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}
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%.