Jae Seok Bae
Asan Medical Center
Network
Latest external collaboration on country level. Dive into details by clicking on the dots.
Publication
Featured researches published by Jae Seok Bae.
Coronary Artery Disease | 2017
Pil Hyung Lee; Se Hun Kang; Seungbong Han; Jung-Min Ahn; Jae Seok Bae; Cheol Hyun Lee; Soo-Jin Kang; Seung-Whan Lee; Young-Hak Kim; Cheol Whan Lee; Seong-Wook Park; Duk-Woo Park; Seung-Jung Park
Objective The aim of this study was to determine how trial-based findings of EXCEL and NOBLE might be interpreted and generalizable in ‘real-world’ settings with comparison of data from the large-scaled, all-comer Interventional Research Incorporation Society−Left MAIN Revascularization (IRIS–MAIN) registry. Patients and methods We compared baseline clinical and procedural characteristics and also determined how the relative treatment effect of percutaneous coronary intervention (PCI) and coronary artery bypass grafting (CABG) was different in EXCEL and NOBLE, compared with those of the multicenter, IRIS–MAIN registry (n=2481). The primary outcome for between-study comparison was a composite of death, myocardial infarction (MI), or stroke. Results There were between-study differences in patient risk profiles (age, BMI, diabetes, and clinical presentation), lesion complexities, and procedural characteristics (stent type, the use of off-pump surgery, and radial artery); the proportion of diabetes and acute coronary syndrome was particularly lower in NOBLE than in other studies. Although there was interstudy heterogeneity for the protocol definition of MI, the risks for serious composite outcome of death, MI, or stroke were similar between PCI and CABG in EXCEL [hazard ratio (HR): 1.00; 95% confidence interval (CI): 0.79–1.26; P=0.98] and in the matched cohort of IRIS–MAIN (HR: 1.08; 95%CI: 0.85–1.38; P=0.53), whereas it was significantly higher after PCI than after CABG in NOBLE (HR: 1.47; 95%CI: 1.06–2.05; P=0.02), which was driven by more common MI and stroke after PCI. Conclusion In the comparison of a large-sized, all-comer registry, the EXCEL trial might represent better generalizability with respect to baseline characteristics and observed clinical outcomes compared with the NOBLE trial.
Journal of The American Society of Echocardiography | 2017
Byung Joo Sun; Sahmin Lee; Jeong Yoon Jang; Osung Kwon; Jae Seok Bae; Ji Hye Lee; Dae-Hee Kim; Sung-Ho Jung; Jong-Min Song; Duk-Hyun Kang; Cheol Hyun Chung; Jae-Kwan Song
Background: A simplified classification of bicuspid aortic valve (BAV) morphology using only the orientation of fused cusps was recently proposed. The aim of this study was to test whether it is useful for showing an association with the type of valvulopathy or aortopathy. Methods: BAV phenotype was retrospectively classified in 681 patients (mean age, 59 ± 12 years; 424 men) who underwent aortic valve surgery. Each BAV was classified using both dichotomous (right and left coronary cusp fusion [CCF] vs mixed cusp fusion [MCF]) and conventional methods, and its association with the dominant valvulopathy (aortic stenosis [AS] vs regurgitation) and concomitant aortic surgery was analyzed. Four cardiologists individually reviewed transthoracic echocardiographic images of 100 randomly selected patients to compare the feasibility and accuracy of the two classification methods. Results: The frequencies of BAV CCF and MCF were 53% (n = 361) and 47% (n = 320), respectively. AS was the predominant cause of surgery (n = 546 [80%]), and concomitant aortic surgery was done in 31% (n = 214). Patients with BAV MCF showed a higher frequency of AS (89% vs 73%, P < .001) and aortic surgery (38% vs 26%, P < .001) than those with BAV CCF. There were independent associations between BAV MCF and AS (odds ratio, 3.32; 95% CI, 1.99–5.54; P < .001) as well as aortic surgery (odds ratio, 1.76; 95% CI, 1.26–2.45; P = .001). The feasibility of the classification methods did not differ, but dichotomous classification revealed higher accuracy than conventional (87% [95% CI, 84.1%–90.7%] vs 70% [95% CI, 65.0%–74.3%]) for all four examiners, with higher &kgr; coefficients representing interrater agreement (&kgr; = 0.73 ± 0.06 to 0.83 ± 0.06 [dichotomous method] vs 0.51 ± 0.06 to 0.73 ± 0.06 [conventional method]). Conclusions: The dichotomous classification method is useful for showing the association with the type of valvulopathy or aortopathy, with better diagnostic performance than the conventional method. HighlightsSimplified dichotomous BAV classification (BAV CCF vs BAV MCF) based on spatial orientation is useful for predicting patterns of valvulopathy and aortopathy.Using routine TTE images alone, this simplified method demonstrates better diagnostic performance compared to the conventional classification, which requires information regarding the individual cusps that are fused and the position of raphe.Simplified dichotomous BAV classification can be easily incorporated into the routine evaluation of BAV patients. Abbreviations: AR = Aortic regurgitation; AS = Aortic stenosis; AV = Aortic valve; BAV = Bicuspid aortic valve; CCF = Coronary cusp fusion; LCC = Left coronary cusp; LV = Left ventricular; MCF = Mixed cusp fusion; NCC = Noncoronary cusp; RCC = Right coronary cusp; TTE = Transthoracic echocardiographic.
