Systematic review of noninvasive positive pressure ventilation in severe stable COPD
Bibliographic record
Abstract
The present systematic review examined the effectiveness of bilevel noninvasive positive pressure ventilation (NIPPV) in the management of chronic respiratory failure (CRF) due to severe stable chronic obstructive pulmonary disease (COPD). Randomised controlled trials (RCTs) and non-RCTs (crossover design) of adults with severe stable COPD and CRF receiving bilevel NIPPV via nasal, oronasal or total face mask were identified from electronic databases and manual screening of journals and reference lists. Respiratory function (gas exchange, lung function, ventilatory/breathing pattern, respiratory muscle function and work of breathing) and health-related outcomes (dyspnoea, functional status, exercise tolerance, health-related quality of life (HRQOL), morbidity and mortality) were assessed. In total, 15 studies met the inclusion criteria: six RCTs and nine non-RCTs. RCTs did not find improved gas exchange with bilevel NIPPV, while non-RCTs did. Lung hyperinflation and diaphragmatic work of breathing were reduced in a nonrandomised subset. HRQOL and dyspnoea, the least studied outcomes, showed improvement with bilevel NIPPV. In a subset of individuals on maximal medical treatment regimes for severe stable chronic obstructive pulmonary disease, bilevel noninvasive positive pressure ventilation may have an adjunctive role in the management of chronic respiratory failure through attenuation of compromised respiratory function and improvement in health-related outcomes.
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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 | 0.005 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.004 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".