The Association of Teamwork and Adverse Tracheal Intubation–Associated Events in Advanced Airway Management in the PICU
Bibliographic record
Abstract
Abstract Tracheal intubation (TI) in critically ill children is a life-saving but high-risk procedure that involves multiple team members with diverse clinical skills. We aim to examine the association between the provider-reported teamwork rating and the occurrence of adverse TI-associated events (TIAEs). A retrospective analysis of prospectively collected data from 45 pediatric intensive care units in the National Emergency Airway Registry for Children (NEAR4KIDS) database from January 2013 to March 2018 was performed. A composite teamwork score was generated using the average of each of five (7-point Likert scale) domains in the teamwork assessment tool. Poor teamwork was defined as an average score of 4 or lower. Team provider stress data were also recorded with each intubation. A total of 12,536 TIs were reported from 2013 to 2018. Approximately 4.1% (n = 520) rated a poor teamwork score. TIs indicated for shock were more commonly associated with a poor teamwork score, while those indicated for procedures and those utilizing neuromuscular blockade were less commonly associated with a poor teamwork score. TIs with poor teamwork were associated with a higher occurrence of adverse TIAE (24.4% vs 14.4%, p < 0.001), severe TIAE (13.7% vs 5.9%, p < 0.001), and peri-intubation hypoxemia < 80% (26.4% vs 17.9%, p < 0.001). After adjusting for indication, provider type, and neuromuscular blockade use, poor teamwork was associated with higher odds of adverse TIAEs (odds ratio [OR], 1.77; 95% confidence interval [CI], 1.35–2.34), severe TIAEs (OR, 2.23; 95% CI, 1.47–3.37), and hypoxemia (OR, 1.63; 95% CI, 1.25–2.03). TIs with poor teamwork were independently associated with a higher occurrence of TIAEs, severe TIAEs, and hypoxemia.
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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 | 0.009 |
| 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".