Risk stratification for arrhythmic death in an emergency department cohort: a new method of nonlinear PD2i analysis of the ECG
Heart rate variability (HRV) reflects both cardiac autonomic function and risk of sudden arrhythmic death (AD). Indices of HRV based on linear stochastic models are independent risk factors for AD in postmyocardial infarction (MI) cohorts. Indices based on nonlinear deterministic models have a highe...
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| Veröffentlicht in: | Therapeutics and clinical risk management 2008-08, Vol.4 (4), p.689-697 |
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| creator | Skinner, James E Meyer, Michael Dalsey, William C Nester, Brian A Ramalanjaona, George O'Neil, Brian J Mangione, Antoinette Terregino, Carol Moreyra, Abel Weiss, Daniel N Anchin, Jerry M Geary, Una Taggart, Pamela |
| description | Heart rate variability (HRV) reflects both cardiac autonomic function and risk of sudden arrhythmic death (AD). Indices of HRV based on linear stochastic models are independent risk factors for AD in postmyocardial infarction (MI) cohorts. Indices based on nonlinear deterministic models have a higher sensitivity and specificity for predicting AD in retrospective data. A new nonlinear deterministic model, the automated Point Correlation Dimension (PD2i), was prospectively evaluated for prediction of AD. Patients were enrolled (N = 918) in 6 emergency departments (EDs) upon presentation with chest pain and being determined to be at risk of acute MI (AMI) >7%. Brief digital ECGs (>1000 heartbeats, approximately 15 min) were recorded and automated PD2i results obtained. Out-of-hospital AD was determined by modified Hinkle-Thaler criteria. All-cause mortality at 1 year was 6.2%, with 3.5% being ADs. Of the AD fatalities, 34% were without previous history of MI or diagnosis of AMI. The PD2i prediction of AD had sensitivity = 96%, specificity = 85%, negative predictive value = 99%, and relative risk >24.2 (p ≤ 0.001). HRV analysis by the time-dependent nonlinear PD2i algorithm can accurately predict risk of AD in an ED cohort and may have both life-saving and resource-saving implications for individual risk assessment. |
| doi_str_mv | 10.2147/TCRM.S2741 |
| format | Article |
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Indices of HRV based on linear stochastic models are independent risk factors for AD in postmyocardial infarction (MI) cohorts. Indices based on nonlinear deterministic models have a higher sensitivity and specificity for predicting AD in retrospective data. A new nonlinear deterministic model, the automated Point Correlation Dimension (PD2i), was prospectively evaluated for prediction of AD. Patients were enrolled (N = 918) in 6 emergency departments (EDs) upon presentation with chest pain and being determined to be at risk of acute MI (AMI) >7%. Brief digital ECGs (>1000 heartbeats, approximately 15 min) were recorded and automated PD2i results obtained. Out-of-hospital AD was determined by modified Hinkle-Thaler criteria. All-cause mortality at 1 year was 6.2%, with 3.5% being ADs. Of the AD fatalities, 34% were without previous history of MI or diagnosis of AMI. The PD2i prediction of AD had sensitivity = 96%, specificity = 85%, negative predictive value = 99%, and relative risk >24.2 (p ≤ 0.001). HRV analysis by the time-dependent nonlinear PD2i algorithm can accurately predict risk of AD in an ED cohort and may have both life-saving and resource-saving implications for individual risk assessment.</description><identifier>ISSN: 1176-6336</identifier><identifier>ISSN: 1178-203X</identifier><identifier>EISSN: 1178-203X</identifier><identifier>DOI: 10.2147/TCRM.S2741</identifier><identifier>PMID: 19209249</identifier><language>eng</language><publisher>New Zealand: Taylor & Francis Ltd</publisher><subject>Automation ; chaos ; Electrocardiography ; Fatalities ; Health risk assessment ; heart rate variability ; non-linear ; Original Research ; sudden death ; ventricular arrhythmias</subject><ispartof>Therapeutics and clinical risk management, 2008-08, Vol.4 (4), p.689-697</ispartof><rights>2008. This work is licensed under https://creativecommons.org/licenses/by-nc/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2008 Dove Medical Press Limited. All rights reserved 2008</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3911-8b28c85e37f5e1274b97bf73ac5032330805d9c2626ca947a06e5355bc88ef5d3</citedby></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC2621378/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC2621378/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,881,3849,27901,27902,53766,53768</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/19209249$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Skinner, James