Obstructive sleep apnoea in patients with fibrotic diffuse parenchymal lung disease—characterization and treatment compliance assessment
Bibliographic record
Abstract
INTRODUCTION: Recent studies have reported a high prevalence of obstructive sleep apnoea (OSA) among patients with diffuse parenchymal lung disease (DPLD), mainly idiopathic pulmonary fibrosis (IPF). Effective OSA treatment appears to have a positive impact on morbidity and mortality in these patients. However, poor compliance to positive airway pressure (PAP) treatment in fibrotic DPLD patients has been reported. The aims of our study were to characterize patients with fibrotic DPLD and OSA and to assess their compliance to PAP treatment. METHODS: Forty-nine patients with fibrotic DPLD underwent level III polysomnography. Auto-adjusting PAP (APAP) treatment was proposed for those patients with moderate-to-severe OSA and those with mild OSA with daytime sleepiness and/or cardiovascular disease. The APAP treatment compliance was assessed after 1 month of therapy. RESULTS: The distribution of the 49 fibrotic DPLD patients included was as follows: 21 with chronic hypersensitivity pneumonitis, 12 with IPF, 10 with connective-tissue associated DPLD, 4 with stage IV sarcoidosis, 1 with idiopathic pleuropulmonary fibroelastosis, and 1 with DPLD-associated vasculitis. Thirty-four (69.4%) of the patients presented with OSA; 22 had mild OSA, and 12 had moderate-to-severe OSA. APAP treatment was prescribed in 17 of the patients. After 1 month of therapy, all patients used APAP more than 70% of the nights for more than 4 h per night. CONCLUSION: We found a high prevalence of OSA among all of the patients with fibrotic DPLD (not only IPF). Despite certain difficulties, it was possible to achieve good APAP compliance in these patients.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".