Longitudinal Change in Galectin-3 and Incident Cardiovascular Outcomes
Galectin-3 (Gal-3) has been associated with heart failure (HF) and poor cardiovascular outcomes. However, the effect of longitudinal changes in Gal-3 on clinical outcomes remains unclear. The authors sought to study clinical determinants of change in Gal-3 among community-dwelling individuals. Furth...
Gespeichert in:
| Veröffentlicht in: | Journal of the American College of Cardiology 2018-12, Vol.72 (25), p.3246-3254 |
|---|---|
| Hauptverfasser: | , , , , , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 3254 |
|---|---|
| container_issue | 25 |
| container_start_page | 3246 |
| container_title | Journal of the American College of Cardiology |
| container_volume | 72 |
| creator | Ghorbani, Anahita Bhambhani, Vijeta Christenson, Robert H. Meijers, Wouter C. de Boer, Rudolf A. Levy, Daniel Larson, Martin G. Ho, Jennifer E. |
| description | Galectin-3 (Gal-3) has been associated with heart failure (HF) and poor cardiovascular outcomes. However, the effect of longitudinal changes in Gal-3 on clinical outcomes remains unclear.
The authors sought to study clinical determinants of change in Gal-3 among community-dwelling individuals. Further, they sought to examine the role of serial Gal-3 measurements in predicting risk of future HF, cardiovascular disease (CVD), and mortality.
A total of 2,477 participants in the Framingham Heart Study Offspring cohort underwent measurement of plasma Gal-3 levels at 2 examinations (1995 to 1998 and 2005 to 2008). Linear regression models were used to examine clinical correlates of change in Gal-3. Proportional hazards models were used to relate future clinical outcomes with change in Gal-3.
The following clinical correlates were associated with greater longitudinal increases in Gal-3 levels: age, female sex, hypertension, diabetes, body mass index, interim development of chronic kidney disease, and HF (p < 0.0001 for all in multivariable model). Change in Gal-3 was associated with future HF (hazard ratio [HR]: 1.39 per 1-SD increase; 95% confidence interval [CI]: 1.13 to 1.71), CVD (HR: 1.29; 95% CI: 1.11 to 1.51), and all-cause mortality (HR: 1.30; 95% CI: 1.17 to 1.46). Change in Gal-3 was associated with both HF with preserved as well as reduced ejection fraction (p < 0.05 for both).
Longitudinal changes in Gal-3 are associated with traditional cardiovascular risk factors and renal disease. In turn, change in Gal-3 predicts future HF, CVD, and mortality in the community. Future studies are needed to determine whether serial Gal-3 measures may be useful in disease prevention.
[Display omitted] |
| doi_str_mv | 10.1016/j.jacc.2018.09.076 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_6516745</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S073510971838906X</els_id><sourcerecordid>2159984429</sourcerecordid><originalsourceid>FETCH-LOGICAL-c549t-a63f7dd03df5eae97a38992d89efe78804bdf7c6a1a872169effdf8bd7ff710f3</originalsourceid><addsrcrecordid>eNp9kV1rFDEUhoModq3-AS9kwBtvZkwmky8QQRZbCwu9aa_D2XxsM8wmNZlZ8N-bdWvRXvTqQM5zXk7Og9B7gjuCCf88diMY0_WYyA6rDgv-Aq0IY7KlTImXaIUFZS3BSpyhN6WMGGMuiXqNzihmguKer9DFJsVdmBcbIkzN-g7izjUhNpcwOTOH2NIGom2uognWxblZQ7YhHaCYZYLcXC-zSXtX3qJXHqbi3j3Uc3R78f1m_aPdXF9erb9tWsMGNbfAqRfWYmo9c-CUACqV6q1UzjshJR621gvDgYAUPeH12Vsvt1Z4Lwj29Bx9PeXeL9u9s6aulGHS9znsIf_SCYL-vxPDnd6lg-aMcDGwGvDpISCnn4srs96HYtw0QXRpKbonTCk5DL2q6Mcn6JiWXM_0hxKy54zzSvUnyuRUSnb-cRmC9VGTHvVRkz5q0ljpqqkOffj3G48jf71U4MsJcPWYh-CyLia4aJwNuXrRNoXn8n8Ds8KkxQ</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2157826566</pqid></control><display><type>article</type><title>Longitudinal Change in Galectin-3 and Incident Cardiovascular Outcomes</title><source>MEDLINE</source><source>Elsevier ScienceDirect Journals</source><source>Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals</source><source>Alma/SFX Local Collection</source><creator>Ghorbani, Anahita ; Bhambhani, Vijeta ; Christenson, Robert H. ; Meijers, Wouter C. ; de Boer, Rudolf A. ; Levy, Daniel ; Larson, Martin G. ; Ho, Jennifer E.</creator><creatorcontrib>Ghorbani, Anahita ; Bhambhani, Vijeta ; Christenson, Robert H. ; Meijers, Wouter C. ; de Boer, Rudolf A. ; Levy, Daniel ; Larson, Martin G. ; Ho, Jennifer E.</creatorcontrib><description>Galectin-3 (Gal-3) has been associated with heart failure (HF) and poor cardiovascular outcomes. However, the effect of longitudinal changes in Gal-3 on clinical outcomes remains unclear.
