Continuous positive airway pressure therapy suppresses inflammatory cytokines and improves glucocorticoid responsiveness in patients with obstructive sleep apnea and asthma
Bibliographic record
Abstract
CONTEXT: Asthma and obstructive sleep apnea (OSA) are prevalent respiratory disorders that frequently coexist. Continuous positive airway pressure (CPAP) therapy is the standard treatment for OSA. However, its effects on systemic inflammation and glucocorticoid responsiveness in OSA patients with asthma are largely unknown. AIMS: To examine the potential role of CPAP therapy in reducing systemic inflammation and improving glucocorticoid responsiveness in asthmatic patients with OSA. SETTINGS AND DESIGN: A case-control study was conducted at the respiratory and sleep clinics involving patients with OSA and patients with asthma and OSA. METHODS: The levels of inflammatory asthma biomarkers (interleukin [IL]-4, IL-17A, IL-8, IL-2, and interferon-γ [IFN-γ]), and glucocorticoid receptors (GR)-α and GR-β, were determined to compare systemic inflammation and glucocorticoid responsiveness between pre- and post-1-month CPAP treatment in both groups. STATISTICAL ANALYSIS: < 0.05 considered statistically significant. The analysis was performed using SPSS. RESULTS: = 23), had OSA with asthma. Interestingly, the blood levels of IL-17 and IL-8 were significantly decreased post-CPAP therapy in OSA patients, whereas IL-4, IL-17, and IFN-γ were significantly reduced post-CPAP treatment in OSA patients with asthma. Remarkably, CPAP therapy improved glucocorticoid responsiveness in asthmatic patients with OSA, but not in the OSA group and an increase in the GR-α/GR-β ratio was noted post-CPAP therapy. CONCLUSIONS: Continuous positive airway pressure therapy improved responsiveness to glucocorticoid treatment and demonstrated a suppressive effect on proinflammatory cytokines in asthmatics with OSA.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".