• Steven W Thiel, Jamie M Rosini, William Shannon, Joshua A Doherty, Scott T Micek, and Marin H Kollef.
• Pulmonary and Critical Care Division, Washington University School of Medicine, St. Louis, Missouri 63110, USA.
• J Hosp Med. 2010 Jan 1;5(1):19-25.

BackgroundHospitalized patients who develop severe sepsis have significant morbidity and mortality. Early goal-directed therapy has been shown to decrease mortality in severe sepsis and septic shock, though a delay in recognizing impending sepsis often precludes this intervention.ObjectiveTo identify early predictors of septic shock among hospitalized non-intensive care unit (ICU) medical patients.DesignRetrospective cohort analysis.SettingA 1200-bed academic medical center.PatientsDerivation cohort consisted of 13,785 patients hospitalized during 2005. The validation cohorts consisted of 13,737 patients during 2006 and 13,937 patients from 2007.InterventionDevelopment and prospective validation of a prediction model using Recursive Partitioning And Regression Tree (RPART) analysis.MethodsRPART analysis of routine laboratory and hemodynamic variables from the derivation cohort to identify predictors prior to the occurrence of shock. Two models were generated, 1 including arterial blood gas (ABG) data and 1 without.ResultsWhen applied to the 2006 cohort, 347 (54.7%) and 121 (19.1%) of the 635 patients developing septic shock were correctly identified by the 2 models, respectively. For the 2007 patients, the 2 models correctly identified 367 (55.0%) and 102 (15.3%) of the 667 patients developing septic shock, respectively.ConclusionsReadily available data can be employed to predict non-ICU patients who develop septic shock several hours prior to ICU admission.(c) 2010 Society of Hospital Medicine.

17 keywords...

hide…