title: Predicting readmission or death after acute ST-elevation myocardial infarction.
abstract: BACKGROUND
  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.
  
  
  OBJECTIVE
  We hypothesize 30-day readmission or death could be predicted using patient, procedural, and process factors.
  
  
  METHODS
  Patients presenting with ST-elevation myocardial infarction (STEMI) from 2006 to 2011 were prospectively enrolled in a STEMI registry (1271 patients). Thirty-day readmission was ascertained by administrative claims data. Death was determined by linking to the Social Security Death Master File. Univariate and stepwise multivariate logistic regression was conducted with Hosmer-Lemeshow goodness-of-fit statistics for model calibration and receiver operating characteristic (ROC) curve for model discrimination.
  
  
  RESULTS
  The combined end point of 30-day readmission or postdischarge death included 135 patients (10.6%), including 109 emergent readmissions and 26 deaths. Factors associated with an increase risk of 30-day readmission or postdischarge death included age ≥ 80 years, diabetes, chest pain or cardiac arrest at presentation, and 3-vessel disease found at initial angiography. Factors associated with a decreased risk of 30-day readmission or postdischarge death included transfer to the catheterization lab from another emergency department, clopidogrel given during the procedure hypercholesterolemia, and receiving aspirin, β-blockers, and angiotensin-converting enzyme or angiotensin receptor blocker inhibitors at discharge. Index admission outcomes indicative of readmission or death postdischarge only included a new diagnosis of congestive heart failure. The model discriminated well with an ROC of 0.71 (95% confidence interval: 0.66-0.76).
  
  
  CONCLUSIONS
  Prehospitalization factors are overlooked and are important factors to incorporate in routine risk prediction models for readmission or death within 30 days following an AMI.
authors.affiliation: The Dartmouth Institute for Health Policy and Clinical Practice, Geisel School of Medicine at Dartmouth,Lebanon, New Hampshire; Section of Cardiology, Department of Medicine, Dartmouth-Hitchcock Medical Center, Lebanon, New Hampshire.
authors.forename: Jeremiah R
authors.initials: JR
authors.lastname: Brown
authors.forename: Sheila M
authors.initials: SM
authors.lastname: Conley
authors.forename: Nathaniel W
authors.initials: NW
authors.lastname: Niles
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D019540:Area Under Curve; D016009:Chi-Square Distribution; D006801:Humans; D016015:Logistic Models; D008875:Middle Aged; D015999:Multivariate Analysis; D009203:Myocardial Infarction / Q000175:diagnosis / Q000401:mortality* / Q000628:therapy*; D010359:Patient Readmission; D011446:Prospective Studies; D012372:ROC Curve; D012042:Registries; D018570:Risk Assessment; D012307:Risk Factors; D013997:Time Factors