Systematic review and cost‐utility of high flow nasal cannula versus continuous positive airway pressure in children with acute severe or moderate bronchiolitis in Colombia
Bibliographic record
Abstract
BACKGROUND: Nasal Continuous Positive Airway Pressure (CPAP) and High-Flow Nasal Cannula (HFNC) have emerged as alternatives to orotracheal intubation and conventional invasive ventilation in patients with moderate to severe bronchiolitis. This study aims to evaluate the evidence and the cost-utility of HFNC compared to CPAP in infants with moderate-severe bronchiolitis in Colombia. METHODS: The search includes electronic databases such as Pubmed, ScienceDirect, and Embase. Through inclusion and exclusion criteria, screen randomized controlled trials. A decision tree model was used to estimate the cost-utility of CPAP compared with HFNC in infants with moderate-severe bronchiolitis. Sensitivity analysis of transition probabilities, utilities, and cost was carried out. RESULTS: = 0%) The base-case analysis showed that compared with HFNC, CPAP was associated with lower costs and higher quality-adjusted life years (QALYs). The expected annual cost per patient with CPAP was US$17,574 and with HFNC was US$29,421. The QALYs per person estimated with CPAP were 0.92 and with HFNC was 0.91. This position of absolute dominance of CPAP (CPAP has lower costs and higher QALYs than HFNI) makes it unnecessary to estimate the incremental cost-utility ratio. CONCLUSIONS: CPAP is cost-effective, over the HFNC, in infants with severe-moderate bronchiolitis in Colombia. Our study provides evidence that should be used by decision-makers to improve clinical practice guidelines and should be replicated to validate their results in other countries.
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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 | 0.006 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.011 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".