Department of Clinical Sciences Lund, Lund University, Skåne University Hospital, Anaesthesiology and Intensive Care, Lund, Sweden.
Norman Cousins Center for Psychoneuroimmunology, Jane and Terry Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles (UCLA), Los Angeles, California, USA.
Acta Anaesthesiol Scand. 2023 Jan;67(1):44-56. doi: 10.1111/aas.14155. Epub 2022 Oct 17.
Failed management of unanticipated difficult airway situations contributes to significant anesthesia-related morbidity and mortality. Optimization of design and layout of difficult airway trolleys (DATs) may influence outcomes during airway emergencies. The main objective of the current study was to evaluate whether a difficult airway algorithm-based DAT with integrated cognitive aids improves efficiency and team performance in difficult airway scenarios.
In a crossover design, 16 teams (anesthetist, nurse anesthetist, assistant nurse) completed two high-fidelity simulated unanticipated difficult airway scenarios. Teams used both an algorithm-based DAT and a comparison, standard DAT, in the scenarios and were randomized to order of trolley type. Outcome measures included objective efficiency parameters, team performance assessment and subjective user-ratings. Linear mixed models ANOVA, including DAT type and order of condition as main factors, was utilized for the primary analyses of the team results.
Usage of the algorithm-based DAT was associated with fewer departures from the difficult airway algorithm (p = .010), and reduced number of unnecessary drawer openings (p = .002), but no significant differences in time to retrieval of airway devices or time to first effective ventilation, compared to the standard DAT. There were no significant differences in team performance, although participants expressed strong preference for the algorithm-based DAT (all user-rated measures p < .0001). Higher percentage of female members of the team improved adherence to the difficult airway algorithm (p = .043).
Algorithm-based DATs with integrated cognitive aids may improve efficiency in difficult airway situations, compared to traditional DATs. These findings have implications for improvement of anesthetic practice.
未预料到的困难气道管理失败会导致显著的麻醉相关发病率和死亡率。困难气道台车（DAT）的设计和布局的优化可能会影响气道紧急情况下的结果。本研究的主要目的是评估基于困难气道算法的 DAT 与集成认知辅助设备是否能提高困难气道情况下的效率和团队表现。
采用交叉设计，16 个团队（麻醉师、麻醉护士、助理护士）完成了两个高保真模拟的未预料到的困难气道场景。团队在这些场景中使用了基于算法的 DAT 和一个比较的标准 DAT，并随机分配了台车类型的顺序。主要的结果包括客观的效率参数、团队表现评估和主观用户评分。线性混合模型方差分析，包括 DAT 类型和条件的顺序作为主要因素，用于团队结果的主要分析。
使用基于算法的 DAT 与较少偏离困难气道算法有关（p=0.010），并且与标准 DAT 相比，减少了不必要的抽屉打开次数（p=0.002），但在气道设备检索时间或首次有效通气时间方面没有显著差异。团队表现没有显著差异，尽管参与者对基于算法的 DAT 表示强烈的偏好（所有用户评分指标 p<0.0001）。团队中女性成员的比例较高，对困难气道算法的依从性也有所提高（p=0.043）。
与传统的 DAT 相比，基于算法的 DAT 与集成认知辅助设备可能会提高困难气道情况下的效率。这些发现对改进麻醉实践具有重要意义。
