Safety of paediatric tracheal intubation after non‐invasive ventilation failure
Bibliographic record
Abstract
CONTEXT: Non-invasive ventilation (NIV) is increasingly used in pediatric intensive care units to limit the complications associated with intubation. However, NIV may fail, and the delay in initiating invasive ventilation may be associated with adverse outcomes. The objective of this retrospective study was to evaluate the safety of tracheal intubation after NIV failure. METHODS: Consecutive tracheal intubation procedures were prospectively evaluated in our PICU from 01/2011 to 02/2012, as part of the National Emergency Airway Registry for Children (NEAR4KIDS) collaborative. The incidence of severe tracheal intubation associated events (TIAEs, including cardiac arrest, esophageal intubation with delayed recognition, emesis with aspiration, hypotension requiring intervention, laryngospasm, malignant hyperthermia, pneumothorax, and pneumomediastinum) and severe desaturation (below 80% when pre-intubation saturation was greater than 94%) were recorded prospectively. NIV use before intubation was retrospectively assessed. RESULTS: 100 consecutive intubation events were analyzed, 46 of which followed NIV failure. NIV exposed and non-exposed groups had different baseline characteristics, with lower weight, more frequent lower airway and lung disorder, and lower PIM2 score at admission in NIV failure patients (all P < 0.05). The nasal route for intubation was more frequent in NIV patients (P < 0.01). The incidence of severe TIAE or desaturation was 41% in the NIV failure group and 24% in primarily intubated patients (P = 0.09). CONCLUSION: Complications occurred in 41% of intubations after NIV failure in this series. Further research is warranted to evaluate strategies to prevent these complications and to identify conditions in which intubation should not be delayed for a trial of NIV.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".