Paediatrics: how to manage acute respiratory distress syndrome
Bibliographic record
Abstract
BACKGROUND: Acute respiratory distress syndrome (ARDS) is a significant cause of mortality and morbidity amongst critically ill children. The purpose of this narrative review is to provide an up-to-date review on the evaluation and management of paediatric ARDS (PARDS). METHODS: A PubMed search was performed with Clinical Queries using the key term "acute respiratory distress syndrome". The search strategy included clinical trials, meta-analyses, randomized controlled trials, observational studies and reviews. Google, Wikipedia and UpToDate were also searched to enrich the review. The search was restricted to the English literature and children. DISCUSSION: Non-invasive positive pressure ventilation, lung-protective ventilation strategies, conservative fluid management and adequate nutritional support all have proven efficacy in the management of PARDS. The Pediatric Acute Lung Injury Consensus Conference recommends the use of corticosteroids, high-frequency oscillation ventilation and inhaled nitric oxide in selected scenarios. Partial liquid ventilation and surfactant are not considered efficacious based on evidence from clinical trials. CONCLUSION: PARDS is a serious but relatively rare cause of admission into the paediatric intensive care unit and is associated with high mortality. Non-invasive positive pressure ventilation, lung-protective ventilation strategies, conservative fluid management and adequate nutrition are advocated. As there has been a lack of progress in the management of PARDS in recent years, further well-designed, large-scale, randomized controlled trials in this field are urgently needed.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".