Methods of creatine kinase-MB analysis to predict mortality in patients with myocardial infarction treated with reperfusion therapy.
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BACKGROUND: Larger infarct size measured by creatine kinase (CK)-MB release is associated with higher mortality and has been used as an important surrogate endpoint in the evaluation of new treatments for ST-segment elevation myocardial infarction (STEMI). Traditional approaches to quantify infarct size include the observed CK-MB peak and calculated CK-MB area under the curve (AUC). We evaluated alternative approaches to quantifying infarct size using CK-MB values, and the relationship between infarct size and clinical outcomes. METHODS: Of 1,850 STEMI patients treated with reperfusion therapy in the COMplement inhibition in Myocardial infarction treated with Angioplasty (COMMA) (percutaneous coronary intervention (PCI)-treated) and the COMPlement inhibition in myocardial infarction treated with thromboLYtics (COMPLY) (fibrinolytic-treated) trials, 1,718 (92.9%) (COMMA, n = 868; COMPLY, n = 850) had at least five of nine protocol-required CK-MB measures. In addition to traditional methods, curve-fitting techniques were used to determine CK-MB AUC and estimated peak CK-MB. Cox proportional hazards modeling assessed the univariable associations between infarct size and mortality, and the composite of death, heart failure, shock and stroke at 90 days. RESULTS: In COMPLY, CK-MB measures by all methods were significantly associated with higher mortality (hazard ratio range per 1,000 units increase: 1.09 to 1.13; hazard ratio range per 1 standard deviation increase: 1.41 to 1.62; P <0.01 for all analyses). In COMMA, the associations were similar but did not reach statistical significance. For the composite outcome of 90-day death, heart failure, shock and stroke, the associations with all CK-MB measures were statistically significant in both the COMMA and COMPLY trials. CONCLUSIONS: Sophisticated curve modeling is an alternative to infarct-size quantification in STEMI patients, but it provides information similar to that of more traditional methods. Future studies will determine whether the same conclusion applies in circumstances other than STEMI, or to studies with different frequencies and patterns of CK-MB data collection.
Published Version (Please cite this version)
Lopes, Renato D, Yuliya Lokhnygina, Victor Hasselblad, Kristin L Newby, Eric Yow, Christopher B Granger, Paul W Armstrong, Judith S Hochman, et al. (2013). Methods of creatine kinase-MB analysis to predict mortality in patients with myocardial infarction treated with reperfusion therapy. Trials, 14. p. 123. 10.1186/1745-6215-14-123 Retrieved from https://hdl.handle.net/10161/12499.
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Antithrombotic Therapy in patients with Acute Coronary Syndromes
Elderly patients with Heart Disease
Biomarkers in Acute Coronary Syndromes and Atrial Fibrillation
Thrombosis and Anticoagulation and novel antithrombotic agents
Metabolomics in Cardiovascular Medicine
Statistical methods in clinical trials, survival analysis, adaptive designs, adaptive treatment strategies, causal inference in observational studies, semiparametric inference
The research interests of Vic Hasselblad include distribution fitting, sample size and power calculations, dose-response estimation, meta-analysis, and non-inferiority designs.
My primary research interest is in conduct and methodology of large randomized clinical trials in heart disease. I have led a number of large international clinical studies in heart attacks, unstable angina, heart failure, and atrial fibrillation. I have lead clinical studies of blood thinners and coronary intervention for heart attacks, stroke prevention in atrial fibrillation, and prevention of heart attack for patients with coronary artery disease. I have been co-director of the Reperfusion of Acute MI in Carolina Emergency Departments (RACE) project that is a North Carolina state-wide program to improve reperfusion care for acute myocardial infarction. I serve as the Chairman of the American Heart Association Mission: Lifeline program to improve heart attack care nationally as well as the American College of Cardiology/American Heart Association guideline committee for heart attack care. I have also studied the effects of genetic variation on heart disease. I work with the National Institute of Health and the Federal Drug Administration on evaluation of heart disease and of new drugs. I have developed tools to predict which patients are at risk for death, heart attack, and need for hospitalization.
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