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C2HEST score predicts clinical outcomes in heart failure with preserved ejection fraction: a secondary analysis of the TOPCAT trial
Background The C.sub.2HEST score has been validated for predicting AF in the general population or post-stroke patients. We aimed to assess whether this risk score could predict incident AF and other clinical outcomes in heart failure with preserved ejection fraction (HFpEF) patients. Methods A tota...
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description | Background The C.sub.2HEST score has been validated for predicting AF in the general population or post-stroke patients. We aimed to assess whether this risk score could predict incident AF and other clinical outcomes in heart failure with preserved ejection fraction (HFpEF) patients. Methods A total of 2202 HFpEF patients without baseline AF in the TOPCAT trial were stratified by baseline C.sub.2HEST score. Cox proportional hazard model and competing risk regression model was used to explore the relationship between C.sub.2HEST score and outcomes, including incident AF, stroke, all-cause death, cardiovascular death, any hospitalization, and HF hospitalization. The discriminative ability of the C.sub.2HEST score for various outcomes was assessed by calculating the area under the curve (AUC). Results The incidence rates of incident AF, stroke, all-cause death, cardiovascular death, any hospitalization, and HF hospitalization were 1.79, 0.70, 3.81, 2.42, 15.50, and 3.32 per 100 person-years, respectively. When the C.sub.2HEST score was analyzed as a continuous variable, increased C.sub.2HEST score was associated with increased risk of incident AF (HR 1.50, 95% CI 1.29-1.75), as well as increased risks of all-cause death, cardiovascular death, any hospitalization, and HF hospitalization. The AUC for the C.sub.2HEST score in predicting incident AF (0.694, 95% CI 0.640-0.748) was higher than all-cause death, cardiovascular death, any hospitalization, or HF hospitalization. Conclusions The C.sub.2HEST score could predict the risk of incident AF as well as death and hospitalization with moderately good predictive abilities in patients with HFpEF. Its simplicity may allow the possibility of quick risk assessments in busy clinical settings. Keywords: Heart failure, Atrial fibrillation, Risk prediction, Outcomes |
doi_str_mv | 10.1186/s12916-021-01921-w |
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H ; Zhu, Wengen ; Liu, Chen</creator><creatorcontrib>Liang, Weihao ; Wu, Yuzhong ; Xue, Ruicong ; Wu, Zexuan ; Wu, Dexi ; He, Jiangui ; Dong, Yugang ; Lip, Gregory Y. H ; Zhu, Wengen ; Liu, Chen</creatorcontrib><description>Background The C.sub.2HEST score has been validated for predicting AF in the general population or post-stroke patients. We aimed to assess whether this risk score could predict incident AF and other clinical outcomes in heart failure with preserved ejection fraction (HFpEF) patients. Methods A total of 2202 HFpEF patients without baseline AF in the TOPCAT trial were stratified by baseline C.sub.2HEST score. Cox proportional hazard model and competing risk regression model was used to explore the relationship between C.sub.2HEST score and outcomes, including incident AF, stroke, all-cause death, cardiovascular death, any hospitalization, and HF hospitalization. The discriminative ability of the C.sub.2HEST score for various outcomes was assessed by calculating the area under the curve (AUC). Results The incidence rates of incident AF, stroke, all-cause death, cardiovascular death, any hospitalization, and HF hospitalization were 1.79, 0.70, 3.81, 2.42, 15.50, and 3.32 per 100 person-years, respectively. When the C.sub.2HEST score was analyzed as a continuous variable, increased C.sub.2HEST score was associated with increased risk of incident AF (HR 1.50, 95% CI 1.29-1.75), as well as increased risks of all-cause death, cardiovascular death, any hospitalization, and HF hospitalization. The AUC for the C.sub.2HEST score in predicting incident AF (0.694, 95% CI 0.640-0.748) was higher than all-cause death, cardiovascular death, any hospitalization, or HF hospitalization. Conclusions The C.sub.2HEST score could predict the risk of incident AF as well as death and hospitalization with moderately good predictive abilities in