E</creatorcontrib><creatorcontrib>Meyer, Michael</creatorcontrib><creatorcontrib>Dalsey, William C</creatorcontrib><creatorcontrib>Nester, Brian A</creatorcontrib><creatorcontrib>Ramalanjaona, George</creatorcontrib><creatorcontrib>O'Neil, Brian J</creatorcontrib><creatorcontrib>Mangione, Antoinette</creatorcontrib><creatorcontrib>Terregino, Carol</creatorcontrib><creatorcontrib>Moreyra, Abel</creatorcontrib><creatorcontrib>Weiss, Daniel N</creatorcontrib><creatorcontrib>Anchin, Jerry M</creatorcontrib><creatorcontrib>Geary, Una</creatorcontrib><creatorcontrib>Taggart, Pamela</creatorcontrib><title>Risk stratification for arrhythmic death in an emergency department cohort: a new method of nonlinear PD2i analysis of the ECG</title><title>Therapeutics and clinical risk management</title><addtitle>Ther Clin Risk Manag</addtitle><description>Heart rate variability (HRV) reflects both cardiac autonomic function and risk of sudden arrhythmic death (AD). Indices of HRV based on linear stochastic models are independent risk factors for AD in postmyocardial infarction (MI) cohorts. Indices based on nonlinear deterministic models have a higher sensitivity and specificity for predicting AD in retrospective data. A new nonlinear deterministic model, the automated Point Correlation Dimension (PD2i), was prospectively evaluated for prediction of AD. Patients were enrolled (N = 918) in 6 emergency departments (EDs) upon presentation with chest pain and being determined to be at risk of acute MI (AMI) >7%. Brief digital ECGs (>1000 heartbeats, approximately 15 min) were recorded and automated PD2i results obtained. Out-of-hospital AD was determined by modified Hinkle-Thaler criteria. All-cause mortality at 1 year was 6.2%, with 3.5% being ADs. Of the AD fatalities, 34% were without previous history of MI or diagnosis of AMI. The PD2i prediction of AD had sensitivity = 96%, specificity = 85%, negative predictive value = 99%, and relative risk >24.2 (p ≤ 0.001). HRV analysis by the time-dependent nonlinear PD2i algorithm can accurately predict risk of AD in an ED cohort and may have both life-saving and resource-saving implications for individual risk assessment.</description><subject>Automation</subject><subject>chaos</subject><subject>Electrocardiography</subject><subject>Fatalities</subject><subject>Health risk assessment</subject><subject>heart rate variability</subject><subject>non-linear</subject><subject>Original Research</subject><subject>sudden death</subject><subject>ventricular 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ECG</atitle><jtitle>Therapeutics and clinical risk management</jtitle><addtitle>Ther Clin Risk Manag</addtitle><date>2008-08-01</date><risdate>2008</risdate><volume>4</volume><issue>4</issue><spage>689</spage><epage>697</epage><pages>689-697</pages><issn>1176-6336</issn><issn>1178-203X</issn><eissn>1178-203X</eissn><abstract>Heart rate variability (HRV) reflects both cardiac autonomic function and risk of sudden arrhythmic death (AD). Indices of HRV based on linear stochastic models are independent risk factors for AD in postmyocardial infarction (MI) cohorts. Indices based on nonlinear deterministic models have a higher sensitivity and specificity for predicting AD in retrospective data. A new nonlinear deterministic model, the automated Point Correlation Dimension (PD2i), was prospectively evaluated for prediction of AD. Patients were enrolled (N = 918) in 6 emergency departments (EDs) upon presentation with chest pain and being determined to be at risk of acute MI (AMI) >7%. Brief digital ECGs (>1000 heartbeats, approximately 15 min) were recorded and automated PD2i results obtained. Out-of-hospital AD was determined by modified Hinkle-Thaler criteria. All-cause mortality at 1 year was 6.2%, with 3.5% being ADs. Of the AD fatalities, 34% were without previous history of MI or diagnosis of AMI. The PD2i prediction of AD had sensitivity = 96%, specificity = 85%, negative predictive value = 99%, and relative risk >24.2 (p ≤ 0.001). HRV analysis by the time-dependent nonlinear PD2i algorithm can accurately predict risk of AD in an ED cohort and may have both life-saving and resource-saving implications for individual risk assessment.</abstract><cop>New Zealand</cop><pub>Taylor & Francis Ltd</pub><pmid>19209249</pmid><doi>10.2147/TCRM.S2741</doi><tpages>9</tpages><oa>free_for_read</oa></addata></record> |
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| subjects | Automation chaos Electrocardiography Fatalities Health risk assessment heart rate variability non-linear Original Research sudden death ventricular arrhythmias |
| title | Risk stratification for arrhythmic death in an emergency department cohort: a new method of nonlinear PD2i analysis of the ECG |
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