-blockers) in patients with COPD, despite their proven effectiveness in preventing cardiovascular events. Methods The large (5,162 patients) phase III TONADO 1 and 2 studies assessed lung function and patient-reported outcomes in patients with moderate to very severe COPD receiving long-acting bronchodilator treatment across 1 year. This post hoc analysis characterized lung-function changes, patient-reported outcomes, and safety in the subgroup of patients receiving β-blockers in the studies. Results In total, 557 of 5,162 patients (11%) received β-blockers at baseline. Postbronchodilator FEV 1 at baseline was higher in the β-blocker group (1.470 L) compared with that in the no β-blocker group (1.362 L). As expected, patients receiving β-blockers had a more frequent history of cardiovascular comorbidities and medications. Lung function improved from baseline in patients with or those without β-blocker treatment, and no relevant between-group differences were observed in trough FEV 1 or trough FVC at 24 or 52 weeks. No relevant differences were observed for St. George's Respiratory Questionnaire results and Transition Dyspnea Index in patients with β-blockers compared with those in patients without. Safety findings were comparable between groups. Conclusions Lung function, overall respiratory status, and safety of tiotropium/olodaterol were not influenced by baseline β-blocker treatment in patients with moderate to very severe COPD. Results from this large patient cohort support the cautious and appropriate use of β-blockers in patients with COPD and cardiovascular comorbidity. Trial Registry ClinicalTrials.gov; No.: NCT01431274 and No. NCT01431287; URL: www.clinicaltrials.gov
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| 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".