We used Cox proportional-hazards models to determine whether mild and moderate renal insufficiency were independent predictors of 1-year mortality (15). These models were adjusted for patient demographic characteristics (age, sex, race, rural or urban setting, and region of the United States); comorbid conditions (history of diabetes mellitus, hypertension, hypercholesterolemia, tobacco use, congestive heart failure, stroke, peripheral vascular disease, angina, myocardial infarction, percutaneous transluminal coronary angioplasty, coronary artery bypass graft surgery, chronic obstructive pulmonary disease, dementia, inability to ambulate, depression, and incontinence); severity of clinical presentation (Killip class, electrocardiogram findings, heart rate, mean arterial blood pressure, alertness and orientation according to the Glasgow coma scale, duration of chest pain, and blood urea nitrogen level [< 30 mg/dL; <10.7 mmol/L as urea or ≥ 30 mg/dL; ≥ 10.7 mmol/L as urea]); hospital characteristics (capability to do coronary angiography and revascularization; volume of myocardial infarction admissions); in-hospital treatments (aspirin, β-blockers, ACE inhibitors, thrombolytic therapy, intravenous nitroglycerin, coronary angiography, percutaneous transluminal coronary angioplasty, and coronary artery bypass graft surgery); and discharge medications (aspirin, β-blockers, calcium-channel blockers, and ACE inhibitors). We evaluated the inclusion of a categorical variable for each hospital (n = 4200) in a 10% sample of our data set, but it had little effect on the association of renal function with survival after myocardial infarction. We also checked for violations of linearity by examining augmented models, which included quadratic terms for continuous predictors.