Is there a role for humidified heated high-flow nasal cannula therapy in paediatric emergency departments?
Bibliographic record
Abstract
BACKGROUND: Humidified heated high-flow nasal cannula (HFNC) therapy is a potentially useful form of non-invasive respiratory support for children with moderate respiratory distress and/or hypoxaemia. No prospective data support its use in the paediatric emergency department (ED). We introduced HFNC therapy into a paediatric ED and evaluated its use and failure rates. METHODS: Prospective observational study of all patients presenting to the Royal Children's Hospital, Australia, who received HFNC therapy between April 2013 and September 2013 (one southern hemisphere winter season). We assessed demographics, indications, failure rate, predictors of failure and adverse events. RESULTS: 71 patients commenced HFNC therapy in ED over the study period. The median age was 9 months. The most common indication was bronchiolitis (49/71; 69%). Five (7%) of the patients failed HFNC and were escalated to other forms of respiratory support in ED, four to nasal continuous positive airway pressure and one required intubation. A further 21 (32%) failed HFNC therapy after intensive care unit (ICU) admission, giving a total failure of 28 (39%). There were no serious adverse events in ED, and one child with asthma developed air leak syndrome after transfer to the ICU. CONCLUSIONS: HFNC therapy may have a role in the paediatric ED as an easily administered and well tolerated form of non-invasive respiratory support, but about one-third of patients required escalation to a higher level of respiratory support. Further studies should assess the safety profile of HFNC in larger series, and define the role of HFNC in key respiratory conditions compared with other possible interventions.
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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 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".