Factors associated with treatment failure of high-flow nasal cannula among children with bronchiolitis: a single-centre retrospective study
Bibliographic record
Abstract
OBJECTIVES: Bronchiolitis is the most common viral lower respiratory tract infection in children under age 2 for which high-flow nasal cannula (HFNC) is increasingly used. Understanding factors associated with HFNC failure is important to identify patients at risk for respiratory deterioration. The objective of this study was to evaluate patient characteristics associated with HFNC failure in bronchiolitis. METHODS: A retrospective review of patients aged 0 to 24 months, with bronchiolitis who received HFNC within a single tertiary paediatric intensive care unit, between January 2014 and December 2018 was conducted. HFNC treatment failure was defined as escalation to non-invasive positive pressure or invasive mechanical ventilation. Multivariable regression analysis was used to identify demographic, clinical, and biochemical parameters associated with HFNC failure. RESULTS: Two hundred eight patients met inclusion criteria, of which 61 (29.33%) failed HFNC. Risk factors for HFNC failure included younger age (odds ratio [OR] 1.12; 95% confidence interval [CI] 1.03, 1.23; P=0.011) and a Modified Tal score greater than 5 at 4 hours of HFNC therapy (OR 2.81; 95% CI 1.04, 7.64; P=0.042). Duration of HFNC in hours was protective (OR 0.94; 95% CI 0.92, 0.96; P<0.001), such that deterioration is less likely once patients have remained stable on HFNC for a prolonged time. CONCLUSION: This is the first study exploring predictors of HFNC failure among Canadian children with bronchiolitis. Patient age, HFNC duration, and Modified Tal score were associated with HFNC failure. These factors should be considered when initiating HFNC for bronchiolitis to identify patients at risk for deterioration.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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".