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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

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dc.contributor.author장혁재-
dc.date.accessioned2021-01-19T08:00:16Z-
dc.date.available2021-01-19T08:00:16Z-
dc.date.issued2020-12-
dc.identifier.issn1569-5794-
dc.identifier.urihttps://ir.ymlib.yonsei.ac.kr/handle/22282913/181418-
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.-
dc.description.statementOfResponsibilityrestriction-
dc.languageEnglish-
dc.publisherKluwer Academic Publishers-
dc.relation.isPartOfINTERNATIONAL JOURNAL OF CARDIOVASCULAR IMAGING-
dc.rightsCC BY-NC-ND 2.0 KR-
dc.subject.MESHAged-
dc.subject.MESHComputed Tomography Angiography*-
dc.subject.MESHCoronary Angiography*-
dc.subject.MESHCoronary Artery Disease / diagnostic imaging*-
dc.subject.MESHCoronary Stenosis / diagnostic imaging*-
dc.subject.MESHCoronary Vessels / diagnostic imaging*-
dc.subject.MESHDisease Progression-
dc.subject.MESHFemale-
dc.subject.MESHHeart Disease Risk Factors-
dc.subject.MESHHumans-
dc.subject.MESHMale-
dc.subject.MESHMiddle Aged-
dc.subject.MESHPlaque, Atherosclerotic*-
dc.subject.MESHPredictive Value of Tests-
dc.subject.MESHProspective Studies-
dc.subject.MESHRegistries-
dc.subject.MESHRisk Assessment-
dc.subject.MESHRupture, Spontaneous-
dc.subject.MESHTime Factors-
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.contributor.collegeCollege of Medicine (의과대학)-
dc.contributor.departmentDept. of Internal Medicine (내과학교실)-
dc.contributor.googleauthorSang-Eun Lee-
dc.contributor.googleauthorJi Min Sung-
dc.contributor.googleauthorDaniele Andreini-
dc.contributor.googleauthorMouaz H Al-Mallah-
dc.contributor.googleauthorMatthew J Budoff-
dc.contributor.googleauthorFilippo Cademartiri-
dc.contributor.googleauthorKavitha Chinnaiyan-
dc.contributor.googleauthorJung Hyun Choi-
dc.contributor.googleauthorEun Ju Chun-
dc.contributor.googleauthorEdoardo Conte-
dc.contributor.googleauthorIlan Gottlieb-
dc.contributor.googleauthorMartin Hadamitzky-
dc.contributor.googleauthorYong Jin Kim-
dc.contributor.googleauthorByoung Kwon Lee-
dc.contributor.googleauthorJonathon A Leipsic-
dc.contributor.googleauthorErica Maffei-
dc.contributor.googleauthorHugo Marques-
dc.contributor.googleauthorPedro de Araújo Gonçalves-
dc.contributor.googleauthorGianluca Pontone-
dc.contributor.googleauthorSanghoon Shin-
dc.contributor.googleauthorPeter H Stone-
dc.contributor.googleauthorHabib Samady-
dc.contributor.googleauthorRenu Virmani-
dc.contributor.googleauthorJagat Narula-
dc.contributor.googleauthorDaniel S Berman-
dc.contributor.googleauthorLeslee J Shaw-
dc.contributor.googleauthorJeroen J Bax-
dc.contributor.googleauthorFay Y Lin-
dc.contributor.googleauthorJames K Min-
dc.contributor.googleauthorHyuk-Jae Chang-
dc.identifier.doi10.1007/s10554-020-01960-z-
dc.contributor.localIdA03490-
dc.relation.journalcodeJ01094-
dc.identifier.eissn1875-8312-
dc.identifier.pmid32779077-
dc.identifier.urlhttps://link.springer.com/article/10.1007/s10554-020-01960-z-
dc.subject.keywordCoronary artery atherosclerosis-
dc.subject.keywordCoronary artery disease-
dc.subject.keywordCoronary computed tomography angiography-
dc.subject.keywordStatins-
dc.contributor.alternativeNameChang, Hyuck Jae-
dc.contributor.affiliatedAuthor장혁재-
dc.citation.volume36-
dc.citation.number12-
dc.citation.startPage2357-
dc.citation.endPage2364-
dc.identifier.bibliographicCitationINTERNATIONAL JOURNAL OF CARDIOVASCULAR IMAGING, Vol.36(12) : 2357-2364, 2020-12-
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Internal Medicine (내과학교실) > 1. Journal Papers

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