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Deceleration capacity derived from a five-minute electrocardiogram predicts mortality in the general population
In contemporary healthcare, effective risk stratification in the general population is vital amidst rising chronic disease rates and an ageing demographic. Deceleration Capacity of the heart rate (DC), derived from 24-hour Holter electrocardiograms, holds promise in risk stratification for cardiac p...
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Published in: | Scientific reports 2024-12, Vol.14 (1), p.30566-8, Article 30566 |
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creator | Steger, Alexander Barthel, Petra Müller, Alexander Rückert-Eheberg, Ina-Maria Linkohr, Birgit Allescher, Julia Maier, Melanie Hapfelmeier, Alexander Martens, Eimo Heidegger, Helene Hildegard Müller, Arne Michael Rizas, Konstantinos D. Kääb, Stefan Sinner, Moritz F. Sinnecker, Daniel Laugwitz, Karl-Ludwig Peters, Annette Schmidt, Georg |
description | In contemporary healthcare, effective risk stratification in the general population is vital amidst rising chronic disease rates and an ageing demographic. Deceleration Capacity of the heart rate (DC), derived from 24-hour Holter electrocardiograms, holds promise in risk stratification for cardiac patients. However, the potential of short-term electrocardiograms of five minutes duration for population screening has not been fully explored. Our study aims to investigate the utility of Deceleration Capacity derived from short-term electrocardiograms as a scalable, fully-automated screening tool for predicting long-term mortality risk in the general population. Within a cohort of a representative population-based survey in Germany (KORA-KMC-study), 823 participants with sinus rhythm aged 27 to 76 years at enrollment (females 47.4%) were followed for a median of 13.4 years (IQR 13.1–13.6). All-cause mortality was defined as the primary endpoint and observed in 159 participants. Deceleration Capacity was calculated from 5-minute 12-lead electrocardiograms by a fully automated approach. Participants were divided into three predefined risk categories: DC
category0
– low-risk (> 4.5ms); DC
category1
– intermediate-risk (2.5-4.5ms); and DC
category2
– high-risk (≤ 2.5ms). More than two-thirds of the participants (
n
= 564, 68.5%) fell into DC
category0
, about one-fifth (
n
= 168, 20.4%) into DC
category1
, and about one-tenth (
n
= 91, 11.1%) into DC
category2
. Estimated 13-years mortality in the risk groups was 16.7%, 23.5%, and 49.1%, respectively (
p
|
doi_str_mv | 10.1038/s41598-024-83712-w |
format | article |
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category0
– low-risk (> 4.5ms); DC
category1
– intermediate-risk (2.5-4.5ms); and DC
category2
– high-risk (≤ 2.5ms). More than two-thirds of the participants (
n
= 564, 68.5%) fell into DC
category0
, about one-fifth (
n
= 168, 20.4%) into DC
category1
, and about one-tenth (
n
= 91, 11.1%) into DC
category2
. Estimated 13-years mortality in the risk groups was 16.7%, 23.5%, and 49.1%, respectively (
p
< 0.001). Adjusting for age, life-style-related risk factors, and comorbidities, increased mortality risk was observed for DC
category2
(HR 2.34, 95%-CI 1.56–3.50). Deceleration Capacity, derived automatically from brief 5-minute electrocardiogram recordings, emerges as a robust, feasible, and independent predictor of long-term mortality risk in the general population.