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Risk Scoring System to Assess Outcomes in Patients Treated with Contemporary Guideline-Adherent Optimal Therapies after Acute Myocardial Infarction

  • Song, Pil Sang (Division of Cardiology, Heart Stroke Vascular Center, Mediplex Sejong General Hospital) ;
  • Ryu, Dong Ryeol (Division of Cardiology, Department of Internal Medicine, Kangwon National University Hospital, Kangwon National University School of Medicine) ;
  • Kim, Min Jeong (Division of Cardiology, Cardiovascular Center, Mediplex Sejong Hospital) ;
  • Jeon, Ki-Hyun (Division of Cardiology, Cardiovascular Center, Mediplex Sejong Hospital) ;
  • Choi, Rak Kyeong (Division of Cardiology, Cardiovascular Center, Mediplex Sejong Hospital) ;
  • Park, Jin Sik (Division of Cardiology, Cardiovascular Center, Mediplex Sejong Hospital) ;
  • Song, Young Bin (Division of Cardiology, Department of Internal Medicine, Heart Vascular Stroke Institute, Samsung Medical Center, Sungkyunkwan University School of Medicine) ;
  • Hahn, Joo-Yong (Division of Cardiology, Department of Internal Medicine, Heart Vascular Stroke Institute, Samsung Medical Center, Sungkyunkwan University School of Medicine) ;
  • Gwon, Hyeon-Cheol (Division of Cardiology, Department of Internal Medicine, Heart Vascular Stroke Institute, Samsung Medical Center, Sungkyunkwan University School of Medicine) ;
  • Ahn, Youngkeun (Heart Research Center, Chonnam National University College of Medicine) ;
  • Jeong, Myung Ho (Heart Research Center, Chonnam National University College of Medicine) ;
  • Choi, Seung-Hyuk (Division of Cardiology, Department of Internal Medicine, Heart Vascular Stroke Institute, Samsung Medical Center, Sungkyunkwan University School of Medicine)
  • 투고 : 2017.09.15
  • 심사 : 2018.02.22
  • 발행 : 2018.06.30

초록

Background and Objectives: A risk prediction is needed even in the contemporary era of acute myocardial infarction (AMI). We sought to develop a risk scoring specific for patients with AMI being treated with guideline-adherent optimal therapies, including percutaneous coronary intervention and all 5 medications (aspirin, thienopyridine, ${\beta}-blocker$, angiotensin-converting enzyme inhibitor or angiotensin receptor blocker, and statin). Methods: From registries, 12,174 AMI patients were evaluated. The primary outcome was 1-year all-cause death or AMI. The Korea Working Group in Myocardial Infarction (KorMI) system was compared with the Assessment of Pexelizumab in Acute Myocardial Infarction (APEX AMI), Controlled Abciximab and Device Investigation to Lower Late Angioplasty Complications (CADILLAC), and Global Registry of Acute Coronary Events scores (GRACE) models. Results: Ten predictors were identified: left ventricular dysfunction (hazard ratio [HR], 2.3), bare-metal stent (HR, 2.0), Killip class ${\geq}II$ (HR, 1.9), renal insufficiency (HR, 1.8), previous stroke (HR, 1.6), regional wall-motion-score >20 on echocardiography (HR, 1.5), body mass index ${\leq}24kg/m^2$ (HR, 1.4), age ${\geq}70years$ (HR, 1.4), prior coronary heart disease (HR, 1.4), and diabetes (HR, 1.4). Compared with the previous models, the KorMI system had good discrimination (time-dependent C statistic, 0.759) and showed reasonable goodness-of-fit by Hosmer-Lemeshow test (p=0.84). Moreover, the continuous-net reclassification improvement varied from -27.3% to -19.1%, the integrated discrimination index varied from -2.1% to -0.9%, and the median improvement in risk score was from -1.0% to -0.4%. Conclusions: The KorMI system would be a useful tool for predicting outcomes in survivors treated with guideline-adherent optimal therapies after AMI.

키워드

과제정보

연구 과제 주관 기관 : Ministry of Health and Welfare

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피인용 문헌

  1. Deep-learning-based risk stratification for mortality of patients with acute myocardial infarction vol.14, pp.10, 2018, https://doi.org/10.1371/journal.pone.0224502
  2. Predictive Factors on the Incidence of Heart Failure in Patients with Ischemic Heart Disease: Using a 10-Year Population-Based Korea National Health Insurance Cohort Data vol.17, pp.22, 2018, https://doi.org/10.3390/ijerph17228670