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无脉性电活动评估与处理的简化结构化教学工具。

A simplified and structured teaching tool for the evaluation and management of pulseless electrical activity.

机构信息

Department of Internal Medicine, Carolinas Medical Center, Charlotte, N.C., USA.

出版信息

Med Princ Pract. 2014;23(1):1-6. doi: 10.1159/000354195. Epub 2013 Aug 13.

Abstract

Cardiac arrest victims who present with pulseless electrical activity (PEA) usually have a grave prognosis. Several conditions, however, have cause-specific treatments which, if applied immediately, can lead to quick and sustained recovery. Current teaching focuses on recollection of numerous conditions that start with the letters H or T as potential causes of PEA. This teaching method is too complex, difficult to recall during resuscitation, and does not provide guidance to the most effective initial interventions. This review proposes a structured algorithm that is based on the differentiation of the PEA rhythm into narrow- or wide-complex subcategories, which simplifies the working differential and initial treatment approach. This, in conjunction with bedside ultrasound, can quickly point towards the most likely cause of PEA and thus guide resuscitation.

摘要

心脏骤停患者出现无脉电活动 (PEA) 通常预后严重。然而,有几种情况有特定的病因治疗,如果立即应用,可迅速且持续地恢复。目前的教学重点是回忆以 H 或 T 开头的许多疾病,这些疾病可能是 PEA 的潜在病因。这种教学方法过于复杂,在复苏过程中难以回忆,并且不能为最有效的初始干预提供指导。本综述提出了一种基于 PEA 节律分为窄或宽复合亚类的结构化算法,简化了工作差异和初始治疗方法。结合床边超声,可快速确定 PEA 最可能的病因,从而指导复苏。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a424/5586830/e6c02344e117/mpp-0023-0001-g01.jpg

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