OBJECTIVES: This study sought to determine the clinical and angiographic variables that would identify patients with high-risk "vulnerable" coronary plaques. BACKGROUND: In the PROSPECT (Providing Regional Observations to Study Predictors of Events in the Coronary Tree) study, in patients successfully treated for acute coronary syndrome (ACS), plaque composition, plaque burden, and minimal luminal area as detected by 3-vessel radiofrequency intravascular ultrasound (IVUS) imaging were associated with an increased risk of developing future events from untreated atherosclerotic lesions (vulnerable plaques). Whether baseline demographic and angiographic findings can be used to identify patients most likely to have vulnerable coronary plaques has not been examined. METHODS: On the basis of 3-vessel radiofrequency IVUS imaging, patents in the PROSPECT trial were classified in 2 groups according to whether or not one or more untreated high-risk plaques were present, defined as having ≥2 high-risk features (a thin-cap fibroatheroma, plaque burden ≥70%, and/or minimal luminal area ≤4 mm(2)). RESULTS: The high-risk group (those with one or more high-risk lesions) had higher Framingham risk score (7.5 ± 3.4 vs. 6.9 ± 3.3; p = 0.04), more extensive coronary artery disease, and more nonculprit lesion-related cardiovascular events during the 3-year follow-up (hazard ratio: 2.63; 95% confidence interval: 1.62 to 3.66; p < 0.0001). However, demographic factors had poor discrimination in detecting high-risk patients (area under the curve 0.55), and discrimination was only slightly improved when angiographic variables were entered into the model (area under the curve 0.64). CONCLUSIONS: Clinical and angiographic characteristics had poor predictive accuracy in identifying patients with untreated high-risk plaques related to future adverse events. This finding highlights the potential value of comprehensive 3-vessel imaging assessment (either invasive or noninvasive) to evaluate plaque phenotype for more accurate risk stratification of patients admitted with ACS.
OBJECTIVES: This study sought to determine the clinical and angiographic variables that would identify patients with high-risk "vulnerable" coronary plaques. BACKGROUND: In the PROSPECT (Providing Regional Observations to Study Predictors of Events in the Coronary Tree) study, in patients successfully treated for acute coronary syndrome (ACS), plaque composition, plaque burden, and minimal luminal area as detected by 3-vessel radiofrequency intravascular ultrasound (IVUS) imaging were associated with an increased risk of developing future events from untreated atherosclerotic lesions (vulnerable plaques). Whether baseline demographic and angiographic findings can be used to identify patients most likely to have vulnerable coronary plaques has not been examined. METHODS: On the basis of 3-vessel radiofrequency IVUS imaging, patents in the PROSPECT trial were classified in 2 groups according to whether or not one or more untreated high-risk plaques were present, defined as having ≥2 high-risk features (a thin-cap fibroatheroma, plaque burden ≥70%, and/or minimal luminal area ≤4 mm(2)). RESULTS: The high-risk group (those with one or more high-risk lesions) had higher Framingham risk score (7.5 ± 3.4 vs. 6.9 ± 3.3; p = 0.04), more extensive coronary artery disease, and more nonculprit lesion-related cardiovascular events during the 3-year follow-up (hazard ratio: 2.63; 95% confidence interval: 1.62 to 3.66; p < 0.0001). However, demographic factors had poor discrimination in detecting high-risk patients (area under the curve 0.55), and discrimination was only slightly improved when angiographic variables were entered into the model (area under the curve 0.64). CONCLUSIONS: Clinical and angiographic characteristics had poor predictive accuracy in identifying patients with untreated high-risk plaques related to future adverse events. This finding highlights the potential value of comprehensive 3-vessel imaging assessment (either invasive or noninvasive) to evaluate plaque phenotype for more accurate risk stratification of patients admitted with ACS.
Authors: Xiaoya Guo; Don P Giddens; David Molony; Chun Yang; Habib Samady; Jie Zheng; Gary S Mintz; Akiko Maehara; Liang Wang; Xuan Pei; Zhi-Yong Li; Dalin Tang Journal: J Biomech Eng Date: 2018-04-01 Impact factor: 2.097
Authors: Hector M Garcia-Garcia; Ik-Kyung Jang; Patrick W Serruys; Jason C Kovacic; Jagat Narula; Zahi A Fayad Journal: Circ Res Date: 2014-06-06 Impact factor: 17.367
Authors: Dalin Tang; Roger D Kamm; Chun Yang; Jie Zheng; Gador Canton; Richard Bach; Xueying Huang; Thomas S Hatsukami; Jian Zhu; Genshan Ma; Akiko Maehara; Gary S Mintz; Chun Yuan Journal: J Biomech Date: 2014-01-14 Impact factor: 2.712
Authors: Mariusz Tomaniak; Dorota Ochijewicz; Łukasz Kołtowski; Adam Rdzanek; Arkadiusz Pietrasik; Jacek Jąkała; Magdalena Slezak; Krzysztof P Malinowski; Martyna Zaleska; Jakub Maksym; Piotr Barus; Tomasz Roleder; Krzysztof J Filipiak; Grzegorz Opolski; Janusz Kochman Journal: J Clin Med Date: 2021-05-28 Impact factor: 4.241