The authors sought to study clinical determinants of change in Gal-3 among community-dwelling individuals. Further, they sought to examine the role of serial Gal-3 measurements in predicting risk of future HF, cardiovascular disease (CVD), and mortality.
A total of 2,477 participants in the Framingham Heart Study Offspring cohort underwent measurement of plasma Gal-3 levels at 2 examinations (1995 to 1998 and 2005 to 2008). Linear regression models were used to examine clinical correlates of change in Gal-3. Proportional hazards models were used to relate future clinical outcomes with change in Gal-3.
The following clinical correlates were associated with greater longitudinal increases in Gal-3 levels: age, female sex, hypertension, diabetes, body mass index, interim development of chronic kidney disease, and HF (p < 0.0001 for all in multivariable model). Change in Gal-3 was associated with future HF (hazard ratio [HR]: 1.39 per 1-SD increase; 95% confidence interval [CI]: 1.13 to 1.71), CVD (HR: 1.29; 95% CI: 1.11 to 1.51), and all-cause mortality (HR: 1.30; 95% CI: 1.17 to 1.46). Change in Gal-3 was associated with both HF with preserved as well as reduced ejection fraction (p < 0.05 for both).
Longitudinal changes in Gal-3 are associated with traditional cardiovascular risk factors and renal disease. In turn, change in Gal-3 predicts future HF, CVD, and mortality in the community. Future studies are needed to determine whether serial Gal-3 measures may be useful in disease prevention.
[Display omitted]</description><identifier>ISSN: 0735-1097</identifier><identifier>ISSN: 1558-3597</identifier><identifier>EISSN: 1558-3597</identifier><identifier>DOI: 10.1016/j.jacc.2018.09.076</identifier><identifier>PMID: 30573026</identifier><language>eng</language><publisher>United States: Elsevier Inc</publisher><subject>Age ; Aged ; Binding sites ; biomarker ; Biomarkers - blood ; Blood pressure ; Blood Proteins ; Body mass ; Body mass index ; Body size ; Cardiology ; Cardiovascular disease ; Cardiovascular diseases ; Cardiovascular Diseases - blood ; Cardiovascular Diseases - diagnosis ; Cardiovascular Diseases - mortality ; change in galectin-3 ; Cholesterol ; Cohort Studies ; Communities ; Confidence intervals ; Diabetes ; Diabetes mellitus ; Enzymes ; Family medical history ; Female ; Galectin 3 - blood ; Galectin-3 ; Galectins ; Hazards ; Health risks ; Heart diseases ; Heart failure ; Humans ; Hypertension ; Incidence ; Kidney diseases ; Longitudinal Studies ; Male ; Middle Aged ; Mortality ; Mortality - trends ; Offspring ; Prospective Studies ; Regression analysis ; Risk analysis ; Risk factors ; Smoking ; Statistical analysis ; Statistical models ; Surveillance</subject><ispartof>Journal of the American College of Cardiology, 2018-12, Vol.72 (25), p.3246-3254</ispartof><rights>2018 American College of Cardiology Foundation</rights><rights>Copyright © 2018 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.</rights><rights>2018. American College of Cardiology Foundation</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c549t-a63f7dd03df5eae97a38992d89efe78804bdf7c6a1a872169effdf8bd7ff710f3</citedby><cites>FETCH-LOGICAL-c549t-a63f7dd03df5eae97a38992d89efe78804bdf7c6a1a872169effdf8bd7ff710f3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S073510971838906X$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>230,314,776,780,881,3536,27903,27904,65309</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/30573026$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Ghorbani, Anahita</creatorcontrib><creatorcontrib>Bhambhani, Vijeta</creatorcontrib><creatorcontrib>Christenson, Robert H.</creatorcontrib><creatorcontrib>Meijers, Wouter C.</creatorcontrib><creatorcontrib>de Boer, Rudolf A.</creatorcontrib><creatorcontrib>Levy, Daniel</creatorcontrib><creatorcontrib>Larson, Martin G.</creatorcontrib><creatorcontrib>Ho, Jennifer E.</creatorcontrib><title>Longitudinal Change in Galectin-3 and Incident Cardiovascular Outcomes</title><title>Journal of the American College of Cardiology</title><addtitle>J Am Coll Cardiol</addtitle><description>Galectin-3 (Gal-3) has been associated with heart failure (HF) and poor cardiovascular outcomes. However, the effect of longitudinal changes in Gal-3 on clinical outcomes remains unclear.
