European Respiratory Society guidelines on long-term home non-invasive ventilation for management of COPD
Bibliographic record
Abstract
BACKGROUND: While the role of acute non-invasive ventilation (NIV) has been shown to improve outcome in acute life-threatening hypercapnic respiratory failure in COPD, the evidence of clinical efficacy of long-term home NIV (LTH-NIV) for management of COPD is less. This document provides evidence-based recommendations for the clinical application of LTH-NIV in chronic hypercapnic COPD patients. MATERIALS AND METHODS: The European Respiratory Society task force committee was composed of clinicians, methodologists and experts in the field of LTH-NIV. The committee developed recommendations based on the GRADE (Grading, Recommendation, Assessment, Development and Evaluation) methodology. The GRADE Evidence to Decision framework was used to formulate recommendations. A number of topics were addressed under a narrative format which provides a useful context for clinicians and patients. RESULTS: The task force committee delivered conditional recommendations for four actionable PICO (target population-intervention-comparator-outcome) questions, 1) suggesting for the use of LTH-NIV in stable hypercapnic COPD; 2) suggesting for the use of LTH-NIV in COPD patients following a COPD exacerbation requiring acute NIV 3) suggesting for the use of NIV settings targeting a reduction in carbon dioxide and 4) suggesting for using fixed pressure support as first choice ventilator mode. CONCLUSIONS: Managing hypercapnia may be an important intervention for improving the health outcome of COPD patients with chronic respiratory failure. The task force conditionally supports the application of LTH-NIV to improve health outcome by targeting a reduction in carbon dioxide in COPD patients with persistent hypercapnic respiratory failure. These recommendations should be applied in clinical practice by practitioners that routinely care for chronic hypercapnic COPD 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 | 0.023 | 0.039 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.006 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.006 | 0.003 |
| Research integrity | 0.010 | 0.009 |
| Insufficient payload (model declined to judge) | 0.014 | 0.011 |
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".