基于hs-cTnT和H-FABP的急性心肌梗死排除算法

César Navarro, M. Kurth, M. Ruddock, S. Fishlock, J. Mclaughlin
{"title":"基于hs-cTnT和H-FABP的急性心肌梗死排除算法","authors":"César Navarro, M. Kurth, M. Ruddock, S. Fishlock, J. Mclaughlin","doi":"10.23919/CinC49843.2019.9005791","DOIUrl":null,"url":null,"abstract":"Our previous work demonstrated that algorithms combining high sensitivity cardiac troponin T (hs-cTnT) and heart-type fatty acid-binding protein (H-FABP) may help in ruling out Acute Myocardial Infarction (AMI). For those algorithms, the hs-cTnT thresholds were adopted from the ESC guidelines. This time, we present a data-driven approach that also explores hs-cTnT thresholds.The results show a significant improvement when compared to previous algorithms reported. Using a cohort of n = 360 patients (288 Non-AMI and 72 AMI), a rule-out algorithm used at presentation identified more low-risk patients who presented with chest pain of suspected cardiac origin than the standard ESC algorithm: (199/288 (69.1%) vs. 83/288 (28.8%) (p <0.0005)), respectively.According to our data, our algorithm at the emergency department, would identify additional non-AMI patients in comparison to the ESC algorithm, potentially reducing the number of hospital admissions by 42%.","PeriodicalId":6697,"journal":{"name":"2019 Computing in Cardiology (CinC)","volume":"175 1","pages":"Page 1-Page 4"},"PeriodicalIF":0.0000,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"An Algorithm Based on Combining hs-cTnT and H-FABP for Ruling Out Acute Myocardial Infarction\",\"authors\":\"César Navarro, M. Kurth, M. Ruddock, S. Fishlock, J. Mclaughlin\",\"doi\":\"10.23919/CinC49843.2019.9005791\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Our previous work demonstrated that algorithms combining high sensitivity cardiac troponin T (hs-cTnT) and heart-type fatty acid-binding protein (H-FABP) may help in ruling out Acute Myocardial Infarction (AMI). For those algorithms, the hs-cTnT thresholds were adopted from the ESC guidelines. This time, we present a data-driven approach that also explores hs-cTnT thresholds.The results show a significant improvement when compared to previous algorithms reported. Using a cohort of n = 360 patients (288 Non-AMI and 72 AMI), a rule-out algorithm used at presentation identified more low-risk patients who presented with chest pain of suspected cardiac origin than the standard ESC algorithm: (199/288 (69.1%) vs. 83/288 (28.8%) (p <0.0005)), respectively.According to our data, our algorithm at the emergency department, would identify additional non-AMI patients in comparison to the ESC algorithm, potentially reducing the number of hospital admissions by 42%.\",\"PeriodicalId\":6697,\"journal\":{\"name\":\"2019 Computing in Cardiology (CinC)\",\"volume\":\"175 1\",\"pages\":\"Page 1-Page 4\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 Computing in Cardiology (CinC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.23919/CinC49843.2019.9005791\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 Computing in Cardiology (CinC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/CinC49843.2019.9005791","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

我们之前的工作表明,结合高灵敏度心肌肌钙蛋白T (hs-cTnT)和心脏型脂肪酸结合蛋白(H-FABP)的算法可能有助于排除急性心肌梗死(AMI)。对于这些算法,采用ESC指南中的hs-cTnT阈值。这一次,我们提出了一种数据驱动的方法,也探索了hs-cTnT阈值。结果表明,与以前报道的算法相比,该算法有了显著的改进。在一组n = 360例患者(288例非AMI和72例AMI)中,在就诊时使用的排除算法比标准ESC算法识别出更多疑似心源性胸痛的低风险患者:(199/288 (69.1%)vs. 83/288 (28.8%) (p <0.0005))。根据我们的数据,与ESC算法相比,我们在急诊科的算法将识别出额外的非ami患者,可能将住院人数减少42%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Algorithm Based on Combining hs-cTnT and H-FABP for Ruling Out Acute Myocardial Infarction
Our previous work demonstrated that algorithms combining high sensitivity cardiac troponin T (hs-cTnT) and heart-type fatty acid-binding protein (H-FABP) may help in ruling out Acute Myocardial Infarction (AMI). For those algorithms, the hs-cTnT thresholds were adopted from the ESC guidelines. This time, we present a data-driven approach that also explores hs-cTnT thresholds.The results show a significant improvement when compared to previous algorithms reported. Using a cohort of n = 360 patients (288 Non-AMI and 72 AMI), a rule-out algorithm used at presentation identified more low-risk patients who presented with chest pain of suspected cardiac origin than the standard ESC algorithm: (199/288 (69.1%) vs. 83/288 (28.8%) (p <0.0005)), respectively.According to our data, our algorithm at the emergency department, would identify additional non-AMI patients in comparison to the ESC algorithm, potentially reducing the number of hospital admissions by 42%.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信