patients with HFpEF. Its simplicity may allow the possibility of quick risk assessments in busy clinical settings. Keywords: Heart failure, Atrial fibrillation, Risk prediction, Outcomes</description><identifier>ISSN: 1741-7015</identifier><identifier>EISSN: 1741-7015</identifier><identifier>DOI: 10.1186/s12916-021-01921-w</identifier><identifier>PMID: 33596909</identifier><language>eng</language><publisher>London: BioMed Central Ltd</publisher><subject>Age ; Atrial fibrillation ; Blood pressure ; Body mass index ; Cardiac arrhythmia ; Cardiovascular disease ; Chronic obstructive pulmonary disease ; Clinical outcomes ; Congestive heart failure ; Continuity (mathematics) ; Coronary vessels ; Datasets ; Death ; Ejection fraction ; Enrollments ; Function tests (Medicine) ; Heart failure ; Heart rate ; Hospitalization ; Hypertension ; Hyperthyroidism ; Medical prognosis ; Mortality ; Outcomes ; Patient outcomes ; Patients ; Practice guidelines (Medicine) ; Prognosis ; Regression analysis ; Regression models ; Risk assessment ; Risk prediction ; Secondary analysis ; Sensitivity analysis ; Statistical models ; Stroke</subject><ispartof>BMC medicine, 2021-02, Vol.19 (1), p.1-44, Article 44</ispartof><rights>COPYRIGHT 2021 BioMed Central Ltd.</rights><rights>2021. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>The Author(s) 2021</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c571t-74826349dffd51090c668ab44721507365aaac680cb3516e316d601dacca17143</citedby><cites>FETCH-LOGICAL-c571t-74826349dffd51090c668ab44721507365aaac680cb3516e316d601dacca17143</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC7890599/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2490939730?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,25753,27924,27925,37012,37013,44590,53791,53793</link.rule.ids></links><search><creatorcontrib>Liang, Weihao</creatorcontrib><creatorcontrib>Wu, Yuzhong</creatorcontrib><creatorcontrib>Xue, Ruicong</creatorcontrib><creatorcontrib>Wu, Zexuan</creatorcontrib><creatorcontrib>Wu, Dexi</creatorcontrib><creatorcontrib>He, Jiangui</creatorcontrib><creatorcontrib>Dong, Yugang</creatorcontrib><creatorcontrib>Lip, Gregory Y. H</creatorcontrib><creatorcontrib>Zhu, Wengen</creatorcontrib><creatorcontrib>Liu, Chen</creatorcontrib><title>C2HEST score predicts clinical outcomes in heart failure with preserved ejection fraction: a secondary analysis of the TOPCAT trial</title><title>BMC medicine</title><description>Background The C.sub.2HEST score has been validated for predicting AF in the general population or post-stroke patients. We aimed to assess whether this risk score could predict incident AF and other clinical outcomes in heart failure with preserved ejection fraction (HFpEF) patients. Methods A total of 2202 HFpEF patients without baseline AF in the TOPCAT trial were stratified by baseline C.sub.2HEST score. Cox proportional hazard model and competing risk regression model was used to explore the relationship between C.sub.2HEST score and outcomes, including incident AF, stroke, all-cause death, cardiovascular death, any hospitalization, and HF hospitalization. The discriminative ability of the C.sub.2HEST score for various outcomes was assessed by calculating the area under the curve (AUC). Results The incidence rates of incident AF, stroke, all-cause death, cardiovascular death, any hospitalization, and HF hospitalization were 1.79, 0.70, 3.81, 2.42, 15.50, and 3.32 per 100 person-years, respectively. When the C.sub.2HEST score was analyzed as a continuous variable, increased C.sub.2HEST score was associated with increased risk of incident AF (HR 1.50, 95% CI 1.29-1.75), as well as increased risks of all-cause death, cardiovascular death, any hospitalization, and HF hospitalization. The AUC for the C.sub.2HEST score in predicting incident AF (0.694, 95% CI 0.640-0.748) was higher than all-cause death, cardiovascular death, any hospitalization, or HF hospitalization. Conclusions The C.sub.2HEST score could predict the risk of incident AF as well as death and hospitalization with moderately good predictive abilities in patients with HFpEF. Its simplicity may allow the possibility of quick risk assessments in busy clinical settings. Keywords: Heart failure, Atrial fibrillation, Risk prediction, Outcomes</description><subject>Age</subject><subject>Atrial