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Per-lesion versus per-patient analysis of coronary artery disease in predicting the development of obstructive lesions: the Progression of AtheRosclerotic PlAque DetermIned by Computed TmoGraphic Angiography Imaging (PARADIGM) study
DC Field | Value | Language |
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dc.contributor.author | 장혁재 | - |
dc.date.accessioned | 2021-01-19T08:00:16Z | - |
dc.date.available | 2021-01-19T08:00:16Z | - |
dc.date.issued | 2020-12 | - |
dc.identifier.issn | 1569-5794 | - |
dc.identifier.uri | https://ir.ymlib.yonsei.ac.kr/handle/22282913/181418 | - |
dc.description.abstract | To determine whether the assessment of individual plaques is superior in predicting the progression to obstructive coronary artery disease (CAD) on serial coronary computed tomography angiography (CCTA) than per-patient assessment. From a multinational registry of 2252 patients who underwent serial CCTA at a ≥ 2-year inter-scan interval, patients with only non-obstructive lesions at baseline were enrolled. CCTA was quantitatively analyzed at both the per-patient and per-lesion level. Models predicting the development of an obstructive lesion at follow up using either the per-patient or per-lesion level CCTA measures were constructed and compared. From 1297 patients (mean age 60 ± 9 years, 43% men) enrolled, a total of 3218 non-obstructive lesions were identified at baseline. At follow-up (inter-scan interval: 3.8 ± 1.6 years), 76 lesions (2.4%, 60 patients) became obstructive, defined as > 50% diameter stenosis. The C-statistics of Model 1, adjusted only by clinical risk factors, was 0.684. The addition of per-patient level total plaque volume (PV) and the presence of high-risk plaque (HRP) features to Model 1 improved the C-statistics to 0.825 [95% confidence interval (CI) 0.823-0.827]. When per-lesion level PV and the presence of HRP were added to Model 1, the predictive value of the model improved the C-statistics to 0.895 [95% CI 0.893-0.897]. The model utilizing per-lesion level CCTA measures was superior to the model utilizing per-patient level CCTA measures in predicting the development of an obstructive lesion (p < 0.001). Lesion-level analysis of coronary atherosclerotic plaques with CCTA yielded better predictive power for the development of obstructive CAD than the simple quantification of total coronary atherosclerotic burden at a per-patient level.Clinical Trial Registration: ClinicalTrials.gov NCT0280341. | - |
dc.description.statementOfResponsibility | restriction | - |
dc.language | English | - |
dc.publisher | Kluwer Academic Publishers | - |
dc.relation.isPartOf | INTERNATIONAL JOURNAL OF CARDIOVASCULAR IMAGING | - |
dc.rights | CC BY-NC-ND 2.0 KR | - |
dc.subject.MESH | Aged | - |
dc.subject.MESH | Computed Tomography Angiography* | - |
dc.subject.MESH | Coronary Angiography* | - |
dc.subject.MESH | Coronary Artery Disease / diagnostic imaging* | - |
dc.subject.MESH | Coronary Stenosis / diagnostic imaging* | - |
dc.subject.MESH | Coronary Vessels / diagnostic imaging* | - |
dc.subject.MESH | Disease Progression | - |
dc.subject.MESH | Female | - |
dc.subject.MESH | Heart Disease Risk Factors | - |
dc.subject.MESH | Humans | - |
dc.subject.MESH | Male | - |
dc.subject.MESH | Middle Aged | - |
dc.subject.MESH | Plaque, Atherosclerotic* | - |
dc.subject.MESH | Predictive Value of Tests | - |
dc.subject.MESH | Prospective Studies | - |
dc.subject.MESH | Registries | - |
dc.subject.MESH | Risk Assessment | - |
dc.subject.MESH | Rupture, Spontaneous | - |
dc.subject.MESH | Time Factors | - |
dc.title | Per-lesion versus per-patient analysis of coronary artery disease in predicting the development of obstructive lesions: the Progression of AtheRosclerotic PlAque DetermIned by Computed TmoGraphic Angiography Imaging (PARADIGM) study | - |
dc.type | Article | - |
dc.contributor.college | College of Medicine (의과대학) | - |
dc.contributor.department | Dept. of Internal Medicine (내과학교실) | - |
dc.contributor.googleauthor | Sang-Eun Lee | - |
dc.contributor.googleauthor | Ji Min Sung | - |
dc.contributor.googleauthor | Daniele Andreini | - |
dc.contributor.googleauthor | Mouaz H Al-Mallah | - |
dc.contributor.googleauthor | Matthew J Budoff | - |
dc.contributor.googleauthor | Filippo Cademartiri | - |
dc.contributor.googleauthor | Kavitha Chinnaiyan | - |
dc.contributor.googleauthor | Jung Hyun Choi | - |
dc.contributor.googleauthor | Eun Ju Chun | - |
dc.contributor.googleauthor | Edoardo Conte | - |
dc.contributor.googleauthor | Ilan Gottlieb | - |
dc.contributor.googleauthor | Martin Hadamitzky | - |
dc.contributor.googleauthor | Yong Jin Kim | - |
dc.contributor.googleauthor | Byoung Kwon Lee | - |
dc.contributor.googleauthor | Jonathon A Leipsic | - |
dc.contributor.googleauthor | Erica Maffei | - |
dc.contributor.googleauthor | Hugo Marques | - |
dc.contributor.googleauthor | Pedro de Araújo Gonçalves | - |
dc.contributor.googleauthor | Gianluca Pontone | - |
dc.contributor.googleauthor | Sanghoon Shin | - |
dc.contributor.googleauthor | Peter H Stone | - |
dc.contributor.googleauthor | Habib Samady | - |
dc.contributor.googleauthor | Renu Virmani | - |
dc.contributor.googleauthor | Jagat Narula | - |
dc.contributor.googleauthor | Daniel S Berman | - |
dc.contributor.googleauthor | Leslee J Shaw | - |
dc.contributor.googleauthor | Jeroen J Bax | - |
dc.contributor.googleauthor | Fay Y Lin | - |
dc.contributor.googleauthor | James K Min | - |
dc.contributor.googleauthor | Hyuk-Jae Chang | - |
dc.identifier.doi | 10.1007/s10554-020-01960-z | - |
dc.contributor.localId | A03490 | - |
dc.relation.journalcode | J01094 | - |
dc.identifier.eissn | 1875-8312 | - |
dc.identifier.pmid | 32779077 | - |
dc.identifier.url | https://link.springer.com/article/10.1007/s10554-020-01960-z | - |
dc.subject.keyword | Coronary artery atherosclerosis | - |
dc.subject.keyword | Coronary artery disease | - |
dc.subject.keyword | Coronary computed tomography angiography | - |
dc.subject.keyword | Statins | - |
dc.contributor.alternativeName | Chang, Hyuck Jae | - |
dc.contributor.affiliatedAuthor | 장혁재 | - |
dc.citation.volume | 36 | - |
dc.citation.number | 12 | - |
dc.citation.startPage | 2357 | - |
dc.citation.endPage | 2364 | - |
dc.identifier.bibliographicCitation | INTERNATIONAL JOURNAL OF CARDIOVASCULAR IMAGING, Vol.36(12) : 2357-2364, 2020-12 | - |
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