Cited 139 times in
A coronary heart disease prediction model: The Korean heart study
DC Field | Value | Language |
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dc.contributor.author | 김현창 | - |
dc.contributor.author | 장양수 | - |
dc.contributor.author | 지선하 | - |
dc.contributor.author | 정금지 | - |
dc.date.accessioned | 2015-01-06T17:28:52Z | - |
dc.date.available | 2015-01-06T17:28:52Z | - |
dc.date.issued | 2014 | - |
dc.identifier.uri | https://ir.ymlib.yonsei.ac.kr/handle/22282913/100059 | - |
dc.description.abstract | OBJECTIVE: The objectives of this study were to develop a coronary heart disease (CHD) risk model among the Korean Heart Study (KHS) population and compare it with the Framingham CHD risk score. DESIGN: A prospective cohort study within a national insurance system. SETTING: 18 health promotion centres nationwide between 1996 and 2001 in Korea. PARTICIPANTS: 268 315 Koreans between the ages of 30 and 74 years without CHD at baseline. OUTCOME MEASURE: Non-fatal or fatal CHD events between 1997 and 2011. During an 11.6-year median follow-up, 2596 CHD events (1903 non-fatal and 693 fatal) occurred in the cohort. The optimal CHD model was created by adding high-density lipoprotein (HDL)-cholesterol, low-density lipoprotein (LDL)-cholesterol and triglycerides to the basic CHD model, evaluating using the area under the receiver operating characteristic curve (ROC) and continuous net reclassification index (NRI). RESULTS: The optimal CHD models for men and women included HDL-cholesterol (NRI=0.284) and triglycerides (NRI=0.207) from the basic CHD model, respectively. The discrimination using the CHD model in the Korean cohort was high: the areas under ROC were 0.764 (95% CI 0.752 to 0.774) for men and 0.815 (95% CI 0.795 to 0.835) for women. The Framingham risk function predicted 3-6 times as many CHD events than observed. Recalibration of the Framingham function using the mean values of risk factors and mean CHD incidence rates of the KHS cohort substantially improved the performance of the Framingham functions in the KHS cohort. CONCLUSIONS: The present study provides the first evidence that the Framingham risk function overestimates the risk of CHD in the Korean population where CHD incidence is low. The Korean CHD risk model is well-calculated alternations which can be used to predict an individual's risk of CHD and provides a useful guide to identify the groups at high risk for CHD among Koreans. | - |
dc.description.statementOfResponsibility | open | - |
dc.format | application/pdf | - |
dc.relation.isPartOf | BMJ OPEN | - |
dc.rights | CC BY-NC-ND 2.0 KR | - |
dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/2.0/kr/ | - |
dc.subject.MESH | Adult | - |
dc.subject.MESH | Aged | - |
dc.subject.MESH | Cohort Studies | - |
dc.subject.MESH | Coronary Artery Disease/epidemiology* | - |
dc.subject.MESH | Female | - |
dc.subject.MESH | Humans | - |
dc.subject.MESH | Male | - |
dc.subject.MESH | Middle Aged | - |
dc.subject.MESH | Models, Statistical | - |
dc.subject.MESH | Prognosis | - |
dc.subject.MESH | Prospective Studies | - |
dc.subject.MESH | Republic of Korea | - |
dc.subject.MESH | Risk Assessment | - |
dc.title | A coronary heart disease prediction model: The Korean heart study | - |
dc.type | Article | - |
dc.contributor.college | College of Medicine (의과대학) | - |
dc.contributor.department | Dept. of Internal Medicine (내과학) | - |
dc.contributor.googleauthor | Sun Ha Jee | - |
dc.contributor.googleauthor | Yangsoo Jang | - |
dc.contributor.googleauthor | Dong Joo Oh | - |
dc.contributor.googleauthor | Byung-Hee Oh | - |
dc.contributor.googleauthor | Sang Hoon Lee | - |
dc.contributor.googleauthor | Seong-Wook Park | - |
dc.contributor.googleauthor | Ki-Bae Seung | - |
dc.contributor.googleauthor | Yejin Mok | - |
dc.contributor.googleauthor | Keum Ji Jung | - |
dc.contributor.googleauthor | Heejin Kimm | - |
dc.contributor.googleauthor | Young Duk Yun | - |
dc.contributor.googleauthor | Soo Jin Baek | - |
dc.contributor.googleauthor | Duk Chul Lee | - |
dc.contributor.googleauthor | Sung Hee Choi | - |
dc.contributor.googleauthor | Moon Jong Kim | - |
dc.contributor.googleauthor | Jidong Sung | - |
dc.contributor.googleauthor | BeLong Cho | - |
dc.contributor.googleauthor | Eung Soo Kim | - |
dc.contributor.googleauthor | Byung-Yeon Yu | - |
dc.contributor.googleauthor | Tae-Yong Lee | - |
dc.contributor.googleauthor | Jong Sung Kim | - |
dc.contributor.googleauthor | Yong-Jin Lee | - |
dc.contributor.googleauthor | Jang-Kyun Oh | - |
dc.contributor.googleauthor | Sung Hi Kim | - |
dc.contributor.googleauthor | Jong-Ku Park | - |
dc.contributor.googleauthor | Sang Baek Koh | - |
dc.contributor.googleauthor | Sat Byul Park | - |
dc.contributor.googleauthor | Soon Young Lee | - |
dc.contributor.googleauthor | Cheol-In Yoo | - |
dc.contributor.googleauthor | Moon Chan Kim | - |
dc.contributor.googleauthor | Hong-Kyu Kim | - |
dc.contributor.googleauthor | Joo-sung Park | - |
dc.contributor.googleauthor | Hyeon Chang Kim | - |
dc.contributor.googleauthor | Gyu Jang Lee | - |
dc.contributor.googleauthor | Mark Woodward | - |
dc.identifier.doi | 10.1136/bmjopen-2014-005025 | - |
dc.admin.author | false | - |
dc.admin.mapping | false | - |
dc.contributor.localId | A01142 | - |
dc.contributor.localId | A03448 | - |
dc.contributor.localId | A03965 | - |
dc.contributor.localId | A03580 | - |
dc.relation.journalcode | J00380 | - |
dc.identifier.eissn | 2044-6055 | - |
dc.identifier.pmid | 24848088 | - |
dc.subject.keyword | Epidemiology | - |
dc.contributor.alternativeName | Kim, Hyeon Chang | - |
dc.contributor.alternativeName | Jang, Yang Soo | - |
dc.contributor.alternativeName | Jee, Sun Ha | - |
dc.contributor.affiliatedAuthor | Kim, Hyeon Chang | - |
dc.contributor.affiliatedAuthor | Jang, Yang Soo | - |
dc.contributor.affiliatedAuthor | Jee, Sun Ha | - |
dc.citation.volume | 4 | - |
dc.citation.number | 5 | - |
dc.citation.startPage | 005025 | - |
dc.identifier.bibliographicCitation | BMJ OPEN, Vol.4(5) : 005025, 2014 | - |
dc.identifier.rimsid | 50113 | - |
dc.type.rims | ART | - |
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