Treatment of severe bronchiolitis: A survey of Canadian pediatric intensivists
Bibliographic record
Abstract
OBJECTIVE: To describe management practices and the factors guiding admission and treatment decisions for viral bronchiolitis across Canadian pediatric intensive care units (PICUs). DESIGN: Cross-sectional survey. SETTING: Canadian PICUs. SUBJECTS: Pediatric intensivists. MEASUREMENTS AND MAIN RESULTS: A survey using two case scenarios (non-intubated vs intubated patients) was developed using focus groups and a literature review. We analyzed our results using descriptive statistics and multivariate logistic regression. Our response rate was 55% (57/103). Regarding bronchiolitis management, 75% (42/56) of respondents would use inhaled therapies, with nebulized epinephrine (33/56, 59%) and salbutamol (20/56, 36%) being the most common. Antibiotic use within the first hour of admission to PICU almost doubled in frequency (36% vs 71%) in patients who required mechanical ventilation (p 0.0004). High flow nasal cannula (HFNC; 32/56, 57%) and continuous positive airway pressure (CPAP; 16/56, 29%) were the preferred modes of non-invasive ventilation (NIV). CONCLUSION: The management of severe viral bronchiolitis is similar across Canadian PICUs. The use of NIV, inhaled treatments, and antibiotics is frequent, which differs from the recommendations made by published guidelines. Canadian pediatric intensivists use homogeneous PICU admission criteria based on patients' characteristics and severity of the clinical picture. Clinical practice guidelines for children with viral bronchiolitis should address the management of patients with severe clinical disease.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".