Effects of Corticosteroids on Systemic Inflammation in Chronic Obstructive Pulmonary Disease
Bibliographic record
Abstract
Patients with chronic obstructive pulmonary disease (COPD) are predisposed to atherosclerosis and coronary artery disease, but the underlying mechanisms are unclear. Although there is wide acceptance that atherosclerosis is related to systemic inflammation, the cause(s) and mechanism(s) of pulmonary inflammation in stable COPD remain unknown. Infectious (bacterial and viral) as well as noninfectious agents can cause acute exacerbations in COPD, and they intensify local and systemic inflammation. Although it is not known how systemic inflammation develops in stable COPD, there is good evidence to suggest that it occurs and that the intensity of systemic inflammation is linked to the severity of airflow obstruction. We postulate that systemic inflammation provides the linkage between COPD and atherosclerosis. Inhaled corticosteroids have been shown to improve health outcomes in COPD, but the mechanism by which this occurs is a pivotal and challenging question that has yet to be answered. To prove the concept that inhaled corticosteroids could suppress systemic inflammation (as exemplified by serum C-reactive protein [CRP] levels), a double-blind, placebo-controlled clinical trial was conducted in a group of patients with mild to moderate COPD. We found that withdrawal of inhaled corticosteroids increased serum CRP levels, and that reintroduction of inhaled fluticasone could suppress CRP levels.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".