</description><identifier>ISSN: 2045-2322</identifier><identifier>EISSN: 2045-2322</identifier><identifier>DOI: 10.1038/s41598-024-83712-w</identifier><identifier>PMID: 39702502</identifier><language>eng</language><publisher>London: Nature Publishing Group UK</publisher><subject>631/114 ; 639/705/1046 ; 692/308/409 ; 692/4019 ; 692/53/2423 ; 692/700/1750 ; 692/700/478/2772 ; Adult ; Aged ; Aging ; Automation ; Autonomic regulation ; Comorbidity ; Deceleration ; Deceleration capacity of the heart rate ; EKG ; Electrocardiogram ; Electrocardiography ; Electrocardiography - methods ; Electrocardiography, Ambulatory - methods ; Female ; Fully automated biosignal analysis ; General population screening ; Germany - epidemiology ; Health risks ; Heart diseases ; Heart rate ; Heart Rate - physiology ; Humanities and Social Sciences ; Humans ; Male ; Middle Aged ; Mortality ; Mortality risk ; multidisciplinary ; Non-invasive long-term risk stratification ; Population ; Population studies ; Risk Assessment - methods ; Risk Factors ; Risk groups ; Science ; Science (multidisciplinary)</subject><ispartof>Scientific reports, 2024-12, Vol.14 (1), p.30566-8, Article 30566</ispartof><rights>The Author(s) 2024</rights><rights>2024. The Author(s).</rights><rights>Copyright Nature Publishing Group 2024</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c2731-9bcc736519d8f223b8a2d4a915ca099dbf63e1865c7ea97c07d728a42972660f3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/3147399735/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/3147399735?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>314,780,784,25753,27924,27925,37012,37013,44590,74998</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/39702502$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Steger, Alexander</creatorcontrib><creatorcontrib>Barthel, Petra</creatorcontrib><creatorcontrib>Müller, Alexander</creatorcontrib><creatorcontrib>Rückert-Eheberg, Ina-Maria</creatorcontrib><creatorcontrib>Linkohr, Birgit</creatorcontrib><creatorcontrib>Allescher, Julia</creatorcontrib><creatorcontrib>Maier, Melanie</creatorcontrib><creatorcontrib>Hapfelmeier, Alexander</creatorcontrib><creatorcontrib>Martens, Eimo</creatorcontrib><creatorcontrib>Heidegger, Helene Hildegard</creatorcontrib><creatorcontrib>Müller, Arne Michael</creatorcontrib><creatorcontrib>Rizas, Konstantinos D.</creatorcontrib><creatorcontrib>Kääb, Stefan</creatorcontrib><creatorcontrib>Sinner, Moritz F.</creatorcontrib><creatorcontrib>Sinnecker, Daniel</creatorcontrib><creatorcontrib>Laugwitz, Karl-Ludwig</creatorcontrib><creatorcontrib>Peters, Annette</creatorcontrib><creatorcontrib>Schmidt, Georg</creatorcontrib><title>Deceleration capacity derived from a five-minute electrocardiogram predicts mortality in the general population</title><title>Scientific reports</title><addtitle>Sci Rep</addtitle><addtitle>Sci Rep</addtitle><description>In contemporary healthcare, effective risk stratification in the general population is vital amidst rising chronic disease rates and an ageing demographic. Deceleration Capacity of the heart rate (DC), derived from 24-hour Holter electrocardiograms, holds promise in risk stratification for cardiac patients. However, the potential of short-term electrocardiograms of five minutes duration for population screening has not been fully explored. Our study aims to investigate the utility of Deceleration Capacity derived from short-term electrocardiograms as a scalable, fully-automated screening tool for predicting long-term mortality risk in the general population. Within a cohort of a representative population-based survey in Germany (KORA-KMC-study), 823 participants with sinus rhythm aged 27 to 76 years at enrollment (females 47.4%) were followed for a median of 13.4 years (IQR 13.1–13.6). All-cause mortality was defined as the primary endpoint and observed in 159 participants. Deceleration Capacity was calculated from 5-minute 12-lead electrocardiograms by a fully automated approach. Participants were divided into three predefined risk categories: DC
category0
– low-risk (> 4.5ms); DC
category1
– intermediate-risk (2.5-4.5ms); and DC
category2
– high-risk (≤ 2.5ms). More than two-thirds of the participants (
n
= 564, 68.5%) fell into DC
category0
, about one-fifth (
n
= 168, 20.4%) into DC
category1
, and about one-tenth (
n
= 91, 11.1%) into DC
category2
