The Potential of Heliox as a Therapy for Acute Respiratory Distress Syndrome in Adults and Children: A Descriptive Review
Bibliographic record
Abstract
BACKGROUND: In neonatal respiratory distress syndrome (RDS) and acute RDS (ARDS) mechanical ventilation is often necessary to manage hypoxia, whilst protecting the lungs through lower volume ventilation and permissive hypercapnia. Mechanical ventilation can, however, induce or aggravate the lung injury caused by the respiratory distress. Helium, in a gas mixture with oxygen (heliox), has a low density and can reduce the flow in narrow airways and allow for lower driving pressures. OBJECTIVES: The aim of this study was to review preclinical and clinical studies of the use of heliox ventilation in acute lung injury associated with respiratory failure. METHODS: A systematic search was executed in the PubMed and EMBASE databases, with search terms referring to ARDS or an acute lung injury condition associated with respiratory failure and the corresponding intervention. RESULTS: A total of 576 papers were retrieved. After the majority had been excluded 20 papers remained, of which 6 articles described animal models (3 paediatric; 3 adult animal models) and 14 were clinical studies, of which 12 described paediatric patient populations and 2 adult patient populations. In both paediatric and adult animal models, heliox improved gas exchange while allowing for less invasive ventilation in a wide variety of models using different ventilation modes. Clinical studies show a reduction in the work of breathing during heliox ventilation, with a concomitant increase in pH and decrease in PaCO2 levels compared to oxygen ventilation. CONCLUSIONS: Although evidence so far is limited, there may be a rationale for heliox ventilation in ARDS as an intervention to improve ventilation and reduce the work of breathing.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| 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".