Akhtar Waqas, Kiff Kristine, Wypych-Zych Agnieszka, Pinto Sofia, Cheng Audrey K H, Banya Winston, Rosenberg Alexander, Bowles Christopher T, Dunning John, Panoulas Vasileios
Cardiologist and Intensivist.
VAD Specialist Nurse.
Br J Cardiol. 2023 Aug 9;30(3):24. doi: 10.5837/bjc.2023.024. eCollection 2023.
We sought to remedy the limited guidance that is available to support the resuscitation of patients with the Impella Cardiac Power (CP) and 5.0 devices during episodes of cardiac arrest or life-threatening events that can result in haemodynamic decompensation. In a specialist tertiary referral centre we developed, by iteration, a novel resuscitation algorithm for Impella emergencies, which we validated through simulation and assessment by our multi- disciplinary team. A mechanical life support course was established to provide theoretical and practical education, combined with simulation to consolidate knowledge and confidence in algorithm use. We assessed these measures using confidence scoring, a key performance indicator (the time taken to resolve a suction event) and a multiple-choice question (MCQ) examination. Following this intervention, median confidence score increased from 2 (interquartile range [IQR] 2 to 3) to 4 (IQR 4 to 4) out of a maximum of 5 (n=53, p<0.0001). Theoretical knowledge of the Impella, as assessed by median MCQ score, increased from 12 (IQR 10 to 13) to 13 (12 to 14) out of a maximum of 17 (p<0.0001). The use of a bespoke Impella resuscitation algorithm reduced the mean time taken to identify and resolve a suction event by 53 seconds (95% confidence interval 36 to 99, p=0.0003). In conclusion, we present an evidence-based resuscitation algorithm that provides both technical and medical guidance to clinicians responding to life-threatening events in Impella recipients.
在心脏骤停或可能导致血流动力学失代偿的危及生命事件期间,支持使用Impella心脏动力(CP)和5.0设备对患者进行复苏的现有指导有限,我们试图对此加以补救。在一家专科三级转诊中心,我们通过反复摸索,开发出一种针对Impella紧急情况的新型复苏算法,并通过多学科团队的模拟和评估对其进行了验证。我们设立了一个机械生命支持课程,提供理论和实践教育,并结合模拟,以巩固对算法使用的知识和信心。我们使用信心评分、一项关键绩效指标(解决抽吸事件所需的时间)和多项选择题(MCQ)考试对这些措施进行了评估。经过这一干预,信心评分中位数从2(四分位间距[IQR]为2至3)提高到了4(IQR为4至4),满分是5分(n = 53,p<0.0001)。通过MCQ评分中位数评估的关于Impella的理论知识,从满分17分中的12分(IQR为10至13)提高到了13分(12至14)(p<0.0001)。使用定制的Impella复苏算法使识别和解决抽吸事件的平均时间减少了53秒(95%置信区间为36至99,p = 0.0003)。总之,我们提出了一种基于证据的复苏算法,为应对Impella使用者危及生命事件的临床医生提供技术和医学指导。