Usefulness of the 2MACE Score to Predicts Adverse Cardiovascular Events in Patients With Atrial Fibrillation.

[1]  Rahul Wadke,et al.  Atrial fibrillation. , 2022, Disease-a-month : DM.

[2]  M. Bozbay,et al.  CHA2DS2-VASc Score Predicts In-Hospital and Long-Term Clinical Outcomes in Patients With ST-Segment Elevation Myocardial Infarction Who Were Undergoing Primary Percutaneous Coronary Intervention , 2017, Clinical and applied thrombosis/hemostasis : official journal of the International Academy of Clinical and Applied Thrombosis/Hemostasis.

[3]  F. Marín,et al.  Direct oral anticoagulants and cardiovascular prevention in patients with nonvalvular atrial fibrillation , 2017, Expert opinion on pharmacotherapy.

[4]  D. Pereg,et al.  CHA2DS2-VASc score and clinical outcomes of patients with acute coronary syndrome. , 2016, European journal of internal medicine.

[5]  L. Fauchier,et al.  Causes of Death and Influencing Factors in Patients with Atrial Fibrillation. , 2016, The American journal of medicine.

[6]  L. Fauchier,et al.  Evaluation of 5 Prognostic Scores for Prediction of Stroke, Thromboembolic and Coronary Events, All-Cause Mortality, and Major Adverse Cardiac Events in Patients With Atrial Fibrillation and Coronary Stenting. , 2016, The American journal of cardiology.

[7]  Mario J. Garcia,et al.  Increased risk of stroke and mortality following new-onset atrial fibrillation during hospitalization , 2016, Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology.

[8]  E. Soliman,et al.  Atrial Fibrillation and Myocardial Infarction: A Systematic Review and Appraisal of Pathophysiologic Mechanisms , 2016, Journal of the American Heart Association.

[9]  M. Çetin,et al.  CHA2DS2-VASc-HS score in non-ST elevation acute coronary syndrome patients: assessment of coronary artery disease severity and complexity and comparison to other scoring systems in the prediction of in-hospital major adverse cardiovascular events , 2016, Anatolian journal of cardiology.

[10]  A. Farcomeni,et al.  Cardiovascular risk stratification in patients with non-valvular atrial fibrillation: the 2MACE score , 2016, Internal and Emergency Medicine.

[11]  Mary Cushman,et al.  Atrial Fibrillation and Risk of ST-Segment–Elevation Versus Non–ST-Segment–Elevation Myocardial Infarction: The Atherosclerosis Risk in Communities (ARIC) Study , 2015, Circulation.

[12]  G. Lip,et al.  Management of acute coronary syndrome in patients with non-valvular atrial fibrillation: results of the European Heart Rhythm Association Survey. , 2014, Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology.

[13]  G. Naccarelli,et al.  CHADS2 and CHA2DS2-VASc risk factors to predict first cardiovascular hospitalization among atrial fibrillation/atrial flutter patients. , 2012, The American journal of cardiology.

[14]  Motoyuki Nakamura,et al.  Relationship between CHA(2)DS(2)-VASc scores and ischemic stroke/cardiovascular events in Japanese patients with paroxysmal atrial fibrillation not receiving anticoagulant therapy. , 2012, Journal of cardiology.

[15]  G. Hankey,et al.  Stroke Risk and Antithrombotic Strategies in Atrial Fibrillation , 2010, Stroke.

[16]  S. Basili,et al.  The risk of myocardial infarction in patients with atrial fibrillation: an unresolved issue , 2010, Internal and emergency medicine.

[17]  Elena B. Elkin,et al.  Extensions to decision curve analysis, a novel method for evaluating diagnostic tests, prediction models and molecular markers , 2008, BMC Medical Informatics Decis. Mak..

[18]  M. Pencina,et al.  Evaluating the added predictive ability of a new marker: From area under the ROC curve to reclassification and beyond , 2008, Statistics in medicine.

[19]  E. Elkin,et al.  Decision Curve Analysis: A Novel Method for Evaluating Prediction Models , 2006, Medical decision making : an international journal of the Society for Medical Decision Making.

[20]  R. Krauss,et al.  Diagnosis and Management of the Metabolic Syndrome: An American Heart Association/National Heart, Lung, and Blood Institute Scientific Statement , 2005, Current opinion in cardiology.

[21]  Xiao-Hua Zhou,et al.  Statistical Methods in Diagnostic Medicine , 2002 .

[22]  李永军,et al.  Atrial Fibrillation , 1999 .

[23]  P. Zimmet,et al.  Definition, diagnosis and classification of diabetes mellitus and its complications. Part 1: diagnosis and classification of diabetes mellitus. Provisional report of a WHO Consultation , 1998, Diabetic medicine : a journal of the British Diabetic Association.

[24]  P. Wolf,et al.  Atrial fibrillation as an independent risk factor for stroke: the Framingham Study. , 1991, Stroke.

[25]  E. DeLong,et al.  Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. , 1988, Biometrics.

[26]  David M Herrington,et al.  Atrial fibrillation and the risk of myocardial infarction. , 2015, JAMA internal medicine.