Uses of high-flow nasal cannula on the community paediatric ward and risk factors for deterioration
Bibliographic record
Abstract
BACKGROUND: High-flow nasal cannula (HFNC) is a form of noninvasive respiratory support used for paediatric acute respiratory illnesses. Past HFNC research has focused on its use in bronchiolitis and in intensive care units, but little is reported on its use in the community hospital setting. We aimed to investigate the paediatric population using HFNC, any adverse events, and risk factors for deterioration. METHODS: A retrospective chart review was performed on patients admitted to a community paediatric ward. Inclusion criteria were patients between 1 day and 17 years of age, admitted between September 2013 and April 2016, and treated with HFNC for at least 4 hours. RESULTS: A total of 85 children met inclusion criteria. The average age of patients in our study was 3.41 years with 39% of patients >2 years of age. 46% of patients had an admitting diagnosis of bronchiolitis, 33% pneumonia, and 16% with asthma. Transfer rate to tertiary care centre paediatric intensive care unit was 18%. Patients transferred required greater FIO2 (odds ratio [OR] 1.04, P=0.018, confidence interval [CI] 1.007 to 1.082), and were 3.2 times more likely to be positive for respiratory syncytial virus (RSV) (P=0.081, CI 0.868-11.739). There were no adverse events attributed to HFNC in the population. CONCLUSION: HFNC is being utilized in the community hospital setting for children of varied age and types of respiratory illnesses. Children requiring higher FIO2 are at risk of respiratory deterioration which may identify them earlier for transfer to tertiary care. Further research into the safety and efficacy of HFNC for different paediatric illnesses in the community is 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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".