Comparison of the Between the Flags calling criteria to the MEWS, NEWS and the electronic Cardiac Arrest Risk Triage (eCART) score for the identification of deteriorating ward patients
Comparison of the Between the Flags calling criteria to the MEWS, NEWS and the electronic Cardiac Arrest Risk Triage (eCART) score for the identification of deteriorating ward patients
复制标题
DOI：
10.1016/j.resuscitation.2017.10.028
复制
发表时间：
2018-02-01
期刊：
影响因子：
6.5
通讯作者：
Edelson, Dana
中科院分区：
文献类型：
--
作者：
Green, Malcolm;Lander, Harvey;Edelson, Dana
导言：传统上，纸质观察表被用来识别病情恶化的患者，最近出现的电子病历允许电子算法进行风险分层，并帮助指导病情恶化的反应。目标(S)：我们试图比较旗帜(BTf)呼叫标准与修正的早期预警评分(MEWS)、国家早期预警评分(NEWS)和电子心脏骤停风险分诊(ERART)评分之间的差异。设计和参与者：对2008年11月至2013年8月美国五家医院收治的所有患者的电子医疗记录数据进行多中心回顾分析。主要结果指标：心脏骤停，结果：ECART的总体准确率最高，AUC值为0.801(95%CI为0.799~0.802)，其次为NEWS、MEWS和BTF(0.718[0.716~0.720])；0.698[0.696-0.700]；0.663[0.661-0.664])。BTF标准的高危(红区)特异度为95.0%，中危(黄区)特异度为27.5%，分别对应MEWS阈值=4和=2，新闻阈值=5和=2，ERART阈值=12和=4。在这些阈值下，使用中风险标准时，ERART在每10,000名患者中发现的不良事件比BTF多22个，使用高风险标准时多发现13个，而MEWS和NEWS发现的相同或更少。结论：在观察24小时内，电子生成的ERART评分比常用的纸质观察工具更准确地预测住院心脏骤停、ICU转院和死亡的综合结果。这项分析的结果有助于为病情恶化的患者提供基于算法的电子风险识别工具，以确保更早地发现并防止医院内的不良事件。(C)2017爱思唯尔B.V.保留所有权利。
Introduction: Traditionally, paper based observation charts have been used to identify deteriorating patients, with emerging recent electronic medical records allowing electronic algorithms to risk stratify and help direct the response to deterioration.Objective(s): We sought to compare the Between the Flags (BTF) calling criteria to the Modified Early Warning Score (MEWS), National Early Warning Score (NEWS) and electronic Cardiac Arrest Risk Triage (eCART) score.Design and participants: Multicenter retrospective analysis of electronic health record data from all patients admitted to five US hospitals from November 2008-August 2013.Main outcome measures: Cardiac arrest, ICU transfer or death within 24 h of a scoreResults: Overall accuracy was highest for eCART, with an AUC of 0.801 (95% CI 0.799-0.802), followed by NEWS, MEWS and BTF respectively (0.718 [0.716-0.720]; 0.698 [0.696-0.700]; 0.663 [0.661-0.664]). BTF criteria had a high risk (Red Zone) specificity of 95.0% and a moderate risk (Yellow Zone) specificity of 27.5%, which corresponded to MEWS thresholds of > = 4 and > = 2, NEWS thresholds of > = 5 and > = 2, and eCART thresholds of > = 12 and > = 4, respectively. At those thresholds, eCART caught 22 more adverse events per 10,000 patients than BTF using the moderate risk criteria and 13 more using high risk criteria, while MEWS and NEWS identified the same or fewer.Conclusion(s): An electronically generated eCART score was more accurate than commonly used paper based observation tools for predicting the composite outcome of in-hospital cardiac arrest, ICU transfer and death within 24 h of observation. The outcomes of this analysis lend weight for a move towards an algorithm based electronic risk identification tool for deteriorating patients to ensure earlier detection and prevent adverse events in the hospital. (C) 2017 Elsevier B.V. All rights reserved.