Mortality risk prediction in high-risk patients undergoing coronary artery bypass grafting: Are traditional risk scores accurate?
The performance of traditional scores is significantly limited to predict mortality in high-risk cardiac surgery. The aim of this study was to compare the performance of STS, ESII and HiriSCORE models in predicting mortality in high-risk patients undergoing CABG. Cross-sectional analysis in the inte...
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Veröffentlicht in: | PloS one 2021-08, Vol.16 (8), p.e0255662-e0255662 |
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creator | Goncharov, Maxim Mejia, Omar Asdrúbal Vilca Arthur, Camila Perez de Souza Orlandi, Bianca Maria Maglia Sousa, Alexandre Oliveira, Marco Antônio Praça Atik, Fernando Antibas Segalote, Rodrigo Coelho Tiveron, Marcos Gradim de Barros E Silva, Pedro Gabriel Melo Nakazone, Marcelo Arruda Lisboa, Luiz Augusto Ferreira Dallan, Luís Alberto Oliveira Zheng, Zhe Hu, Shengshou Jatene, Fabio Biscegli |
description | The performance of traditional scores is significantly limited to predict mortality in high-risk cardiac surgery. The aim of this study was to compare the performance of STS, ESII and HiriSCORE models in predicting mortality in high-risk patients undergoing CABG.
Cross-sectional analysis in the international prospective database of high-risk patients: HiriSCORE project. We evaluated 248 patients with STS or ESII (5-10%) undergoing CABG in 8 hospitals in Brazil and China. The main outcome was mortality, defined as all deaths occurred during the hospitalization in which the operation was performed, even after 30 days. Five variables were selected as predictors of mortality in this cohort of patients. The model's performance was evaluated through the calibration-in-the-large and the receiver operating curve (ROC) tests.
The mean age was 69.90±9.45, with 52.02% being female, 25% of the patients were on New York Heart Association (NYHA) class IV and 49.6% had Canadian Cardiovascular Society (CCS) class 4 angina, and 85.5% had urgency or emergency status. The mortality observed in the sample was 13.31%. The HiriSCORE model showed better calibration (15.0%) compared to ESII (6.6%) and the STS model (2.0%). In the ROC curve, the HiriSCORE model showed better accuracy (ROC = 0.74) than the traditional models STS (ROC = 0.67) and ESII (ROC = 0.50).
Traditional models were inadequate to predict mortality of high-risk patients undergoing CABG. However, the HiriSCORE model was simple and accurate to predict mortality in high-risk patients. |
doi_str_mv | 10.1371/journal.pone.0255662 |
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Cross-sectional analysis in the international prospective database of high-risk patients: HiriSCORE project. We evaluated 248 patients with STS or ESII (5-10%) undergoing CABG in 8 hospitals in Brazil and China. The main outcome was mortality, defined as all deaths occurred during the hospitalization in which the operation was performed, even after 30 days. Five variables were selected as predictors of mortality in this cohort of patients. The model's performance was evaluated through the calibration-in-the-large and the receiver operating curve (ROC) tests.
The mean age was 69.90±9.45, with 52.02% being female, 25% of the patients were on New York Heart Association (NYHA) class IV and 49.6% had Canadian Cardiovascular Society (CCS) class 4 angina, and 85.5% had urgency or emergency status. The mortality observed in the sample was 13.31%. The HiriSCORE model showed better calibration (15.0%) compared to ESII (6.6%) and the STS model (2.0%). In the ROC curve, the HiriSCORE model showed better accuracy (ROC = 0.74) than the traditional models STS (ROC = 0.67) and ESII (ROC = 0.50).
