E. Pueyo, P. Smetana, K. Hnatkova, P. Laguna, M. Malik
{"title":"胺碘酮治疗患者QT适应RR变化的时间与心律失常死亡率降低的关系","authors":"E. Pueyo, P. Smetana, K. Hnatkova, P. Laguna, M. Malik","doi":"10.1109/CIC.2002.1166835","DOIUrl":null,"url":null,"abstract":"A new method is proposed to evaluate, in continuous 24-hour recordings, the influence on QT of changes in heart rate occurred during some previous minutes. The method is based on considering averages of the RR intervals preceding the ith beat (R~R~i) using window lengths of up to 10 minutes. The averages are performed using several forgetting strategies, with the exponential weighted average turning out to be the best in modeling the QT dependence on previous RR intervals. For each patient, the regression model (selected from a defined set) and the window length leading to the optimum fit of the [QT/sub i/, R~R~i] relationship are selected RR variations in the past 4 minutes, on average, are shown to be required to accurately model the QT response to changes infrequency. A measure of the optimum fit residuum (ORR) is then calculated, showing a remarkable discriminative power to identify post-myocardial infarction patients at high risk of arrhythmic death after treatment with amiodarone.","PeriodicalId":80984,"journal":{"name":"Computers in cardiology","volume":"1 1","pages":"565-568"},"PeriodicalIF":0.0000,"publicationDate":"2002-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/CIC.2002.1166835","citationCount":"8","resultStr":"{\"title\":\"Time for QT adaptation to RR changes and relation to arrhythmic mortality reduction in amiodarone-treated patients\",\"authors\":\"E. Pueyo, P. Smetana, K. Hnatkova, P. Laguna, M. Malik\",\"doi\":\"10.1109/CIC.2002.1166835\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A new method is proposed to evaluate, in continuous 24-hour recordings, the influence on QT of changes in heart rate occurred during some previous minutes. The method is based on considering averages of the RR intervals preceding the ith beat (R~R~i) using window lengths of up to 10 minutes. The averages are performed using several forgetting strategies, with the exponential weighted average turning out to be the best in modeling the QT dependence on previous RR intervals. For each patient, the regression model (selected from a defined set) and the window length leading to the optimum fit of the [QT/sub i/, R~R~i] relationship are selected RR variations in the past 4 minutes, on average, are shown to be required to accurately model the QT response to changes infrequency. A measure of the optimum fit residuum (ORR) is then calculated, showing a remarkable discriminative power to identify post-myocardial infarction patients at high risk of arrhythmic death after treatment with amiodarone.\",\"PeriodicalId\":80984,\"journal\":{\"name\":\"Computers in cardiology\",\"volume\":\"1 1\",\"pages\":\"565-568\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2002-09-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1109/CIC.2002.1166835\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computers in cardiology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CIC.2002.1166835\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computers in cardiology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIC.2002.1166835","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Time for QT adaptation to RR changes and relation to arrhythmic mortality reduction in amiodarone-treated patients
A new method is proposed to evaluate, in continuous 24-hour recordings, the influence on QT of changes in heart rate occurred during some previous minutes. The method is based on considering averages of the RR intervals preceding the ith beat (R~R~i) using window lengths of up to 10 minutes. The averages are performed using several forgetting strategies, with the exponential weighted average turning out to be the best in modeling the QT dependence on previous RR intervals. For each patient, the regression model (selected from a defined set) and the window length leading to the optimum fit of the [QT/sub i/, R~R~i] relationship are selected RR variations in the past 4 minutes, on average, are shown to be required to accurately model the QT response to changes infrequency. A measure of the optimum fit residuum (ORR) is then calculated, showing a remarkable discriminative power to identify post-myocardial infarction patients at high risk of arrhythmic death after treatment with amiodarone.