Effects of inhaled corticosteroids on airway inflammation in chronic obstructive pulmonary disease: a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Chronic obstructive pulmonary disease (COPD) is characterized by chronic inflammation in the small airways. The effect of inhaled corticosteroids (ICS) on lung inflammation in COPD remains uncertain. We sought to determine the effects of ICS on inflammatory indices in bronchial biopsies and bronchoalveolar lavage fluid of patients with COPD. METHODS: We searched Medline, Embase, Cinahl, and the Cochrane database for randomized, controlled clinical trials that used bronchial biopsies and bronchoalveolar lavage to evaluate the effects of ICS in stable COPD. For each chosen study, we calculated the mean differences in the concentrations of inflammatory cells before and after treatment in both intervention and control groups. These values were then converted into standardized mean differences (SMD) to accommodate the differences in patient selection, clinical treatment, and biochemical procedures that were employed across the original studies. If significant heterogeneity was present (P < 0.1), then a random effects model was used to pool the original data; otherwise, a fixed effects model was used. RESULTS: We identified eight original studies that met the inclusion criteria. Four studies used bronchial biopsies (n =102 participants) and showed that ICS were effective in reducing CD4 and CD8 cell counts (SMD, -0.52 units and -0.66 units, 95% confidence interval). The five studies used bronchoalveolar lavage fluid (n =309), which together showed that ICS reduced neutrophil and lymphocyte counts (SMD, -0.64 units and -0.64 units, 95% confidence interval). ICS on the other hand significantly increased macrophage counts (SMD, 0.68 units, 95% confidence interval) in bronchoalveolar lavage fluid. CONCLUSION: ICS has important immunomodulatory effects in airways with COPD that may explain its beneficial effect on exacerbations and enhanced risk of pneumonia.
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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 | 0.014 | 0.032 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.023 | 0.035 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".