Variation in Practice Related to the Use of High Flow Nasal Cannula in Critically Ill Children
Bibliographic record
Abstract
OBJECTIVES: To determine current management of critically ill children and gather views regarding high flow nasal cannula therapy and to evaluate research priorities for a large prospective randomized controlled trial of noninvasive respiratory support in children. DESIGN: Multinational cross-sectional questionnaire survey conducted in 2018. SETTING: The sample included pediatric intensive care physicians in North and South America, Asia, Europe, and Australia/New Zealand. MEASUREMENT: Questions consisted of: 1) characteristics of intensivists and hospital, 2) practice of high flow nasal cannula, 3) supportive treatment, and 4) research of high flow nasal cannula. INTERVENTIONS: None. MAIN RESULTS: We collected data from 1,031 respondents; 919 (North America, 215; Australia/New Zealand, 34; Asia, 203; South America, 186; Europe, 281) were analyzed. Sixty-nine percent of the respondents used high flow nasal cannula in non-PICU settings in their institutions. For a case of bronchiolitis/pneumonia infant, 2 L/kg/min of initial flow rate was the most commonly used. For a scenario of pneumonia with 30 kg weight, more than 60% of the respondents initiated flow based on patient body weight; while, 18% applied a fixed flow rate. Noninvasive ventilation was considered as a next step in more than 85% of respondents when the patient is failing with high flow nasal cannula. Significant practice variations were observed in clinical practice markers used, flow weaning strategy, and supportive practices. Views comparing high flow nasal cannula to continuous positive airway pressure also noticeably varied across the respondents. CONCLUSIONS: Significant practice variations including views of high flow nasal cannula compared to continuous positive airway pressure was found among pediatric intensive care physicians. To expedite establishment and standardization of high flow nasal cannula practice, research aimed at understanding the heterogeneity found in this study should be undertaken.
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How this classification was reachedexpand
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 | 0.041 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".