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Ischemic Stroke Risk Assessment by Multiscale Entropy Analysis of Heart Rate Variability in Patients with Persistent Atrial Fibrillation
It has been recognized that heart rate variability (HRV), defined as the fluctuation of ventricular response intervals in atrial fibrillation (AFib) patients, is not completely random, and its nonlinear characteristics, such as multiscale entropy (MSE), contain clinically significant information. We...
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Published in: | Entropy (Basel, Switzerland) Switzerland), 2021-07, Vol.23 (7), p.918 |
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description | It has been recognized that heart rate variability (HRV), defined as the fluctuation of ventricular response intervals in atrial fibrillation (AFib) patients, is not completely random, and its nonlinear characteristics, such as multiscale entropy (MSE), contain clinically significant information. We investigated the relationship between ischemic stroke risk and HRV with a large number of stroke-naïve AFib patients (628 patients), focusing on those who had never developed an ischemic/hemorrhagic stroke before the heart rate measurement. The CHA2DS2−VASc score was calculated from the baseline clinical characteristics, while the HRV analysis was made from the recording of morning, afternoon, and evening. Subsequently, we performed Kaplan–Meier method and cumulative incidence function with mortality as a competing risk to estimate the survival time function. We found that patients with sample entropy (SE(s)) ≥ 0.68 at 210 s had a significantly higher risk of an ischemic stroke occurrence in the morning recording. Meanwhile, the afternoon recording showed that those with SE(s) ≥ 0.76 at 240 s and SE(s) ≥ 0.78 at 270 s had a significantly lower risk of ischemic stroke occurrence. Therefore, SE(s) at 210 s (morning) and 240 s ≤ s ≤ 270 s (afternoon) demonstrated a statistically significant predictive value for ischemic stroke in stroke-naïve AFib patients. |
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We investigated the relationship between ischemic stroke risk and HRV with a large number of stroke-naïve AFib patients (628 patients), focusing on those who had never developed an ischemic/hemorrhagic stroke before the heart rate measurement. The CHA2DS2−VASc score was calculated from the baseline clinical characteristics, while the HRV analysis was made from the recording of morning, afternoon, and evening. Subsequently, we performed Kaplan–Meier method and cumulative incidence function with mortality as a competing risk to estimate the survival time function. We found that patients with sample entropy (SE(s)) ≥ 0.68 at 210 s had a significantly higher risk of an ischemic stroke occurrence in the morning recording. Meanwhile, the afternoon recording showed that those with SE(s) ≥ 0.76 at 240 s and SE(s) ≥ 0.78 at 270 s had a significantly lower risk of ischemic stroke occurrence. Therefore, SE(s) at 210 s (morning) and 240 s ≤ s ≤ 270 s (afternoon) demonstrated a statistically significant predictive value for ischemic stroke in stroke-naïve AFib patients.</description><identifier>ISSN: 1099-4300</identifier><identifier>EISSN: 1099-4300</identifier><identifier>DOI: 10.3390/e23070918</identifier><identifier>PMID: 34356459</identifier><language>eng</language><publisher>Basel: MDPI AG</publisher><subject>atrial fibrillation ; Cardiac arrhythmia ; Cardiomyopathy ; Cardiovascular disease ; Coronary vessels ; Diabetes ; Electrocardiography ; Entropy ; Fibrillation ; Heart failure ; Heart rate ; heart rate variability ; Hypertension ; ischemic stroke ; Morning ; multiscale entropy ; Patients ; Probability ; Probability distribution ; Recording ; Risk assessment ; Standard deviation ; Stroke ; Time functions ; Time series ; Transient ischemic attack</subject><ispartof>Entropy (Basel, Switzerland), 2021-07, Vol.23 (7), p.918</ispartof><rights>2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). 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We investigated the relationship between ischemic stroke risk and HRV with a large number of stroke-naïve AFib patients (628 patients), focusing on those who had never developed an ischemic/hemorrhagic stroke before the heart rate measurement. The CHA2DS2−VASc score was calculated from the baseline clinical characteristics, while the HRV analysis was made from the recording of morning, afternoon, and evening. Subsequently, we performed Kaplan–Meier method and cumulative incidence function with mortality as a competing risk to estimate the survival time function. We found that patients with sample entropy (SE(s)) ≥ 0.68 at 210 s had a significantly higher risk of an ischemic stroke occurrence in the morning recording. Meanwhile, the afternoon recording showed that those with SE(s) ≥ 0.76 at 240 s and SE(s) ≥ 0.78 at 270 s had a significantly lower risk of ischemic stroke occurrence. Therefore, SE(s) at 210 s (morning) and 240 s ≤ s ≤ 270 s (afternoon) demonstrated a statistically significant predictive value for ischemic stroke in stroke-naïve AFib patients.