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Prediction of the risk of mortality using risk score in patients with coronary heart disease

BACKGROUND: The aim of the study is to develop risk scores with traditional factors for all-cause and cardiovascular mortality among coronary heart disease (CHD) patients. METHODS AND RESULTS: We performed a prospective cohort study of 1911 CHD patients aged 40 and older. Cox models were used to est...

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Autores principales: Chen, Qian, Ding, Ding, Zhang, Yuan, Yang, Yunou, Li, Qing, Chen, Xuechen, Hu, Gang, Ling, Wenhua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals LLC 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5348422/
https://www.ncbi.nlm.nih.gov/pubmed/27835576
http://dx.doi.org/10.18632/oncotarget.13166
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author Chen, Qian
Ding, Ding
Zhang, Yuan
Yang, Yunou
Li, Qing
Chen, Xuechen
Hu, Gang
Ling, Wenhua
author_facet Chen, Qian
Ding, Ding
Zhang, Yuan
Yang, Yunou
Li, Qing
Chen, Xuechen
Hu, Gang
Ling, Wenhua
author_sort Chen, Qian
collection PubMed
description BACKGROUND: The aim of the study is to develop risk scores with traditional factors for all-cause and cardiovascular mortality among coronary heart disease (CHD) patients. METHODS AND RESULTS: We performed a prospective cohort study of 1911 CHD patients aged 40 and older. Cox models were used to estimate the association of traditional factors [sex, age, fasting blood glucose (FBG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), blood pressure (BP), and cigarette use] and risk scores with all-cause and cardiovascular mortality. During a mean follow-up of 4.9 years, 232 deaths were identified, 159 of which were cardiovascular-related. Both 4-year and whole follow-up data showed age, sex, HDL-C, LDL-C, and FBG were significantly associated with the risk of mortality, while BP and smoking were not significant predictors in all models. We incorporated age, sex, FBG, HDL-C, and LDL-C to establish risk scores for all-cause and cardiovascular mortality in the 4-year and whole follow-up study. These risk scores were positively associated with the risk of death as quartiles and continuous variables. Assessed by the area under the receiver operating characteristic curves (AUROCs), these risk scores demonstrated strong discriminatory capacity, from 0.744 to 0.763; and the utility of these scores was confirmed with AUROCs from 0.736 to 0.756 (all P<0.001) in a validation cohort of 1506 CHD patients with a mean follow-up of 4.7 years. CONCLUSIONS: These simple risk score assessments, including a set of traditional risk factors, might improve the identification of high-risk CHD patients for a more intensive secondary prevention treatment.
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spelling pubmed-53484222017-03-31 Prediction of the risk of mortality using risk score in patients with coronary heart disease Chen, Qian Ding, Ding Zhang, Yuan Yang, Yunou Li, Qing Chen, Xuechen Hu, Gang Ling, Wenhua Oncotarget Research Paper BACKGROUND: The aim of the study is to develop risk scores with traditional factors for all-cause and cardiovascular mortality among coronary heart disease (CHD) patients. METHODS AND RESULTS: We performed a prospective cohort study of 1911 CHD patients aged 40 and older. Cox models were used to estimate the association of traditional factors [sex, age, fasting blood glucose (FBG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), blood pressure (BP), and cigarette use] and risk scores with all-cause and cardiovascular mortality. During a mean follow-up of 4.9 years, 232 deaths were identified, 159 of which were cardiovascular-related. Both 4-year and whole follow-up data showed age, sex, HDL-C, LDL-C, and FBG were significantly associated with the risk of mortality, while BP and smoking were not significant predictors in all models. We incorporated age, sex, FBG, HDL-C, and LDL-C to establish risk scores for all-cause and cardiovascular mortality in the 4-year and whole follow-up study. These risk scores were positively associated with the risk of death as quartiles and continuous variables. Assessed by the area under the receiver operating characteristic curves (AUROCs), these risk scores demonstrated strong discriminatory capacity, from 0.744 to 0.763; and the utility of these scores was confirmed with AUROCs from 0.736 to 0.756 (all P<0.001) in a validation cohort of 1506 CHD patients with a mean follow-up of 4.7 years. CONCLUSIONS: These simple risk score assessments, including a set of traditional risk factors, might improve the identification of high-risk CHD patients for a more intensive secondary prevention treatment. Impact Journals LLC 2016-11-07 /pmc/articles/PMC5348422/ /pubmed/27835576 http://dx.doi.org/10.18632/oncotarget.13166 Text en Copyright: © 2016 Chen et al. http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Paper
Chen, Qian
Ding, Ding
Zhang, Yuan
Yang, Yunou
Li, Qing
Chen, Xuechen
Hu, Gang
Ling, Wenhua
Prediction of the risk of mortality using risk score in patients with coronary heart disease
title Prediction of the risk of mortality using risk score in patients with coronary heart disease
title_full Prediction of the risk of mortality using risk score in patients with coronary heart disease
title_fullStr Prediction of the risk of mortality using risk score in patients with coronary heart disease
title_full_unstemmed Prediction of the risk of mortality using risk score in patients with coronary heart disease
title_short Prediction of the risk of mortality using risk score in patients with coronary heart disease
title_sort prediction of the risk of mortality using risk score in patients with coronary heart disease
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5348422/
https://www.ncbi.nlm.nih.gov/pubmed/27835576
http://dx.doi.org/10.18632/oncotarget.13166
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