Intensive Care Unit, Hospital Sírio-Libanes, São Paulo, Brazil.
Interdepartmental Division of Critical Care Medicine, St. Michael's Hospital, Toronto, Canada.
Crit Care. 2023 Mar 30;27(1):128. doi: 10.1186/s13054-023-04414-9.
Patient-ventilator asynchronies are usually detected by visual inspection of ventilator waveforms but with low sensitivity, even when performed by experts in the field. Recently, estimation of the inspiratory muscle pressure (P) waveforms through artificial intelligence algorithm has been proposed (Magnamed®, São Paulo, Brazil). We hypothesized that the display of these waveforms could help healthcare providers identify patient-ventilator asynchronies.
A prospective single-center randomized study with parallel assignment was conducted to assess whether the display of the estimated P waveform would improve the correct identification of asynchronies in simulated clinical scenarios. The primary outcome was the mean asynchrony detection rate (sensitivity). Physicians and respiratory therapists who work in intensive care units were randomized to control or intervention group. In both groups, participants analyzed pressure and flow waveforms of 49 different scenarios elaborated using the ASL-5000 lung simulator. In the intervention group the estimated P waveform was displayed in addition to pressure and flow waveforms.
A total of 98 participants were included, 49 per group. The sensitivity per participant in identifying asynchronies was significantly higher in the P group (65.8 ± 16.2 vs. 52.94 ± 8.42, p < 0.001). This effect remained when stratifying asynchronies by type.
We showed that the display of the P waveform improved the ability of healthcare professionals to recognize patient-ventilator asynchronies by visual inspection of ventilator tracings. These findings require clinical validation.
ClinicalTrials.gov: NTC05144607. Retrospectively registered 3 December 2021.
患者-呼吸机不同步通常通过观察呼吸机波形来检测，但敏感性较低，即使由该领域的专家进行检测也是如此。最近，通过人工智能算法估计吸气肌压力（P）波形的方法已经提出（巴西圣保罗的 Magnamed®）。我们假设显示这些波形可以帮助医疗保健提供者识别患者-呼吸机不同步。
进行了一项前瞻性单中心随机研究，采用平行分组方法，评估估计 P 波形的显示是否会提高在模拟临床场景中识别不同步的准确性。主要结局是平均不同步检测率（敏感性）。在重症监护病房工作的医生和呼吸治疗师被随机分配到对照组或干预组。在两组中，参与者分析了使用 ASL-5000 肺模拟器设计的 49 种不同情况的压力和流量波形。在干预组中，除了压力和流量波形外，还显示了估计的 P 波形。
共有 98 名参与者被纳入研究，每组 49 名。在识别不同步方面，每个参与者的敏感性在 P 组明显更高（65.8±16.2 比 52.94±8.42，p<0.001）。这种效果在按类型分层不同步时仍然存在。
我们表明，通过观察呼吸机轨迹，显示 P 波形可提高医疗保健专业人员识别患者-呼吸机不同步的能力。这些发现需要临床验证。
ClinicalTrials.gov：NTC05144607。2021 年 12 月 3 日回顾性注册。
