Cited 11 times in
The Predictive Value of Coronary Artery Calcium Scoring for Major Adverse Cardiac Events According to Renal Function (from the Coronary Computed Tomography Angiography Evaluation for Clinical Outcomes: An International Multicenter [CONFIRM] Registry)
DC Field | Value | Language |
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dc.contributor.author | 장혁재 | - |
dc.date.accessioned | 2019-07-11T03:32:35Z | - |
dc.date.available | 2019-07-11T03:32:35Z | - |
dc.date.issued | 2019 | - |
dc.identifier.issn | 0002-9149 | - |
dc.identifier.uri | https://ir.ymlib.yonsei.ac.kr/handle/22282913/170024 | - |
dc.description.abstract | The prognostic performance of coronary artery calcium score (CACS) for predicting adverse outcomes in patients with decreased renal function remains unclear. We aimed to examine whether CACS improves risk stratification by demonstrating incremental value beyond a traditional risk score according to renal function status. 9,563 individuals without known coronary artery disease were enrolled. Estimated glomerular filtration rate (eGFR, ml/min/1.73 m2) was ascertained using the modified Modification of Diet in Renal Disease formula, and was categorized as: ≥90, 60 to 89, and <60. CACS was categorized as 0, 1 to 100, 101 to 400, and >400. Multivariable Cox regression was used to estimate hazard ratios (HR) with 95% confidence intervals (95% CI) for major adverse cardiac events (MACE), comprising all-cause mortality, myocardial infarction, and late revascularization (>90 days). Mean age was 55.8 ± 11.5 years (52.8% male). In total, 261 (2.7%) patients experienced MACE over a median follow-up of 24.5 months (interquartile range: 16.9 to 41.1). Incident MACE increased with higher CACS across each eGFR category, with the highest rate observed among patients with CACS >400 and eGFR <60 (95.1 per 1,000 person-years). A CACS >400 increased MACE risk with HR 4.46 (95% CI 1.68 to 11.85), 6.63 (95% CI 4.03 to 10.92), and 6.14 (95% CI 2.85 to 13.21) for eGFR ≥90, 60 to 89, and <60, respectively, as compared with CACS 0. Further, CACS improved discrimination and reclassification beyond Framingham 10-year risk score (FRS) (AUC: 0.70 vs 0.64; category free-NRI: 0.51, all p <0.001) for predicting MACE in patients with impaired renal function (eGFR < 90). In conclusion, CACS improved risk stratification and provided incremental value beyond FRS for predicting MACE, irrespective of eGFR status. | - |
dc.description.statementOfResponsibility | restriction | - |
dc.language | English | - |
dc.publisher | Excerpta Medica | - |
dc.relation.isPartOf | AMERICAN JOURNAL OF CARDIOLOGY | - |
dc.rights | CC BY-NC-ND 2.0 KR | - |
dc.rights | https://creativecommons.org/licenses/by-nc-nd/2.0/kr/ | - |
dc.title | The Predictive Value of Coronary Artery Calcium Scoring for Major Adverse Cardiac Events According to Renal Function (from the Coronary Computed Tomography Angiography Evaluation for Clinical Outcomes: An International Multicenter [CONFIRM] Registry) | - |
dc.type | Article | - |
dc.contributor.college | College of Medicine (의과대학) | - |
dc.contributor.department | Dept. of Internal Medicine (내과학교실) | - |
dc.contributor.googleauthor | Ji Hyun Lee | - |
dc.contributor.googleauthor | Asim Rizvi | - |
dc.contributor.googleauthor | Bríain Ó. Hartaigh | - |
dc.contributor.googleauthor | Donghee Han | - |
dc.contributor.googleauthor | Mahn Won Park | - |
dc.contributor.googleauthor | Hadi Mirhedayati Roudsari | - |
dc.contributor.googleauthor | Wijnand J. Stuijfzand | - |
dc.contributor.googleauthor | Heidi Gransar | - |
dc.contributor.googleauthor | Yao Lu | - |
dc.contributor.googleauthor | Tracy Q. Callister | - |
dc.contributor.googleauthor | Daniel S. Berman | - |
dc.contributor.googleauthor | Augustin DeLago | - |
dc.contributor.googleauthor | Martin Hadamitzky | - |
dc.contributor.googleauthor | Joerg Hausleiter | - |
dc.contributor.googleauthor | Mouaz H. Al-Mallah | - |
dc.contributor.googleauthor | Matthew J. Budoff | - |
dc.contributor.googleauthor | Philipp A. Kaufmann | - |
dc.contributor.googleauthor | Gilbert L. Raff | - |
dc.contributor.googleauthor | Kavitha Chinnaiyan | - |
dc.contributor.googleauthor | Filippo Cademartiri | - |
dc.contributor.googleauthor | Erica Maffei | - |
dc.contributor.googleauthor | Todd C. Villines | - |
dc.contributor.googleauthor | Yong-Jin Kim | - |
dc.contributor.googleauthor | Jonathon Leipsic | - |
dc.contributor.googleauthor | Gudrun Feuchtner | - |
dc.contributor.googleauthor | Gianluca Pontone | - |
dc.contributor.googleauthor | Daniele Andreini | - |
dc.contributor.googleauthor | Hugo Marques | - |
dc.contributor.googleauthor | Pedro de Araújo Gonçalves | - |
dc.contributor.googleauthor | Ronen Rubinshtein | - |
dc.contributor.googleauthor | Stephan Achenbach | - |
dc.contributor.googleauthor | Leslee J. Shaw | - |
dc.contributor.googleauthor | Benjamin J.W. Chow | - |
dc.contributor.googleauthor | Ricardo C. Cury | - |
dc.contributor.googleauthor | Jeroen J. Bax | - |
dc.contributor.googleauthor | Hyuk-Jae Chang | - |
dc.contributor.googleauthor | Erica C. Jones | - |
dc.contributor.googleauthor | Fay Y. Lin | - |
dc.contributor.googleauthor | James K. Min | - |
dc.contributor.googleauthor | Jessica M. Peña | - |
dc.identifier.doi | 10.1016/j.amjcard.2019.01.055 | - |
dc.contributor.localId | A03490 | - |
dc.relation.journalcode | J00071 | - |
dc.identifier.eissn | 1879-1913 | - |
dc.identifier.pmid | 30850210 | - |
dc.identifier.url | https://www.sciencedirect.com/science/article/pii/S0002914919301882 | - |
dc.contributor.alternativeName | Chang, Hyuck Jae | - |
dc.contributor.affiliatedAuthor | 장혁재 | - |
dc.citation.volume | 123 | - |
dc.citation.number | 9 | - |
dc.citation.startPage | 1435 | - |
dc.citation.endPage | 1442 | - |
dc.identifier.bibliographicCitation | AMERICAN JOURNAL OF CARDIOLOGY, Vol.123(9) : 1435-1442, 2019 | - |
dc.identifier.rimsid | 62079 | - |
dc.type.rims | ART | - |
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