Journal of the American College of Cardiology | 2017
Jung Ae Hong; Ungjeong Do; Osung Kwon; Kyusup Lee; Do-Yoon Kang; Yu Na Kim; Jae Seok Bae; Min Soo Cho; Cheol Hyun Lee; Pil Hyung Lee; Jung-Min Ahn; Duk-Woo Park; Seung-Whan Lee; Young-Hak Kim; Cheol Whan Lee; Seong-Wook Park; Seung-Jung Park
Journal of the American College of Cardiology | 2016
Mineok Chang; Yu Na Kim; Seung-Jung Park; Seong-Wook Park; Cheol Whan Lee; Young-Hak Kim; Seung-Whan Lee; Duk-Woo Park; Soo-Jin Kang; Jung-Min Ahn; Pil Hyung Lee; Se Hun Kang; Cheol Hyun Lee; Min Soo Cho; Jae Seok Bae; Sung Han Yoon; Do-Yoon Kang
Journal of the American College of Cardiology | 2016
Min Soo Cho; Seung-Jung Park; Seong-Wook Park; Cheol Whan Lee; Young-Hak Kim; Seung-Whan Lee; Duk-Woo Park; Soo-Jin Kang; Jung-Min Ahn; Pil Hyung Lee; Se Hun Kang; Cheol Hyun Lee; Jae Seok Bae; Yu Na Kim; Sung Han Yoon; Do-Yoon Kang; Mineok Chang
Journal of the American College of Cardiology | 2016
Byeong Joo Bae; Se Hun Kang; Seung-Jung Park; Seong-Wook Park; Cheol Whan Lee; Young-Hak Kim; Seung-Whan Lee; Duk-Woo Park; Soo-Jin Kang; Jung-Min Ahn; Pil Hyung Lee; Cheol Hyun Lee; Min Soo Cho; Jae Seok Bae; Yu Na Kim; Sung Han Yoon; Do-Yoon Kang; Mineok Chang
Journal of the American College of Cardiology | 2016
Min Soo Cho; Seung-Jung Park; Seong-Wook Park; Cheol Whan Lee; Young-Hak Kim; Seung-Whan Lee; Duk-Woo Park; Soo-Jin Kang; Jung-Min Ahn; Pil Hyung Lee; Se Hun Kang; Cheol Hyun Lee; Jae Seok Bae; Yu Na Kim; Sung Han Yoon; Mineok Chang; Do-Yoon Kang
Journal of the American College of Cardiology | 2016
Pil Hyung Lee; Seung-Jung Park; Seong-Wook Park; Cheol Whan Lee; Young-Hak Kim; Seung-Whan Lee; Duk-Woo Park; Soo-Jin Kang; Jung-Min Ahn; Se Hun Kang; Cheol Hyun Lee; Min Soo Cho; Jae Seok Bae; Yu Na Kim; Sung Han Yoon; Do-Yoon Kang; Mineok Chang
Journal of the American College of Cardiology | 2016
Mineok Chang; Jung-Min Ahn; Duk-Woo Park; Pil Hyung Lee; Jae-Hyung Roh; Sung Han Yoon; Soo-Jin Kang; Seung-Whan Lee; Young-Hak Kim; Cheol Whan Lee; Seong-Wook Park; Seung-Jung Park; Se Hun Kang; Cheol Hyun Lee; Min Soo Cho; Jae Seok Bae; Yu Na Kim; Do-Yoon Kang
Journal of the American College of Cardiology | 2015
Min Soo Cho; Cheol Hyun Lee; Yu Na Kim; Jae Seok Bae; Pil Hyung Lee; Jae-Hyung Roh; Mineok Chang; Sung-Han Yoon; Jung-Min Ahn; Duk-Woo Park; Soo-Jin Kang; Seung-Whan Lee; Young-Hak Kim; Cheol Whan Lee; Seong-Wook Park; Seung-Jung Park