The authors sought to study clinical determinants of change in Gal-3 among community-dwelling individuals. Further, they sought to examine the role of serial Gal-3 measurements in predicting risk of future HF, cardiovascular disease (CVD), and mortality.
A total of 2,477 participants in the Framingham Heart Study Offspring cohort underwent measurement of plasma Gal-3 levels at 2 examinations (1995 to 1998 and 2005 to 2008). Linear regression models were used to examine clinical correlates of change in Gal-3. Proportional hazards models were used to relate future clinical outcomes with change in Gal-3.
The following clinical correlates were associated with greater longitudinal increases in Gal-3 levels: age, female sex, hypertension, diabetes, body mass index, interim development of chronic kidney disease, and HF (p < 0.0001 for all in multivariable model). Change in Gal-3 was associated with future HF (hazard ratio [HR]: 1.39 per 1-SD increase; 95% confidence interval [CI]: 1.13 to 1.71), CVD (HR: 1.29; 95% CI: 1.11 to 1.51), and all-cause mortality (HR: 1.30; 95% CI: 1.17 to 1.46). Change in Gal-3 was associated with both HF with preserved as well as reduced ejection fraction (p < 0.05 for both).
Longitudinal changes in Gal-3 are associated with traditional cardiovascular risk factors and renal disease. In turn, change in Gal-3 predicts future HF, CVD, and mortality in the community. Future studies are needed to determine whether serial Gal-3 measures may be useful in disease prevention.
[Display omitted]</description><subject>Age</subject><subject>Aged</subject><subject>Binding sites</subject><subject>biomarker</subject><subject>Biomarkers - blood</subject><subject>Blood pressure</subject><subject>Blood Proteins</subject><subject>Body mass</subject><subject>Body mass index</subject><subject>Body size</subject><subject>Cardiology</subject><subject>Cardiovascular disease</subject><subject>Cardiovascular diseases</subject><subject>Cardiovascular Diseases - blood</subject><subject>Cardiovascular Diseases - diagnosis</subject><subject>Cardiovascular Diseases - mortality</subject><subject>change in galectin-3</subject><subject>Cholesterol</subject><subject>Cohort Studies</subject><subject>Communities</subject><subject>Confidence intervals</subject><subject>Diabetes</subject><subject>Diabetes mellitus</subject><subject>Enzymes</subject><subject>Family medical history</subject><subject>Female</subject><subject>Galectin 3 - blood</subject><subject>Galectin-3</subject><subject>Galectins</subject><subject>Hazards</subject><subject>Health risks</subject><subject>Heart diseases</subject><subject>Heart failure</subject><subject>Humans</subject><subject>Hypertension</subject><subject>Incidence</subject><subject>Kidney diseases</subject><subject>Longitudinal Studies</subject><subject>Male</subject><subject>Middle Aged</subject><subject>Mortality</subject><subject>Mortality - trends</subject><subject>Offspring</subject><subject>Prospective Studies</subject><subject>Regression analysis</subject><subject>Risk analysis</subject><subject>Risk factors</subject><subject>Smoking</subject><subject>Statistical analysis</subject><subject>Statistical models</subject><subject>Surveillance</subject><issn>0735-1097</issn><issn>1558-3597</issn><issn>1558-3597</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9kV1rFDEUhoModq3-AS9kwBtvZkwmky8QQRZbCwu9aa_D2XxsM8wmNZlZ8N-bdWvRXvTqQM5zXk7Og9B7gjuCCf88diMY0_WYyA6rDgv-Aq0IY7KlTImXaIUFZS3BSpyhN6WMGGMuiXqNzihmguKer9DFJsVdmBcbIkzN-g7izjUhNpcwOTOH2NIGom2uognWxblZQ7YhHaCYZYLcXC-zSXtX3qJXHqbi3j3Uc3R78f1m_aPdXF9erb9tWsMGNbfAqRfWYmo9c-CUACqV6q1UzjshJR621gvDgYAUPeH12Vsvt1Z4Lwj29Bx9PeXeL9u9s6aulGHS9znsIf_SCYL-vxPDnd6lg-aMcDGwGvDpISCnn4srs96HYtw0QXRpKbonTCk5DL2q6Mcn6JiWXM_0hxKy54zzSvUnyuRUSnb-cRmC9VGTHvVRkz5q0ljpqqkOffj3G48jf71U4MsJcPWYh-CyLia4aJwNuXrRNoXn8n8Ds8KkxQ</recordid><startdate>20181225</startdate><enddate>20181225</enddate><creator>Ghorbani, Anahita</creator><creator>Bhambhani, Vijeta</creator><creator>Christenson, Robert H.