Risk patterns of consecutive adverse events in airway management: a Bayesian network analysis
Authors' conclusion
Identification of risk patterns and typical structures of event sequences provides a clinically relevant perspective on airway incidents. It further provides a means to quantify the impact of targeted airway management changes. These targeted changes can influence some event sequences, but overall, the benefit results from the cumulative effect of improvements in multiple events.
Study context
- Population
- Patients undergoing airway management with minor, frequently occurring adverse airway events audited
- Comparison
- Before vs After
- Outcome
- Risk of first adverse airway event and conditional probabilities of event sequences
Methodological detailsbefore-and-after implementation
- Before-and-after implementation
Main finding
As reported in the abstract
Most likely event after difficult bag-mask ventilation: Cormack-Lehane grade ≥3
14.3%
95% CrI 11.4–17.2%
Further findings
| Outcome | Before | After |
|---|---|---|
| No consecutive event after a tracheal tube-related event | 43.3% (95% CrI 39.4–47.6%) | 56.4% (95% CrI 52.0–60.5%) |
- No consecutive event after a tracheal tube-related event: 95% credible interval
Original publication
Risk patterns of consecutive adverse events in airway management: a Bayesian network analysis. Br J Anaesth. Published 22 December 2022. doi:10.
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