Combination Therapy of Inhaled Corticosteroids and Long-Acting β2- Adrenergics In Management of Patients with Chronic Obstructive Pulmonary Disease
Bibliographic record
Abstract
Chronic obstructive pulmonary disease (COPD) affects over 5% of the adult population and is the only major cause of death in the United States where morbidity and mortality are increasing. Clinically, COPD is characterized by irreversible airflow obstruction and airway inflammation that eventually lead to dyspnea, cough and sputum production. Long-acting beta(2)-agonists (LABAs) are effective in reducing patient symptoms through their bronchodilatory action on airway smooth muscle. More importantly, when LABAs are given in conjunction with inhaled corticosteroids, they appear to provide added benefits for patients. While the mechanisms for this observation are not entirely clear, there is emerging evidence to indicate that LABAs and corticosteroids attenuate different but complementary components of the inflammatory cascade related to COPD. Moreover, LABAs and corticosteroids may beneficially interact to prevent downregulation of beta(2)-receptors in airway cells (and thereby preventing tachyphylaxis) and to facilitate translocation of glucocorticoid receptors into the nucleus of inflammatory cells (thereby, amplifying the anti-inflammatory activity of the corticosteroid). Regardless of the mechanism, several large, high-quality randomized controlled clinical trials indicate that combination therapy of LABA with inhaled corticosteroids improves patient symptoms, and reduces exacerbations by a third (compared to placebo). More importantly, combination therapy produces superior health outcomes than mono-therapy with inhaled corticosteroids or LABA, suggesting added clinical benefits of these two compounds in COPD. This article will present a comprehensive overview of the currently available clinical evidence for the use of combination therapy as well as the potential mechanisms of their actions in COPD.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".