</description><subject>atrial fibrillation</subject><subject>Cardiac arrhythmia</subject><subject>Cardiomyopathy</subject><subject>Cardiovascular disease</subject><subject>Coronary vessels</subject><subject>Diabetes</subject><subject>Electrocardiography</subject><subject>Entropy</subject><subject>Fibrillation</subject><subject>Heart failure</subject><subject>Heart rate</subject><subject>heart rate variability</subject><subject>Hypertension</subject><subject>ischemic stroke</subject><subject>Morning</subject><subject>multiscale entropy</subject><subject>Patients</subject><subject>Probability</subject><subject>Probability distribution</subject><subject>Recording</subject><subject>Risk assessment</subject><subject>Standard deviation</subject><subject>Stroke</subject><subject>Time functions</subject><subject>Time series</subject><subject>Transient ischemic attack</subject><issn>1099-4300</issn><issn>1099-4300</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNpdkt9uFCEUhydGY2v1wjcg8UYvVg8DzAw3JpumtZvU2NQ_twSYM1227LACo5k38LFlu01jvYLAx5dzfpyqek3hPWMSPmDNoAVJuyfVMQUpF5wBPP1nf1S9SGkDULOaNs-rI8aZaLiQx9WfVbJr3DpLvuYYbpFcu3RLlilhSlscMzEz-Tz57JLVHsnZWKjdTJaj9nNyiYSBXKCOmVzrjOSHjk4b512eiRvJlc6uOBL57fKaXGEsL_JeusyF8-Tcmei8L1QYX1bPBu0TvrpfT6rv52ffTi8Wl18-rU6XlwvLeZMXvIOOSioakLUAYANvemssUIYwmBKD6YUwTNp2MKLTmuqutjVwg0IMumXspFodvH3QG7WLbqvjrIJ26u4gxBtV2nHWo-prI20vGmot4xYb3dZaYk-5rikK1hfXx4NrN5kt9ra0FrV_JH18M7q1ugm_VMdACE6L4O29IIafE6astiVoLJGMGKakaiEkZ0zAvu43_6GbMMXyDXcUF9CyRhTq3YGyMaQUcXgohoLaz4p6mBX2F0GjsVI</recordid><startdate>20210719</startdate><enddate>20210719</enddate><creator>Chairina, Ghina</creator><creator>Yoshino, Kohzoh</creator><creator>Kiyono, Ken</creator><creator>Watanabe, Eiichi</creator><general>MDPI AG</general><general>MDPI</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7TB</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>HCIFZ</scope><scope>KR7</scope><scope>L6V</scope><scope>M7S</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0001-5433-7002</orcidid></search><sort><creationdate>20210719</creationdate><title>Ischemic Stroke Risk Assessment by Multiscale Entropy Analysis of Heart Rate Variability in Patients with Persistent Atrial Fibrillation</title><author>Chairina, Ghina ; Yoshino, Kohzoh ; Kiyono, Ken ; Watanabe, Eiichi</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c446t-4808191560925003f46dcbc013e0fb307bd55b39c7fb58aa1a82c204be55fa733</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>atrial fibrillation</topic><topic>Cardiac arrhythmia</topic><topic>Cardiomyopathy</topic><topic>Cardiovascular disease</topic><topic>Coronary vessels</topic><topic>Diabetes</topic><topic>Electrocardiography</topic><topic>Entropy</topic><topic>Fibrillation</topic><topic>Heart failure</topic><topic>Heart rate</topic><topic>heart rate variability</topic><topic>Hypertension</topic><topic>ischemic stroke</topic><topic>Morning</topic><topic>multiscale entropy</topic><topic>Patients</topic><topic>Probability</topic><topic>Probability distribution</topic><topic>Recording</topic><topic>Risk assessment</topic><topic>Standard deviation</topic><topic>Stroke</topic><topic>Time functions</topic><topic>Time series</topic><topic>Transient ischemic attack</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Chairina, Ghina</creatorcontrib><creatorcontrib>Yoshino, Kohzoh</creatorcontrib><creatorcontrib>Kiyono, Ken</creatorcontrib><creatorcontrib>Watanabe, Eiichi</creatorcontrib><collection>CrossRef</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>AUTh Library subscriptions: ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>SciTech Premium Collection</collection><collection>Civil Engineering Abstracts</collection><collection>ProQuest Engineering Collection</collection><collection>Engineering Database</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering Collection</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>Entropy (Basel, Switzerland)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Chairina, Ghina</au><au>Yoshino, Kohzoh</au><au>Kiyono, Ken</au><au>Watanabe, Eiichi</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Ischemic Stroke Risk Assessment by Multiscale Entropy Analysis of Heart Rate Variability in Patients with Persistent Atrial Fibrillation</atitle><jtitle>Entropy (Basel, Switzerland)</jtitle><date>2021-07-19</date><risdate>2021</risdate><volume>23</volume><issue>7</issue><spage>918</spage><pages>918-</pages><issn>1099-4300</issn><eissn>1099-4300</eissn><abstract>It has been recognized that heart rate variability (HRV), defined as the fluctuation of ventricular response intervals in atrial fibrillation (AFib) patients, is not completely random, and its nonlinear characteristics, such as multiscale entropy (MSE), contain clinically significant information. 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subjects | atrial fibrillation Cardiac arrhythmia Cardiomyopathy Cardiovascular disease Coronary vessels Diabetes Electrocardiography Entropy Fibrillation Heart failure Heart rate heart rate variability Hypertension ischemic stroke Morning multiscale entropy Patients Probability Probability distribution Recording Risk assessment Standard deviation Stroke Time functions Time series Transient ischemic attack |
title | Ischemic Stroke Risk Assessment by Multiscale Entropy Analysis of Heart Rate Variability in Patients with Persistent Atrial Fibrillation |
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