. Estimated 13-years mortality in the risk groups was 16.7%, 23.5%, and 49.1%, respectively (
p
< 0.001). Adjusting for age, life-style-related risk factors, and comorbidities, increased mortality risk was observed for DC
category2
(HR 2.34, 95%-CI 1.56–3.50). Deceleration Capacity, derived automatically from brief 5-minute electrocardiogram recordings, emerges as a robust, feasible, and independent predictor of long-term mortality risk in the general population.</description><subject>631/114</subject><subject>639/705/1046</subject><subject>692/308/409</subject><subject>692/4019</subject><subject>692/53/2423</subject><subject>692/700/1750</subject><subject>692/700/478/2772</subject><subject>Adult</subject><subject>Aged</subject><subject>Aging</subject><subject>Automation</subject><subject>Autonomic regulation</subject><subject>Comorbidity</subject><subject>Deceleration</subject><subject>Deceleration capacity of the heart rate</subject><subject>EKG</subject><subject>Electrocardiogram</subject><subject>Electrocardiography</subject><subject>Electrocardiography - methods</subject><subject>Electrocardiography, Ambulatory - methods</subject><subject>Female</subject><subject>Fully automated biosignal analysis</subject><subject>General population screening</subject><subject>Germany - epidemiology</subject><subject>Health risks</subject><subject>Heart diseases</subject><subject>Heart rate</subject><subject>Heart Rate - physiology</subject><subject>Humanities and Social Sciences</subject><subject>Humans</subject><subject>Male</subject><subject>Middle Aged</subject><subject>Mortality</subject><subject>Mortality risk</subject><subject>multidisciplinary</subject><subject>Non-invasive long-term risk stratification</subject><subject>Population</subject><subject>Population studies</subject><subject>Risk Assessment - methods</subject><subject>Risk Factors</subject><subject>Risk groups</subject><subject>Science</subject><subject>Science (multidisciplinary)</subject><issn>2045-2322</issn><issn>2045-2322</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNp9kUtv1TAQhSMEaqu2f6ALZIkNm4CfcbxEpdBKldiUtTWxJxdfJXGwE6r-e9ybtiAWeOPXd87Yc6rqgtEPjIr2Y5ZMmbamXNat0IzX96-qE06lqrng_PVf6-PqPOc9LUNxI5k5qo6F0ZQryk-q-BkdDphgCXEiDmZwYXkgHlP4hZ70KY4ESF829RimdUFSaLek6CD5EHcJRjIn9MEtmYwxLTA86sNElh9IdjgV64HMcV6HQ4mz6k0PQ8bzp_m0-v7l6u7yur799vXm8tNt7bgWrDadc1o0ihnf9pyLrgXuJRimHFBjfNc3AlnbKKcRjHZUe81bkNxo3jS0F6fVzebrI-ztnMII6cFGCPZwENPOQlqCG9B2DBtuirAUkAhNh6XBqPtGK6Ylg-L1fvOaU_y5Yl7sGHLp2gATxjVbwaSWrRLcFPTdP-g-rmkqPz1QopQRqlB8o1yKOSfsXx7IqH1M127p2pKuPaRr74vo7ZP12o3oXyTPWRZAbEAuV9MO05_a_7H9DckOsF0</recordid><startdate>20241219</startdate><enddate>20241219</enddate><creator>Steger, Alexander</creator><creator>Barthel, Petra</creator><creator>Müller, Alexander</creator><creator>Rückert-Eheberg, Ina-Maria</creator><creator>Linkohr, Birgit</creator><creator>Allescher, Julia</creator><creator>Maier, Melanie</creator><creator>Hapfelmeier, Alexander</creator><creator>Martens, Eimo</creator><creator>Heidegger, Helene Hildegard</creator><creator>Müller, Arne Michael</creator><creator>Rizas, Konstantinos D.</creator><creator>Kääb, Stefan</creator><creator>Sinner, Moritz F.</creator><creator>Sinnecker, Daniel</creator><creator>Laugwitz, Karl-Ludwig</creator><creator>Peters, Annette</creator><creator>Schmidt, Georg</creator><general>Nature Publishing Group UK</general><general>Nature Publishing Group</general><general>Nature Portfolio</general><scope>C6C</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7X7</scope><scope>7XB</scope><scope>88A</scope><scope>88E</scope><scope>88I</scope><scope>8FE</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>LK8</scope><scope>M0S</scope><scope>M1P</scope><scope>M2P</scope><scope>M7P</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>Q9U</scope><scope>7X8</scope><scope>DOA</scope></search><sort><creationdate>20241219</creationdate><title>Deceleration capacity derived from a five-minute