Cited 27 times in
Medical history for prognostic risk assessment and diagnosis of stable patients with suspected coronary artery disease
DC Field | Value | Language |
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dc.contributor.author | 장혁재 | - |
dc.date.accessioned | 2018-03-26T17:05:20Z | - |
dc.date.available | 2018-03-26T17:05:20Z | - |
dc.date.issued | 2015 | - |
dc.identifier.issn | 0002-9343 | - |
dc.identifier.uri | https://ir.ymlib.yonsei.ac.kr/handle/22282913/157166 | - |
dc.description.abstract | OBJECTIVE: To develop a clinical cardiac risk algorithm for stable patients with suspected coronary artery disease based upon angina typicality and coronary artery disease risk factors. METHODS: Between 2004 and 2011, 14,004 adults with suspected coronary artery disease referred for cardiac imaging were followed: 1) 9093 patients for coronary computed tomography angiography (CCTA) followed for 2.0 years (CCTA-1); 2) 2132 patients for CCTA followed for 1.6 years (CCTA-2); and 3) 2779 patients for exercise myocardial perfusion scintigraphy (MPS) followed for 5.0 years. A best-fit model from CCTA-1 for prediction of death or myocardial infarction was developed, with integer values proportional to regression coefficients. Discrimination was assessed using C-statistic. The validated model was tested for estimation of the likelihood of obstructive coronary artery disease, defined as ≥50% stenosis, as compared with the method of Diamond and Forrester. Primary outcomes included all-cause mortality and nonfatal myocardial infarction. Secondary outcomes included prevalent angiographically obstructive coronary artery disease. RESULTS: In CCTA-1, best-fit model discriminated individuals at risk of death or myocardial infarction (C-statistic 0.76). The integer model ranged from 3 to 13, corresponding to 3-year death risk or myocardial infarction of 0.25% to 53.8%. When applied to CCTA-2 and MPS cohorts, the model demonstrated C-statistics of 0.71 and 0.77, respectively. Both best-fit (C = 0.76; 95% confidence interval [CI], 0.746-0.771) and integer models (C = 0.71; 95% CI, 0.693-0.719) performed better than Diamond and Forrester (C = 0.64; 95% CI, 0.628-0.659) for estimating obstructive coronary artery disease. CONCLUSIONS: For stable symptomatic patients with suspected coronary artery disease, we developed a history-based method for prediction of death and obstructive coronary artery disease. | - |
dc.description.statementOfResponsibility | open | - |
dc.language | English | - |
dc.publisher | Excerpta Medica | - |
dc.relation.isPartOf | AMERICAN JOURNAL OF MEDICINE | - |
dc.rights | CC BY-NC-ND 2.0 KR | - |
dc.rights | https://creativecommons.org/licenses/by-nc-nd/2.0/kr/ | - |
dc.subject.MESH | Adolescent | - |
dc.subject.MESH | Adult | - |
dc.subject.MESH | Algorithms | - |
dc.subject.MESH | Coronary Angiography | - |
dc.subject.MESH | Coronary Artery Disease/complications | - |
dc.subject.MESH | Coronary Artery Disease/diagnosis* | - |
dc.subject.MESH | Female | - |
dc.subject.MESH | Humans | - |
dc.subject.MESH | Male | - |
dc.subject.MESH | Medical History Taking* | - |
dc.subject.MESH | Middle Aged | - |
dc.subject.MESH | Myocardial Infarction/diagnosis | - |
dc.subject.MESH | Myocardial Infarction/mortality | - |
dc.subject.MESH | Prognosis | - |
dc.subject.MESH | Proportional Hazards Models | - |
dc.subject.MESH | Reproducibility of Results | - |
dc.subject.MESH | Risk Assessment/methods* | - |
dc.subject.MESH | Risk Factors | - |
dc.subject.MESH | Tomography, X-Ray Computed | - |
dc.subject.MESH | Young Adult | - |
dc.title | Medical history for prognostic risk assessment and diagnosis of stable patients with suspected coronary artery disease | - |
dc.type | Article | - |
dc.contributor.college | College of Medicine | - |
dc.contributor.department | Dept. of Internal Medicine | - |
dc.contributor.googleauthor | James K. Min | - |
dc.contributor.googleauthor | Allison Dunning | - |
dc.contributor.googleauthor | Heidi Gransar | - |
dc.contributor.googleauthor | Stephan Achenbach | - |
dc.contributor.googleauthor | Fay Y. Lin | - |
dc.contributor.googleauthor | Mouaz Al-Mallah | - |
dc.contributor.googleauthor | Matthew J. Budoff | - |
dc.contributor.googleauthor | Tracy Q. Callister | - |
dc.contributor.googleauthor | Hyuk-Jae Chang | - |
dc.contributor.googleauthor | Filippo Cademartiri | - |
dc.contributor.googleauthor | Kavitha Chinnaiyan | - |
dc.contributor.googleauthor | Benjamin J. W. Chow | - |
dc.contributor.googleauthor | Ralph D’Agostino | - |
dc.contributor.googleauthor | Augustin DeLago | - |
dc.contributor.googleauthor | John Friedman | - |
dc.contributor.googleauthor | Martin Hadamitzky | - |
dc.contributor.googleauthor | Joerg Hausleiter | - |
dc.contributor.googleauthor | Sean Hayes | - |
dc.contributor.googleauthor | Philipp Kaufmann | - |
dc.contributor.googleauthor | Gilbert L. Raff | - |
dc.contributor.googleauthor | Leslee J. Shaw | - |
dc.contributor.googleauthor | Louise Thomson | - |
dc.contributor.googleauthor | Todd Villines | - |
dc.contributor.googleauthor | Ricardo C. Cury | - |
dc.contributor.googleauthor | Gudrun Feuchtner | - |
dc.contributor.googleauthor | Yong-Jin Kim | - |
dc.contributor.googleauthor | Jonathon Leipsic | - |
dc.contributor.googleauthor | Daniel S. Berman | - |
dc.contributor.googleauthor | Michael Pencina | - |
dc.identifier.doi | 10.1016/j.amjmed.2014.10.031 | - |
dc.contributor.localId | A03490 | - |
dc.relation.journalcode | J00093 | - |
dc.identifier.eissn | 1555-7162 | - |
dc.identifier.pmid | 25865923 | - |
dc.subject.keyword | Coronary artery disease | - |
dc.subject.keyword | Diagnosis | - |
dc.subject.keyword | Prognosis | - |
dc.contributor.alternativeName | Chang, Hyuck Jae | - |
dc.contributor.affiliatedAuthor | Chang, Hyuck Jae | - |
dc.citation.volume | 128 | - |
dc.citation.number | 8 | - |
dc.citation.startPage | 871 | - |
dc.citation.endPage | 878 | - |
dc.identifier.bibliographicCitation | AMERICAN JOURNAL OF MEDICINE, Vol.128(8) : 871-878, 2015 | - |
dc.identifier.rimsid | 41727 | - |
dc.type.rims | ART | - |
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