fibrillation</subject><subject>Blood pressure</subject><subject>Body mass index</subject><subject>Cardiac arrhythmia</subject><subject>Cardiovascular disease</subject><subject>Chronic obstructive pulmonary disease</subject><subject>Clinical outcomes</subject><subject>Congestive heart failure</subject><subject>Continuity (mathematics)</subject><subject>Coronary vessels</subject><subject>Datasets</subject><subject>Death</subject><subject>Ejection fraction</subject><subject>Enrollments</subject><subject>Function tests (Medicine)</subject><subject>Heart failure</subject><subject>Heart rate</subject><subject>Hospitalization</subject><subject>Hypertension</subject><subject>Hyperthyroidism</subject><subject>Medical prognosis</subject><subject>Mortality</subject><subject>Outcomes</subject><subject>Patient outcomes</subject><subject>Patients</subject><subject>Practice guidelines (Medicine)</subject><subject>Prognosis</subject><subject>Regression analysis</subject><subject>Regression models</subject><subject>Risk assessment</subject><subject>Risk prediction</subject><subject>Secondary analysis</subject><subject>Sensitivity analysis</subject><subject>Statistical models</subject><subject>Stroke</subject><issn>1741-7015</issn><issn>1741-7015</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNptklFrFDEQxxdRbK1-AZ8CgviydWazm2x8EI6j2kKhgudzyCXZ2xy5zZns9uizX9zcXdGeSCAZJr_5J5P8i-ItwiViyz4mrASyEiosAUWed8-Kc-Q1lhywef4kPitepbQGqBrO65fFGaWNYALEefFrXl1ffV-QpEO0ZButcXpMRHs3OK08CdOow8Ym4gbSWxVH0innp8zu3NjvC5KN99YQu7Z6dGEgXVSH4BNRJFkdBqPiA1GD8g_JJRI6MvaWLO6-zWcLMkan_OviRad8sm8e14vix5erxfy6vL37ejOf3Za64TiWvG4rRmthus40CAI0Y61a1jWvsAFOWaOU0qwFvaQNMkuRGQZolNYKOdb0org56pqg1nIb3SbfTAbl5CER4krmBp32VhohhBa0a4RRNUOrhG61AWAaKs0ryFqfj1rbabmxRtthjMqfiJ7uDK6Xq3AveSugESILfHgUiOHnZNMoNy5p670abJiSrGqBwBEozei7f9B1mGJ-0AMFggpO4S-1UrkBN3Qhn6v3onLGGsqQImCmLv9D5WHsxuXPsp3L-ZOC908KsgX82Kfgp_0Xp1OwOoI6hpSi7f48BoLc-1Ue_SqzX-XBr3JHfwOFw9pD</recordid><startdate>20210218</startdate><enddate>20210218</enddate><creator>Liang, Weihao</creator><creator>Wu, Yuzhong</creator><creator>Xue, Ruicong</creator><creator>Wu, Zexuan</creator><creator>Wu, Dexi</creator><creator>He, Jiangui</creator><creator>Dong, Yugang</creator><creator>Lip, Gregory Y. H</creator><creator>Zhu, Wengen</creator><creator>Liu, Chen</creator><general>BioMed Central Ltd</general><general>BioMed Central</general><general>BMC</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7QL</scope><scope>7U9</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>H94</scope><scope>K9.</scope><scope>M0S</scope><scope>M1P</scope><scope>M7N</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope></search><sort><creationdate>20210218</creationdate><title>C2HEST score predicts clinical outcomes in heart failure with preserved ejection fraction: a secondary analysis of the TOPCAT trial</title><author>Liang, Weihao ; Wu, Yuzhong ; Xue, Ruicong ; Wu, Zexuan ; Wu, Dexi ; He, Jiangui ; Dong, Yugang ; Lip, Gregory Y. H ; Zhu, Wengen ; Liu, Chen</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c571t-74826349dffd51090c668ab44721507365aaac680cb3516e316d601dacca17143</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Age</topic><topic>Atrial fibrillation</topic><topic>Blood pressure</topic><topic>Body mass index</topic><topic>Cardiac arrhythmia</topic><topic>Cardiovascular disease</topic><topic>Chronic obstructive pulmonary disease</topic><topic>Clinical outcomes</topic><topic>Congestive heart failure</topic><topic>Continuity (mathematics)</topic><topic>Coronary vessels</topic><topic>Datasets</topic><topic>Death</topic><topic>Ejection fraction</topic><topic>Enrollments</topic><topic>Function tests (Medicine)</topic><topic>Heart failure</topic><topic>Heart rate</topic><topic>Hospitalization</topic><topic>Hypertension</topic><topic>Hyperthyroidism</topic><topic>Medical prognosis</topic><topic>Mortality</topic><topic>Outcomes</topic><topic>Patient outcomes</topic><topic>Patients</topic><topic>Practice guidelines (Medicine)</topic><topic>Prognosis</topic><topic>Regression analysis</topic><topic>Regression models</topic><topic>Risk assessment</topic><topic>Risk prediction</topic><topic>Secondary analysis</topic><topic>Sensitivity analysis</topic><topic>Statistical