title: Predicting outcomes for cardiac surgery patients after intensive care unit admission.
abstract: Most performance assessments of cardiac surgery programs use models based on preoperative risk factors. Models that were primarily developed to assess performance in general intensive care unit (ICU) populations have also been used to evaluate the quality of surgical, anesthetic, and ICU management after cardiac surgery. Although there are currently 5 models for evaluating general ICU populations, only the Acute Physiology and Chronic Health Evaluation (APACHE) system has been independently validated for cardiac surgery patients. This review describes the evolution, rationale, and accuracy of APACHE models that are specific for cardiac surgery patients as well as for patients who have had vascular and thoracic procedures. In addition to performance comparisons based on observed and predicted mortality, APACHE provides similar comparisons of ICU and hospital lengths of stay and duration of mechanical ventilation. However, the low mortality incidence of many cardiac outcomes means that very large numbers of patients must be obtained to get good predictive models. Thus, the equations are not designed for predicting individual patients' outcome but have proven useful in performance comparisons and for quality improvement initiatives.
authors.affiliation: Cerner Corporation, Vienna, Virginia 22182, USA. akramer@cerner.com
authors.forename: Andrew A
authors.initials: AA
authors.lastname: Kramer
authors.forename: Jack E
authors.initials: JE
authors.lastname: Zimmerman
mesh_terms: D018806:APACHE; D000465:Algorithms; D006348:Cardiac Surgical Procedures; D003422:Critical Care; D006801:Humans; D007362:Intensive Care Units / Q000706:statistics & numerical data*; D015233:Models, Statistical; D011237:Predictive Value of Tests; D016896:Treatment Outcome