Pre-hospital non-invasive ventilation for acute respiratory failure: a systematic review and cost-effectiveness evaluation
Bibliographic record
Abstract
BACKGROUND: Non-invasive ventilation (NIV), in the form of continuous positive airway pressure (CPAP) or bilevel inspiratory positive airway pressure (BiPAP), is used in hospital to treat patients with acute respiratory failure. Pre-hospital NIV may be more effective than in-hospital NIV but requires additional ambulance service resources. OBJECTIVES: We aimed to determine the clinical effectiveness and cost-effectiveness of pre-hospital NIV compared with usual care for adults presenting to the emergency services with acute respiratory failure and to identify priorities for future research. DATA SOURCES: Fourteen electronic databases and research registers (including MEDLINE In-Process & Other Non-Indexed Citations, MEDLINE, EMBASE, and Cumulative Index to Nursing and Allied Health Literature) were searched from inception to August 2013, supplemented by hand-searching reference lists and contacting experts in the field. REVIEW METHODS: We included all randomised or quasi-randomised controlled trials of pre-hospital NIV in patients with acute respiratory failure. Methodological quality was assessed according to established criteria. An aggregate data network meta-analysis (NMA) of mortality and intubation was used to jointly estimate intervention effects relative to usual care. A NMA, using individual patient-level data (IPD) and aggregate data where IPD were not available, was carried out to assess whether or not covariates were treatment effect modifiers. A de novo economic model was developed to explore the costs and health outcomes when pre-hospital NIV (specifically CPAP provided by paramedics) and standard care (in-hospital NIV) were applied to a hypothetical cohort of patients with acute respiratory failure. RESULTS: The literature searches identified 2284 citations. Of the 10 studies that met the inclusion criteria, eight were randomised controlled trials and two were quasi-randomised trials (six CPAP; four BiPAP; sample sizes 23-207 participants). IPD were available from seven trials (650 patients). The aggregate data NMA suggested that CPAP was the most effective treatment in terms of mortality (probability = 0.989) and intubation rate (probability = 0.639), and reduced both mortality [odds ratio (OR) 0.41, 95% credible interval (CrI) 0.20 to 0.77] and intubation rate (OR 0.32, 95% CrI 0.17 to 0.62) compared with standard care. The effect of BiPAP on mortality (OR 1.94, 95% CrI 0.65 to 6.14) and intubation rate (OR 0.40, 95% CrI 0.14 to 1.16) compared with standard care was uncertain. The combined IPD and aggregate data NMA suggested that sex was a statistically significant treatment effect modifier for mortality. The economic analysis showed that pre-hospital CPAP was more effective and more expensive than standard care, with an incremental cost-effectiveness ratio of £20,514 per quality-adjusted life-year (QALY) and a 49.5% probability of being cost-effective at the £20,000-per-QALY threshold. Variation in the incidence of eligible patients had a marked impact on cost-effectiveness and the expected value of sample information for a future randomised trial. LIMITATIONS: The meta-analysis lacked power to detect potentially important differences in outcome (particularly for BiPAP), the intervention was not always compared with the best alternative care (in-hospital NIV) in the primary studies and findings may not be generalisable. CONCLUSIONS: Pre-hospital CPAP can reduce mortality and intubation rates, but cost-effectiveness is uncertain and the value of further randomised evaluation depends on the incidence of suitable patients. A feasibility study is required to determine if a large pragmatic trial of clinical effectiveness and cost-effectiveness is appropriate. STUDY REGISTRATION: The study is registered as PROSPERO CRD42012002933. FUNDING: The National Institute for Health Research Health Technology Assessment programme.
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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 | 0.017 | 0.054 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.018 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".