</creator><creator>Meijers, Wouter C.</creator><creator>de Boer, Rudolf A.</creator><creator>Levy, Daniel</creator><creator>Larson, Martin G.</creator><creator>Ho, Jennifer E.</creator><general>Elsevier Inc</general><general>Elsevier Limited</general><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>7T5</scope><scope>7TK</scope><scope>H94</scope><scope>K9.</scope><scope>NAPCQ</scope><scope>7X8</scope><scope>5PM</scope></search><sort><creationdate>20181225</creationdate><title>Longitudinal Change in Galectin-3 and Incident Cardiovascular Outcomes</title><author>Ghorbani, Anahita ; Bhambhani, Vijeta ; Christenson, Robert H. ; Meijers, Wouter C. ; de Boer, Rudolf A. ; Levy, Daniel ; Larson, Martin G. ; Ho, Jennifer E.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c549t-a63f7dd03df5eae97a38992d89efe78804bdf7c6a1a872169effdf8bd7ff710f3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Age</topic><topic>Aged</topic><topic>Binding sites</topic><topic>biomarker</topic><topic>Biomarkers - blood</topic><topic>Blood pressure</topic><topic>Blood Proteins</topic><topic>Body mass</topic><topic>Body mass index</topic><topic>Body size</topic><topic>Cardiology</topic><topic>Cardiovascular disease</topic><topic>Cardiovascular diseases</topic><topic>Cardiovascular Diseases - blood</topic><topic>Cardiovascular Diseases - diagnosis</topic><topic>Cardiovascular Diseases - mortality</topic><topic>change in galectin-3</topic><topic>Cholesterol</topic><topic>Cohort Studies</topic><topic>Communities</topic><topic>Confidence intervals</topic><topic>Diabetes</topic><topic>Diabetes mellitus</topic><topic>Enzymes</topic><topic>Family medical history</topic><topic>Female</topic><topic>Galectin 3 - blood</topic><topic>Galectin-3</topic><topic>Galectins</topic><topic>Hazards</topic><topic>Health risks</topic><topic>Heart diseases</topic><topic>Heart failure</topic><topic>Humans</topic><topic>Hypertension</topic><topic>Incidence</topic><topic>Kidney diseases</topic><topic>Longitudinal Studies</topic><topic>Male</topic><topic>Middle Aged</topic><topic>Mortality</topic><topic>Mortality - trends</topic><topic>Offspring</topic><topic>Prospective Studies</topic><topic>Regression analysis</topic><topic>Risk analysis</topic><topic>Risk factors</topic><topic>Smoking</topic><topic>Statistical analysis</topic><topic>Statistical models</topic><topic>Surveillance</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ghorbani, Anahita</creatorcontrib><creatorcontrib>Bhambhani, Vijeta</creatorcontrib><creatorcontrib>Christenson, Robert H.</creatorcontrib><creatorcontrib>Meijers, Wouter C.</creatorcontrib><creatorcontrib>de Boer, Rudolf A.</creatorcontrib><creatorcontrib>Levy, Daniel</creatorcontrib><creatorcontrib>Larson, Martin G.</creatorcontrib><creatorcontrib>Ho, Jennifer E.</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Immunology Abstracts</collection><collection>Neurosciences Abstracts</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Premium</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Journal of the American College of Cardiology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ghorbani, Anahita</au><au>Bhambhani, Vijeta</au><au>Christenson, Robert H.</au><au>Meijers, Wouter C.</au><au>de Boer, Rudolf A.</au><au>Levy, Daniel</au><au>Larson, Martin G.</au><au>Ho, Jennifer E.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Longitudinal Change in Galectin-3 and Incident Cardiovascular Outcomes</atitle><jtitle>Journal of the American College of Cardiology</jtitle><addtitle>J Am Coll Cardiol</addtitle><date>2018-12-25</date><risdate>2018</risdate><volume>72</volume><issue>25</issue><spage>3246</spage><epage>3254</epage><pages>3246-3254</pages><issn>0735-1097</issn><issn>1558-3597</issn><eissn>1558-3597</eissn><abstract>Galectin-3 (Gal-3) has been associated with heart failure (HF) and poor cardiovascular outcomes. However, the effect of longitudinal changes in Gal-3 on clinical outcomes remains unclear.