electrocardiogram predicts mortality in the general population</title><author>Steger, Alexander ; Barthel, Petra ; Müller, Alexander ; Rückert-Eheberg, Ina-Maria ; Linkohr, Birgit ; Allescher, Julia ; Maier, Melanie ; Hapfelmeier, Alexander ; Martens, Eimo ; Heidegger, Helene Hildegard ; Müller, Arne Michael ; Rizas, Konstantinos D. ; Kääb, Stefan ; Sinner, Moritz F. ; Sinnecker, Daniel ; Laugwitz, Karl-Ludwig ; Peters, Annette ; Schmidt, Georg</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c2731-9bcc736519d8f223b8a2d4a915ca099dbf63e1865c7ea97c07d728a42972660f3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>631/114</topic><topic>639/705/1046</topic><topic>692/308/409</topic><topic>692/4019</topic><topic>692/53/2423</topic><topic>692/700/1750</topic><topic>692/700/478/2772</topic><topic>Adult</topic><topic>Aged</topic><topic>Aging</topic><topic>Automation</topic><topic>Autonomic regulation</topic><topic>Comorbidity</topic><topic>Deceleration</topic><topic>Deceleration capacity of the heart rate</topic><topic>EKG</topic><topic>Electrocardiogram</topic><topic>Electrocardiography</topic><topic>Electrocardiography - methods</topic><topic>Electrocardiography, Ambulatory - methods</topic><topic>Female</topic><topic>Fully automated biosignal analysis</topic><topic>General population screening</topic><topic>Germany - epidemiology</topic><topic>Health risks</topic><topic>Heart diseases</topic><topic>Heart rate</topic><topic>Heart Rate - physiology</topic><topic>Humanities and Social Sciences</topic><topic>Humans</topic><topic>Male</topic><topic>Middle Aged</topic><topic>Mortality</topic><topic>Mortality risk</topic><topic>multidisciplinary</topic><topic>Non-invasive long-term risk stratification</topic><topic>Population</topic><topic>Population studies</topic><topic>Risk Assessment - methods</topic><topic>Risk Factors</topic><topic>Risk groups</topic><topic>Science</topic><topic>Science (multidisciplinary)</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Steger, Alexander</creatorcontrib><creatorcontrib>Barthel, Petra</creatorcontrib><creatorcontrib>Müller, Alexander</creatorcontrib><creatorcontrib>Rückert-Eheberg, Ina-Maria</creatorcontrib><creatorcontrib>Linkohr, Birgit</creatorcontrib><creatorcontrib>Allescher, Julia</creatorcontrib><creatorcontrib>Maier, Melanie</creatorcontrib><creatorcontrib>Hapfelmeier, Alexander</creatorcontrib><creatorcontrib>Martens, Eimo</creatorcontrib><creatorcontrib>Heidegger, Helene Hildegard</creatorcontrib><creatorcontrib>Müller, Arne Michael</creatorcontrib><creatorcontrib>Rizas, Konstantinos D.</creatorcontrib><creatorcontrib>Kääb, Stefan</creatorcontrib><creatorcontrib>Sinner, Moritz F.</creatorcontrib><creatorcontrib>Sinnecker, Daniel</creatorcontrib><creatorcontrib>Laugwitz, Karl-Ludwig</creatorcontrib><creatorcontrib>Peters, Annette</creatorcontrib><creatorcontrib>Schmidt, Georg</creatorcontrib><collection>SpringerOpen</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Biology Database (Alumni Edition)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Science Database (Alumni Edition)</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>ProQuest Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Biological Sciences</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Science Database</collection><collection>Biological Science Database</collection><collection>Publicly Available Content (ProQuest)</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>ProQuest Central Basic</collection><collection>MEDLINE - Academic</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>Scientific reports</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Steger, Alexander</au><au>Barthel, Petra</au><au>Müller, Alexander</au><au>Rückert-Eheberg, Ina-Maria</au><au>Linkohr, Birgit</au><au>Allescher, Julia</au><au>Maier, Melanie</au><au>Hapfelmeier, Alexander</au><au>Martens, Eimo</au><au>Heidegger, Helene Hildegard</au><au>Müller, Arne Michael</au><au>Rizas, Konstantinos D.