Paediatrics: how to manage acute respiratory distress syndrome
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it