Early prediction of septic shock in hospitalized patients.
BACKGROUND
Hospitalized 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.


OBJECTIVE
To identify early predictors of septic shock among hospitalized non-intensive care unit (ICU) medical patients.


METHODS
Retrospective cohort analysis.


METHODS
A 1200-bed academic medical center.


METHODS
Derivation 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.


METHODS
Development and prospective validation of a prediction model using Recursive Partitioning And Regression Tree (RPART) analysis.


METHODS
RPART 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.


RESULTS
When 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.


CONCLUSIONS
Readily available data can be employed to predict non-ICU patients who develop septic shock several hours prior to ICU admission.
Thiel
Steven W
SW
Pulmonary and Critical Care Division, Washington University School of Medicine, St. Louis, Missouri 63110, USA.
Rosini
Jamie M
JM
Shannon
William
W
Doherty
Joshua A
JA
Micek
Scott T
ST
Kollef
Marin H
MH
D000046:Academic Medical Centers; D015415:Biomarkers; D015331:Cohort Studies; D042241:Early Diagnosis; D006760:Hospitalization; D006801:Humans; D008923:Missouri; D008962:Models, Theoretical; D011237:Predictive Value of Tests; D012189:Retrospective Studies; D018570:Risk Assessment / Q000379:methods; D012772:Shock, Septic / Q000175:diagnosis* / Q000209:etiology
D015415:Biomarkers