models</topic><topic>Stroke</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Liang, Weihao</creatorcontrib><creatorcontrib>Wu, Yuzhong</creatorcontrib><creatorcontrib>Xue, Ruicong</creatorcontrib><creatorcontrib>Wu, Zexuan</creatorcontrib><creatorcontrib>Wu, Dexi</creatorcontrib><creatorcontrib>He, Jiangui</creatorcontrib><creatorcontrib>Dong, Yugang</creatorcontrib><creatorcontrib>Lip, Gregory Y. H</creatorcontrib><creatorcontrib>Zhu, Wengen</creatorcontrib><creatorcontrib>Liu, Chen</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Virology and AIDS Abstracts</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</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 Central</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</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>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>Open Access: DOAJ - Directory of Open Access Journals</collection><jtitle>BMC medicine</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Liang, Weihao</au><au>Wu, Yuzhong</au><au>Xue, Ruicong</au><au>Wu, Zexuan</au><au>Wu, Dexi</au><au>He, Jiangui</au><au>Dong, Yugang</au><au>Lip, Gregory Y. H</au><au>Zhu, Wengen</au><au>Liu, Chen</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>C2HEST score predicts clinical outcomes in heart failure with preserved ejection fraction: a secondary analysis of the TOPCAT trial</atitle><jtitle>BMC medicine</jtitle><date>2021-02-18</date><risdate>2021</risdate><volume>19</volume><issue>1</issue><spage>1</spage><epage>44</epage><pages>1-44</pages><artnum>44</artnum><issn>1741-7015</issn><eissn>1741-7015</eissn><abstract>Background The C.sub.2HEST score has been validated for predicting AF in the general population or post-stroke patients. We aimed to assess whether this risk score could predict incident AF and other clinical outcomes in heart failure with preserved ejection fraction (HFpEF) patients. Methods A total of 2202 HFpEF patients without baseline AF in the TOPCAT trial were stratified by baseline C.sub.2HEST score. Cox proportional hazard model and competing risk regression model was used to explore the relationship between C.sub.2HEST score and outcomes, including incident AF, stroke, all-cause death, cardiovascular death, any hospitalization, and HF hospitalization. The discriminative ability of the C.sub.2HEST score for various outcomes was assessed by calculating the area under the curve (AUC). Results The incidence rates of incident AF, stroke, all-cause death, cardiovascular death, any hospitalization, and HF hospitalization were 1.79, 0.70, 3.81, 2.42, 15.50, and 3.32 per 100 person-years, respectively. When the C.sub.2HEST score was analyzed as a continuous variable, increased C.sub.2HEST score was associated with increased risk of incident AF (HR 1.50, 95% CI 1.29-1.75), as well as increased risks of all-cause death, cardiovascular death, any hospitalization, and HF hospitalization. The AUC for the C.sub.2HEST score in predicting incident AF (0.694, 95% CI 0.640-0.748) was higher than all-cause death, cardiovascular death, any hospitalization, or HF hospitalization. Conclusions The C.sub.2HEST score could predict the risk of incident AF as well as death and hospitalization with moderately good predictive abilities in patients with HFpEF. Its simplicity may allow the possibility of quick risk assessments in busy clinical settings. Keywords: Heart failure, Atrial fibrillation, Risk prediction, Outcomes</abstract><cop>London</cop><pub>BioMed Central Ltd</pub><pmid>33596909</pmid><doi>10.1186/s12916-021-01921-w</doi><oa>free_for_read</oa></addata></record> |
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subjects | Age Atrial fibrillation Blood pressure Body mass index Cardiac arrhythmia Cardiovascular disease Chronic obstructive pulmonary disease Clinical outcomes Congestive heart failure Continuity (mathematics) Coronary vessels Datasets Death Ejection fraction Enrollments Function tests (Medicine) Heart failure Heart rate Hospitalization Hypertension Hyperthyroidism Medical prognosis Mortality Outcomes Patient outcomes Patients Practice guidelines (Medicine) Prognosis Regression analysis Regression models Risk assessment Risk prediction Secondary analysis Sensitivity analysis Statistical models Stroke |
title | C2HEST score predicts clinical outcomes in heart failure with preserved ejection fraction: a secondary analysis of the TOPCAT trial |
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