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 id...

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Published in:Journal of hospital medicine 2010-01, Vol.5 (1), p.19-25
Main Authors: Thiel, Steven W., Rosini, Jamie M., Shannon, William, Doherty, Joshua A., Micek, Scott T., Kollef, Marin H.
Format: Article
Language:English
Subjects:
Academic Medical Centers
Biomarkers
Cohort Studies
Early Diagnosis
Hospitalization
Humans
Missouri
Models, Theoretical
prediction
Predictive Value of Tests
Retrospective Studies
Risk Assessment - methods
sepsis
shock
Shock, Septic - diagnosis
Shock, Septic - etiology
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Summary: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. DESIGN: Retrospective cohort analysis. SETTING: A 1200‐bed academic medical center. PATIENTS: 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. INTERVENTION: 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. Journal of Hospital Medicine 2010;5:19–25. © 2010 Society of Hospital Medicine.
ISSN:1553-5592
1553-5606
DOI:10.1002/jhm.530