Traditional models were inadequate to predict mortality of high-risk patients undergoing CABG. However, the HiriSCORE model was simple and accurate to predict mortality in high-risk patients.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0255662</identifier><identifier>PMID: 34343224</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Aged ; Angina ; Area Under Curve ; Biology and Life Sciences ; Brazil - epidemiology ; Calibration ; Cardiac patients ; Cardiovascular diseases ; Care and treatment ; China - epidemiology ; Complications and side effects ; Coronary artery ; Coronary artery bypass ; Coronary Artery Bypass - adverse effects ; Coronary Artery Disease - epidemiology ; Coronary Artery Disease - mortality ; Coronary Artery Disease - surgery ; Cross-Sectional Studies ; Databases, Factual ; Female ; Health risks ; Heart attacks ; Heart surgery ; Hospital Mortality ; Humans ; Male ; Medicine and Health Sciences ; Middle Aged ; Model accuracy ; Models, Statistical ; Mortality ; Patient outcomes ; Patients ; Performance evaluation ; Prognosis ; Prospective Studies ; Risk ; Risk Assessment ; Risk Factors ; Risk groups ; ROC Curve ; Treatment Outcome ; Variables</subject><ispartof>PloS one, 2021-08, Vol.16 (8), p.e0255662-e0255662</ispartof><rights>COPYRIGHT 2021 Public Library of Science</rights><rights>2021 Goncharov et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2021 Goncharov et al 2021 Goncharov et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c692t-69303151efd50f3708f11cde2b817cb95bf98b7db60b31c3667415cfa471552f3</citedby><cites>FETCH-LOGICAL-c692t-69303151efd50f3708f11cde2b817cb95bf98b7db60b31c3667415cfa471552f3</cites><orcidid>0000-0002-4672-6494 ; 0000-0002-2310-5310 ; 0000-0002-0449-7056 ; 0000-0002-1635-4984 ; 0000-0003-1940-4470</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8330943/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8330943/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,864,885,2102,2928,23866,27924,27925,53791,53793</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/34343224$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Deo, Salil</contributor><creatorcontrib>Goncharov, Maxim</creatorcontrib><creatorcontrib>Mejia, Omar Asdrúbal Vilca</creatorcontrib><creatorcontrib>Arthur, Camila Perez de Souza</creatorcontrib><creatorcontrib>Orlandi, Bianca Maria Maglia</creatorcontrib><creatorcontrib>Sousa, Alexandre</creatorcontrib><creatorcontrib>Oliveira, Marco Antônio Praça</creatorcontrib><creatorcontrib>Atik, Fernando Antibas</creatorcontrib><creatorcontrib>Segalote, Rodrigo Coelho</creatorcontrib><creatorcontrib>Tiveron, Marcos Gradim</creatorcontrib><creatorcontrib>de Barros E Silva, Pedro Gabriel Melo</creatorcontrib><creatorcontrib>Nakazone, Marcelo Arruda</creatorcontrib><creatorcontrib>Lisboa, Luiz Augusto Ferreira</creatorcontrib><creatorcontrib>Dallan, Luís Alberto Oliveira</creatorcontrib><creatorcontrib>Zheng, Zhe</creatorcontrib><creatorcontrib>Hu, Shengshou</creatorcontrib><creatorcontrib>Jatene, Fabio Biscegli</creatorcontrib><title>Mortality risk prediction in high-risk patients undergoing coronary artery bypass grafting: Are traditional risk scores accurate?</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>The performance of traditional scores is significantly limited to predict mortality in high-risk cardiac surgery. The aim of this study was to compare the performance of STS, ESII and HiriSCORE models in predicting mortality in high-risk patients undergoing CABG.
Cross-sectional analysis in the international prospective database of high-risk patients: HiriSCORE project. We evaluated 248 patients with STS or ESII (5-10%) undergoing CABG in 8 hospitals in Brazil and China. The main outcome was mortality, defined as all deaths occurred during the hospitalization in which the operation was performed, even after 30 days. Five variables were selected as predictors of mortality in this cohort of patients. The model's performance was evaluated through the calibration-in-the-large and the receiver operating curve (ROC) tests.
The mean age was 69.90±9.45, with 52.02% being female, 25% of the patients were on New York Heart Association (NYHA) class IV and 49.6% had Canadian Cardiovascular Society (CCS) class 4 angina, and 85.5% had urgency or emergency status. The mortality observed in the sample was 13.31%. The HiriSCORE model showed better calibration (15.0%) compared to ESII (6.6%) and the STS model (2.0%). In the ROC curve, the HiriSCORE model showed better accuracy (ROC = 0.74) than the traditional models STS (ROC = 0.67) and ESII (ROC = 0.50).
