Literature DB >> 26255683

The ACC/AHA 2013 pooled cohort equations compared to a Korean Risk Prediction Model for atherosclerotic cardiovascular disease.

Keum Ji Jung1, Yangsoo Jang2, Dong Joo Oh3, Byung-Hee Oh4, Sang Hoon Lee5, Seong-Wook Park6, Ki-Bae Seung7, Hong-Kyu Kim8, Young Duk Yun9, Sung Hee Choi10, Jidong Sung11, Tae-Yong Lee12, Sung Hi Kim13, Sang Baek Koh14, Moon Chan Kim15, Hyeon Chang Kim16, Heejin Kimm17, Chungmo Nam16, Sungha Park2, Sun Ha Jee18.   

Abstract

BACKGROUND AND AIMS: To evaluate the performance of the American College of Cardiology/American Heart Association (ACC/AHA) 2013 Pooled Cohort Equations in the Korean Heart Study (KHS) population and to develop a Korean Risk Prediction Model (KRPM) for atherosclerotic cardiovascular disease (ASCVD) events.
METHODS: The KHS cohort included 200,010 Korean adults aged 40-79 years who were free from ASCVD at baseline. Discrimination, calibration, and recalibration of the ACC/AHA Equations in predicting 10-year ASCVD risk in the KHS cohort were evaluated. The KRPM was derived using Cox model coefficients, mean risk factor values, and mean incidences from the KHS cohort.
RESULTS: In the discriminatory analysis, the ACC/AHA Equations' White and African-American (AA) models moderately distinguished cases from non-cases, and were similar to the KRPM: For men, the area under the receiver operating characteristic curve (AUROCs) were 0.727 (White model), 0.725 (AA model), and 0.741 (KRPM); for women, the corresponding AUROCs were 0.738, 0.739, and 0.745. Absolute 10-year ASCVD risk for men in the KHS cohort was overestimated by 56.5% (White model) and 74.1% (AA model), while the risk for women was underestimated by 27.9% (White model) and overestimated by 29.1% (AA model). Recalibration of the ACC/AHA Equations did not affect discriminatory ability but improved calibration substantially, especially in men in the White model. Of the three ASCVD risk prediction models, the KRPM showed best calibration.
CONCLUSIONS: The ACC/AHA Equations should not be directly applied for ASCVD risk prediction in a Korean population. The KRPM showed best predictive ability for ASCVD risk.
Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Entities:  

Keywords:  Atherosclerotic cardiovascular disease; Cohort study; Prediction; Validation

Mesh:

Year:  2015        PMID: 26255683     DOI: 10.1016/j.atherosclerosis.2015.07.033

Source DB:  PubMed          Journal:  Atherosclerosis        ISSN: 0021-9150            Impact factor:   5.162


  40 in total

1.  Estimated glomerular filtration rate and albuminuria in Korean population evaluated for cardiovascular risk.

Authors:  Kayoung Lee; Jinseung Kim
Journal:  Int Urol Nephrol       Date:  2016-02-23       Impact factor: 2.370

2.  Calibration and discrimination of the Framingham Risk Score and the Pooled Cohort Equations.

Authors:  Dennis T Ko; Atul Sivaswamy; Maneesh Sud; Gynter Kotrri; Paymon Azizi; Maria Koh; Peter C Austin; Douglas S Lee; Idan Roifman; George Thanassoulis; Karen Tu; Jacob A Udell; Harindra C Wijeysundera; Todd J Anderson
Journal:  CMAJ       Date:  2020-04-27       Impact factor: 8.262

Review 3.  Implications of the heterogeneity between guideline recommendations for the use of low dose aspirin in primary prevention of cardiovascular disease.

Authors:  Xiao-Ying Li; Li Li; Sang-Hoon Na; Francesca Santilli; Zhongwei Shi; Michael Blaha
Journal:  Am J Prev Cardiol       Date:  2022-06-06

4.  2019 ACC/AHA Guideline on the Primary Prevention of Cardiovascular Disease: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines.

Authors:  Donna K Arnett; Roger S Blumenthal; Michelle A Albert; Andrew B Buroker; Zachary D Goldberger; Ellen J Hahn; Cheryl Dennison Himmelfarb; Amit Khera; Donald Lloyd-Jones; J William McEvoy; Erin D Michos; Michael D Miedema; Daniel Muñoz; Sidney C Smith; Salim S Virani; Kim A Williams; Joseph Yeboah; Boback Ziaeian
Journal:  J Am Coll Cardiol       Date:  2019-03-17       Impact factor: 24.094

Review 5.  2019 ACC/AHA Guideline on the Primary Prevention of Cardiovascular Disease: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines.

Authors:  Donna K Arnett; Roger S Blumenthal; Michelle A Albert; Andrew B Buroker; Zachary D Goldberger; Ellen J Hahn; Cheryl Dennison Himmelfarb; Amit Khera; Donald Lloyd-Jones; J William McEvoy; Erin D Michos; Michael D Miedema; Daniel Muñoz; Sidney C Smith; Salim S Virani; Kim A Williams; Joseph Yeboah; Boback Ziaeian
Journal:  Circulation       Date:  2019-03-17       Impact factor: 29.690

6.  2019 AHA/ACC Clinical Performance and Quality Measures for Adults With High Blood Pressure: A Report of the American College of Cardiology/American Heart Association Task Force on Performance Measures.

Authors:  Donald E Casey; Randal J Thomas; Vivek Bhalla; Yvonne Commodore-Mensah; Paul A Heidenreich; Dhaval Kolte; Paul Muntner; Sidney C Smith; John A Spertus; John R Windle; Gregory D Wozniak; Boback Ziaeian
Journal:  J Am Coll Cardiol       Date:  2019-11-26       Impact factor: 24.094

Review 7.  2019 AHA/ACC Clinical Performance and Quality Measures for Adults With High Blood Pressure: A Report of the American College of Cardiology/American Heart Association Task Force on Performance Measures.

Authors:  Donald E Casey; Randal J Thomas; Vivek Bhalla; Yvonne Commodore-Mensah; Paul A Heidenreich; Dhaval Kolte; Paul Muntner; Sidney C Smith; John A Spertus; John R Windle; Gregory D Wozniak; Boback Ziaeian
Journal:  Circ Cardiovasc Qual Outcomes       Date:  2019-11-12

8.  Cardiovascular Disease Prediction by Machine Learning Algorithms Based on Cytokines in Kazakhs of China.

Authors:  Yunxing Jiang; Xianghui Zhang; Rulin Ma; Xinping Wang; Jiaming Liu; Mulatibieke Keerman; Yizhong Yan; Jiaolong Ma; Yanpeng Song; Jingyu Zhang; Jia He; Shuxia Guo; Heng Guo
Journal:  Clin Epidemiol       Date:  2021-06-09       Impact factor: 4.790

9.  Machine Learning-Based Cardiovascular Disease Prediction Model: A Cohort Study on the Korean National Health Insurance Service Health Screening Database.

Authors:  Joung Ouk Ryan Kim; Yong-Suk Jeong; Jin Ho Kim; Jong-Weon Lee; Dougho Park; Hyoung-Seop Kim
Journal:  Diagnostics (Basel)       Date:  2021-05-25

10.  Prediction of 8-year risk of cardiovascular diseases in Korean adult population.

Authors:  Sung Hyouk Choi; Seung Min Lee; Su Hwan Kim; Minseon Park; Hyung-Jin Yoon
Journal:  Sci Rep       Date:  2021-07-12       Impact factor: 4.379

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