Early prediction of septic shock in hospitalized patients

✍ Scribed by Steven W. Thiel; Jamie M. Rosini; William Shannon; Joshua A. Doherty; Scott T. Micek; Marin H. Kollef

• Publisher: John Wiley and Sons
• Year: 2010
• Tongue: English
• Weight: 245 KB
• Volume: 5
• Category: Article
• ISSN: 1553-5592
• DOI: 10.1002/jhm.530

✦ Synopsis

Abstract

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.