The authors sought to study clinical determinants of change in Gal-3 among community-dwelling individuals. Further, they sought to examine the role of serial Gal-3 measurements in predicting risk of future HF, cardiovascular disease (CVD), and mortality.
A total of 2,477 participants in the Framingham Heart Study Offspring cohort underwent measurement of plasma Gal-3 levels at 2 examinations (1995 to 1998 and 2005 to 2008). Linear regression models were used to examine clinical correlates of change in Gal-3. Proportional hazards models were used to relate future clinical outcomes with change in Gal-3.
The following clinical correlates were associated with greater longitudinal increases in Gal-3 levels: age, female sex, hypertension, diabetes, body mass index, interim development of chronic kidney disease, and HF (p < 0.0001 for all in multivariable model). Change in Gal-3 was associated with future HF (hazard ratio [HR]: 1.39 per 1-SD increase; 95% confidence interval [CI]: 1.13 to 1.71), CVD (HR: 1.29; 95% CI: 1.11 to 1.51), and all-cause mortality (HR: 1.30; 95% CI: 1.17 to 1.46). Change in Gal-3 was associated with both HF with preserved as well as reduced ejection fraction (p < 0.05 for both).
Longitudinal changes in Gal-3 are associated with traditional cardiovascular risk factors and renal disease. In turn, change in Gal-3 predicts future HF, CVD, and mortality in the community. Future studies are needed to determine whether serial Gal-3 measures may be useful in disease prevention.
[Display omitted]</abstract><cop>United States</cop><pub>Elsevier Inc</pub><pmid>30573026</pmid><doi>10.1016/j.jacc.2018.09.076</doi><tpages>9</tpages><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0735-1097 |
| ispartof | Journal of the American College of Cardiology, 2018-12, Vol.72 (25), p.3246-3254 |
| issn | 0735-1097 1558-3597 1558-3597 |
| language | eng |
| recordid | cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_6516745 |
| source | MEDLINE; Elsevier ScienceDirect Journals; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; Alma/SFX Local Collection |
| subjects | Age Aged Binding sites biomarker Biomarkers - blood Blood pressure Blood Proteins Body mass Body mass index Body size Cardiology Cardiovascular disease Cardiovascular diseases Cardiovascular Diseases - blood Cardiovascular Diseases - diagnosis Cardiovascular Diseases - mortality change in galectin-3 Cholesterol Cohort Studies Communities Confidence intervals Diabetes Diabetes mellitus Enzymes Family medical history Female Galectin 3 - blood Galectin-3 Galectins Hazards Health risks Heart diseases Heart failure Humans Hypertension Incidence Kidney diseases Longitudinal Studies Male Middle Aged Mortality Mortality - trends Offspring Prospective Studies Regression analysis Risk analysis Risk factors Smoking Statistical analysis Statistical models Surveillance |
| title | Longitudinal Change in Galectin-3 and Incident Cardiovascular Outcomes |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-26T03%3A57%3A13IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_pubme&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Longitudinal%20Change%20in%20Galectin-3%20and%20Incident%20Cardiovascular%20Outcomes&rft.jtitle=Journal%20of%20the%20American%20College%20of%20Cardiology&rft.au=Ghorbani,%20Anahita&rft.date=2018-12-25&rft.volume=72&rft.issue=25&rft.spage=3246&rft.epage=3254&rft.pages=3246-3254&rft.issn=0735-1097&rft.eissn=1558-3597&rft_id=info:doi/10.1016/j.jacc.2018.09.076&rft_dat=%3Cproquest_pubme%3E2159984429%3C/proquest_pubme%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2157826566&rft_id=info:pmid/30573026&rft_els_id=S073510971838906X&rfr_iscdi=true |