</au><au>Kääb, Stefan</au><au>Sinner, Moritz F.</au><au>Sinnecker, Daniel</au><au>Laugwitz, Karl-Ludwig</au><au>Peters, Annette</au><au>Schmidt, Georg</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Deceleration capacity derived from a five-minute electrocardiogram predicts mortality in the general population</atitle><jtitle>Scientific reports</jtitle><stitle>Sci Rep</stitle><addtitle>Sci Rep</addtitle><date>2024-12-19</date><risdate>2024</risdate><volume>14</volume><issue>1</issue><spage>30566</spage><epage>8</epage><pages>30566-8</pages><artnum>30566</artnum><issn>2045-2322</issn><eissn>2045-2322</eissn><abstract>In contemporary healthcare, effective risk stratification in the general population is vital amidst rising chronic disease rates and an ageing demographic. Deceleration Capacity of the heart rate (DC), derived from 24-hour Holter electrocardiograms, holds promise in risk stratification for cardiac patients. However, the potential of short-term electrocardiograms of five minutes duration for population screening has not been fully explored. Our study aims to investigate the utility of Deceleration Capacity derived from short-term electrocardiograms as a scalable, fully-automated screening tool for predicting long-term mortality risk in the general population. Within a cohort of a representative population-based survey in Germany (KORA-KMC-study), 823 participants with sinus rhythm aged 27 to 76 years at enrollment (females 47.4%) were followed for a median of 13.4 years (IQR 13.1–13.6). All-cause mortality was defined as the primary endpoint and observed in 159 participants. Deceleration Capacity was calculated from 5-minute 12-lead electrocardiograms by a fully automated approach. Participants were divided into three predefined risk categories: DC
category0
– low-risk (> 4.5ms); DC
category1
– intermediate-risk (2.5-4.5ms); and DC
category2
– high-risk (≤ 2.5ms). More than two-thirds of the participants (
n
= 564, 68.5%) fell into DC
category0
, about one-fifth (
n
= 168, 20.4%) into DC
category1
, and about one-tenth (
n
= 91, 11.1%) into DC
category2
. Estimated 13-years mortality in the risk groups was 16.7%, 23.5%, and 49.1%, respectively (
p
< 0.001). Adjusting for age, life-style-related risk factors, and comorbidities, increased mortality risk was observed for DC
category2
(HR 2.34, 95%-CI 1.56–3.50). Deceleration Capacity, derived automatically from brief 5-minute electrocardiogram recordings, emerges as a robust, feasible, and independent predictor of long-term mortality risk in the general population.</abstract><cop>London</cop><pub>Nature Publishing Group UK</pub><pmid>39702502</pmid><doi>10.1038/s41598-024-83712-w</doi><tpages>8</tpages><oa>free_for_read</oa></addata></record> |
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source | PMC (PubMed Central); Full-Text Journals in Chemistry (Open access); Publicly Available Content (ProQuest); Springer Nature - nature.com Journals - Fully Open Access |
subjects | 631/114 639/705/1046 692/308/409 692/4019 692/53/2423 692/700/1750 692/700/478/2772 Adult Aged Aging Automation Autonomic regulation Comorbidity Deceleration Deceleration capacity of the heart rate EKG Electrocardiogram Electrocardiography Electrocardiography - methods Electrocardiography, Ambulatory - methods Female Fully automated biosignal analysis General population screening Germany - epidemiology Health risks Heart diseases Heart rate Heart Rate - physiology Humanities and Social Sciences Humans Male Middle Aged Mortality Mortality risk multidisciplinary Non-invasive long-term risk stratification Population Population studies Risk Assessment - methods Risk Factors Risk groups Science Science (multidisciplinary) |
title | Deceleration capacity derived from a five-minute electrocardiogram predicts mortality in the general population |
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