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dc.contributor.author이상은-
dc.date.accessioned2020-12-21T16:30:02Z-
dc.date.available2020-12-21T16:30:02Z-
dc.date.issued2020-
dc.identifier.issn1569-5794-
dc.identifier.otherOAK-28346-
dc.identifier.urihttps://dspace.ewha.ac.kr/handle/2015.oak/255737-
dc.description.abstractTo 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 © 2020, Springer Nature B.V.-
dc.languageEnglish-
dc.publisherSpringer Science and Business Media B.V.-
dc.subjectCoronary artery atherosclerosis-
dc.subjectCoronary artery disease-
dc.subjectCoronary computed tomography angiography-
dc.subjectStatins-
dc.titlePer-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.typeArticle-
dc.relation.issue12-
dc.relation.volume36-
dc.relation.indexSCIE-
dc.relation.indexSCOPUS-
dc.relation.startpage2357-
dc.relation.lastpage2364-
dc.relation.journaltitleInternational Journal of Cardiovascular Imaging-
dc.identifier.doi10.1007/s10554-020-01960-z-
dc.identifier.scopusid2-s2.0-85089248654-
dc.author.googleLee S.-E.-
dc.author.googleSung J.M.-
dc.author.googleAndreini D.-
dc.author.googleAl-Mallah M.H.-
dc.author.googleBudoff M.J.-
dc.author.googleCademartiri F.-
dc.author.googleChinnaiyan K.-
dc.author.googleChoi J.H.-
dc.author.googleChun E.J.-
dc.author.googleConte E.-
dc.author.googleGottlieb I.-
dc.author.googleHadamitzky M.-
dc.author.googleKim Y.J.-
dc.author.googleLee B.K.-
dc.author.googleLeipsic J.A.-
dc.author.googleMaffei E.-
dc.author.googleMarques H.-
dc.author.googlede Araújo Gonçalves P.-
dc.author.googlePontone G.-
dc.author.googleShin S.-
dc.author.googleStone P.H.-
dc.author.googleSamady H.-
dc.author.googleVirmani R.-
dc.author.googleNarula J.-
dc.author.googleBerman D.S.-
dc.author.googleShaw L.J.-
dc.author.googleBax J.J.-
dc.author.googleLin F.Y.-
dc.author.googleMin J.K.-
dc.author.googleChang H.-J.-
dc.contributor.scopusid이상은(57213176330)-
dc.date.modifydate20230208112553-
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