title: Prognosis in critical care.
abstract: Prognostic risk prediction models have been employed in the intensive care unit (ICU) setting since the 1980s and provide health care providers with important information to help inform decisions related to treatment and prognosis, as well as to compare outcomes across institutions. Prognostic models for critical care are among the most widely utilized and tested predictive models in healthcare. In this article, we review and compare mortality prediction models, including the APACHE (1981), SAPS (1984), APACHE-II (1985), MPM (1987), APACHE-III (1991), SAPS-II (1993), and MPM-II (1993). We emphasize the importance of model calibration in this domain. In addition, we present a brief review of the statistical methodology, multiple logistic regression, which underlies most of the models currently used in critical care.
authors.affiliation: Decision Systems Group, Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts 02115, USA.
authors.forename: Lucila
authors.initials: L
authors.lastname: Ohno-Machado
authors.forename: Frederic S
authors.initials: FS
authors.lastname: Resnic
authors.forename: Michael E
authors.initials: ME
authors.lastname: Matheny
mesh_terms: D001185:Artificial Intelligence; D003422:Critical Care / Q000379:methods* / Q000458:organization & administration*; D020000:Decision Support Systems, Clinical; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D006305:Health Status Indicators; D006801:Humans; D011379:Prognosis; D016016:Proportional Hazards Models; D018570:Risk Assessment / Q000379:methods*; D012307:Risk Factors