Predicting Readmission or Death After Acute ST‐Elevation Myocardial Infarction

Risk factors for emergent readmissions or death after acute myocardial infarction (AMI) are important in identifying patients at risk for major adverse events. However, there has been limited investigation conducted of prospective clinical registries to determine relevant risk factors.

[1]  D. Hosmer,et al.  A review of goodness of fit statistics for use in the development of logistic regression models. , 1982, American journal of epidemiology.

[2]  J. Hanley,et al.  The meaning and use of the area under a receiver operating characteristic (ROC) curve. , 1982, Radiology.

[3]  Robert Tibshirani,et al.  Bootstrap Methods for Standard Errors, Confidence Intervals, and Other Measures of Statistical Accuracy , 1986 .

[4]  J. Buring,et al.  Epidemiology in Medicine , 1987 .

[5]  E. Antman,et al.  TIMI Risk Score for ST-Elevation Myocardial Infarction: A Convenient, Bedside, Clinical Score for Risk Assessment at Presentation: An Intravenous nPA for Treatment of Infarcting Myocardium Early II Trial Substudy , 2000, Circulation.

[6]  D. Gifford,et al.  Access to postacute nursing home care before and after the BBA. Balanced Budget Act. , 2002, Health affairs.

[7]  D. Fuchs,et al.  Predicting Mortality in Patients With ST-Elevation Myocardial Infarction Treated With Primary Percutaneous Coronary Intervention (PAMI Risk Score) , 2004 .

[8]  G. Stone,et al.  Predicting mortality in patients with ST-elevation myocardial infarction treated with primary percutaneous coronary intervention (PAMI risk score). , 2004, The American journal of cardiology.

[9]  K. Eagle,et al.  In-hospital revascularization and one-year outcome of acute coronary syndrome patients stratified by the GRACE risk score. , 2005, The American journal of cardiology.

[10]  B. Gersh,et al.  Prediction of mortality after primary percutaneous coronary intervention for acute myocardial infarction: the CADILLAC risk score. , 2005, Journal of the American College of Cardiology.

[11]  Sharon-Lise T. Normand,et al.  An Administrative Claims Measure Suitable for Profiling Hospital Performance on the Basis of 30-Day All-Cause Readmission Rates Among Patients With Heart Failure , 2008, Circulation. Cardiovascular quality and outcomes.

[12]  R. Kornowski,et al.  Comparison of the predictive value of four different risk scores for outcomes of patients with ST-elevation acute myocardial infarction undergoing primary percutaneous coronary intervention. , 2008, The American journal of cardiology.

[13]  E. Rackow Rehospitalizations among patients in the Medicare fee-for-service program. , 2009, The New England journal of medicine.

[14]  M. Desai,et al.  Statistical Models and Patient Predictors of Readmission for Acute Myocardial Infarction: A Systematic Review , 2009, Circulation. Cardiovascular quality and outcomes.

[15]  Harlan M. Krumholz,et al.  An Administrative Claims Measure Suitable for Profiling Hospital Performance Based on 30-Day All-Cause Readmission Rates Among Patients With Acute Myocardial Infarction , 2011, Circulation. Cardiovascular quality and outcomes.

[16]  Samin K. Sharma,et al.  30-day readmission for patients undergoing percutaneous coronary interventions in New York state. , 2011, JACC. Cardiovascular interventions.

[17]  S. Normand,et al.  Sources of Hospital Variation in Short-Term Readmission Rates After Percutaneous Coronary Intervention , 2012, Circulation. Cardiovascular interventions.

[18]  B. Gersh,et al.  Factors associated with 30-day readmission rates after percutaneous coronary intervention. , 2012, Archives of internal medicine.

[19]  Marcin R Dada,et al.  All-cause readmission and repeat revascularization after percutaneous coronary intervention. , 2012, Cardiology journal.

[20]  Shoshannah A. Pearlman The Patient Protection and Affordable Care Act , 2013, Journal of the American Psychiatric Nurses Association.

[21]  S. Chae,et al.  Incremental Predictive Value of Red Cell Distribution Width for 12‐Month Clinical Outcome After Acute Myocardial Infarction , 2013, Clinical cardiology.

[22]  G. Ephrem,et al.  Red Blood Cell Distribution Width Is a Predictor of Readmission in Cardiac Patients , 2013, Clinical cardiology.

[23]  Wenyaw Chan,et al.  Statistical Methods in Medical Research , 2013, Model. Assist. Stat. Appl..