Ability of ICU Health-Care Professionals to Identify Patient-Ventilator Asynchrony Using Waveform Analysis

摘要

BACKGROUND: Waveform analysis by visual inspection can be a reliable, noninvasive, and useful tool for detecting patient-ventilator asynchrony. However, it is a skill that requires a properly trained professional. METHODS: This observational study was conducted in 17 urban ICUs. Health-care professionals (HCPs) working in these ICUs were asked to recognize different types of asynchrony shown in 3 evaluation videos. The health-care professionals were categorized according to years of experience, prior training in mechanical ventilation, profession, and number of asyn-chronies identified correctly. RESULTS: A total of 366 HCPs were evaluated. Statistically significant differences were found when HCPs with and without prior training in mechanical ventilation (trained vs non-trained HCPs) were compared according to the number of asynchronies detected correctly (of the HCPs who identified 3 asynchronies, 63 [81 %] trained vs 15 [19%] non-trained, P <.001; 2 asynchronies, 72 [65 %] trained vs 39 [35 %] non-trained, P =.034; 1 asynchrony, 55 [47 %] trained vs 61 [53 %] non-trained, P =.02; 0 asynchronies, 17 [28 %] trained vs 44 [72 %] non-trained, P <.001). HCPs who had prior training in mechanical ventilation also increased, nearly 4-fold, their odds of identifying >= 2 asynchronies correctly (odds ratio 3.67, 95% CI 1.93-6.96, P <.001). However, neither years of experience nor profession were associated with the ability of HCPs to identify asynchrony. CONCLUSIONS: HCPs who have specific training in mechanical ventilation increase their ability to identify asynchrony using waveform analysis. Neither experience nor profession proved to be a relevant factor to identify asynchrony correctly using waveform analysis.