Traditional models were inadequate to predict mortality of high-risk patients undergoing CABG. However, the HiriSCORE model was simple and accurate to predict mortality in high-risk patients.</description><subject>Aged</subject><subject>Angina</subject><subject>Area Under Curve</subject><subject>Biology and Life Sciences</subject><subject>Brazil - epidemiology</subject><subject>Calibration</subject><subject>Cardiac patients</subject><subject>Cardiovascular diseases</subject><subject>Care and treatment</subject><subject>China - epidemiology</subject><subject>Complications and side effects</subject><subject>Coronary artery</subject><subject>Coronary artery bypass</subject><subject>Coronary Artery Bypass - adverse effects</subject><subject>Coronary Artery Disease - epidemiology</subject><subject>Coronary Artery Disease - mortality</subject><subject>Coronary Artery Disease - surgery</subject><subject>Cross-Sectional Studies</subject><subject>Databases, Factual</subject><subject>Female</subject><subject>Health risks</subject><subject>Heart attacks</subject><subject>Heart surgery</subject><subject>Hospital Mortality</subject><subject>Humans</subject><subject>Male</subject><subject>Medicine and Health Sciences</subject><subject>Middle Aged</subject><subject>Model accuracy</subject><subject>Models, Statistical</subject><subject>Mortality</subject><subject>Patient outcomes</subject><subject>Patients</subject><subject>Performance evaluation</subject><subject>Prognosis</subject><subject>Prospective Studies</subject><subject>Risk</subject><subject>Risk Assessment</subject><subject>Risk Factors</subject><subject>Risk groups</subject><subject>ROC Curve</subject><subject>Treatment 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Aerospace Collection</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Environmental Science Database</collection><collection>Materials Science Collection</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>Engineering Collection</collection><collection>Environmental Science Collection</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>PloS one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Goncharov, Maxim</au><au>Mejia, Omar Asdrúbal Vilca</au><au>Arthur, Camila Perez de Souza</au><au>Orlandi, Bianca Maria Maglia</au><au>Sousa, Alexandre</au><au>Oliveira, Marco Antônio Praça</au><au>Atik, Fernando Antibas</au><au>Segalote, Rodrigo Coelho</au><au>Tiveron, Marcos Gradim</au><au>de Barros E Silva, Pedro Gabriel Melo</au><au>Nakazone, Marcelo Arruda</au><au>Lisboa, Luiz Augusto Ferreira</au><au>Dallan, Luís Alberto Oliveira</au><au>Zheng, Zhe</au><au>Hu, Shengshou</au><au>Jatene, Fabio Biscegli</au><au>Deo, Salil</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Mortality risk prediction in high-risk patients undergoing coronary artery bypass grafting: Are traditional risk scores accurate?</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2021-08-03</date><risdate>2021</risdate><volume>16</volume><issue>8</issue><spage>e0255662</spage><epage>e0255662</epage><pages>e0255662-e0255662</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>The performance of traditional scores is significantly limited to predict mortality in high-risk cardiac surgery. The aim of this study was to compare the performance of STS, ESII and HiriSCORE models in predicting mortality in high-risk patients undergoing CABG.
Cross-sectional analysis in the international prospective database of high-risk patients: HiriSCORE project. We evaluated 248 patients with STS or ESII (5-10%) undergoing CABG in 8 hospitals in Brazil and China. The main outcome was mortality, defined as all deaths occurred during the hospitalization in which the operation was performed, even after 30 days. Five variables were selected as predictors of mortality in this cohort of patients. The model's performance was evaluated through the calibration-in-the-large and the receiver operating curve (ROC) tests.
The mean age was 69.90±9.45, with 52.02% being female, 25% of the patients were on New York Heart Association (NYHA) class IV and 49.6% had Canadian Cardiovascular Society (CCS) class 4 angina, and 85.5% had urgency or emergency status. The mortality observed in the sample was 13.31%. The HiriSCORE model showed better calibration (15.0%) compared to ESII (6.6%) and the STS model (2.0%). In the ROC curve, the HiriSCORE model showed better accuracy (ROC = 0.74) than the traditional models STS (ROC = 0.67) and ESII (ROC = 0.50).
Traditional models were inadequate to predict mortality of high-risk patients undergoing CABG. However, the HiriSCORE model was simple and accurate to predict mortality in high-risk patients.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>34343224</pmid><doi>10.1371/journal.pone.0255662</doi><tpages>e0255662</tpages><orcidid>https://orcid.org/0000-0002-4672-6494</orcidid><orcidid>https://orcid.org/0000-0002-2310-5310</orcidid><orcidid>https://orcid.org/0000-0002-0449-7056</orcidid><orcidid>https://orcid.org/0000-0002-1635-4984</orcidid><orcidid>https://orcid.org/0000-0003-1940-4470</orcidid><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 1932-6203 |
ispartof | PloS one, 2021-08, Vol.16 (8), p.e0255662-e0255662 |
issn | 1932-6203 1932-6203 |
language | eng |
recordid | cdi_plos_journals_2557825585 |
source | MEDLINE; DOAJ Directory of Open Access Journals; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; Public Library of Science (PLoS) Journals Open Access; PubMed Central; Free Full-Text Journals in Chemistry |
subjects | Aged Angina Area Under Curve Biology and Life Sciences Brazil - epidemiology Calibration Cardiac patients Cardiovascular diseases Care and treatment China - epidemiology Complications and side effects Coronary artery Coronary artery bypass Coronary Artery Bypass - adverse effects Coronary Artery Disease - epidemiology Coronary Artery Disease - mortality Coronary Artery Disease - surgery Cross-Sectional Studies Databases, Factual Female Health risks Heart attacks Heart surgery Hospital Mortality Humans Male Medicine and Health Sciences Middle Aged Model accuracy Models, Statistical Mortality Patient outcomes Patients Performance evaluation Prognosis Prospective Studies Risk Risk Assessment Risk Factors Risk groups ROC Curve Treatment Outcome Variables |
title | Mortality risk prediction in high-risk patients undergoing coronary artery bypass grafting: Are traditional risk scores accurate? |
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