Session P7A.7

Septic Shock: A Multivariate Logistic Regression Early Warning System

D Shavdia*, A Reisner, R Mark

Massachusetts Institute of Technology
Boston, MA, USA

Early goal-directed therapy (EGDT) in severe sepsis and septic shock has shown to provide substantial benefits in patient outcomes. However, these preventive therapeutic interventions are contingent upon an early detection or suspicion of the underlying septic etiology. Detection of sepsis in the early stages can be difficult, as the initial pathogenesis can occur while the patient is still displaying normal vital signs. This study focuses on developing an early warning system (EWS) to provide clinicians with a forewarning of an impending hypotensive crisis—thus allowing for EGDT intervention. A multivariate logistic regression model was generated to differentiate between 107 high-risk sepsis patients of whom 39 experienced a hypotensive crisis and 68 who remained stable. The model was tested using 7-fold cross validation; the mean area under the receiver operating characteristic (ROC) curve was 0.87 ± 0.15. The EWS was then tested in a forward, casual manner on a random cohort of 304 ICU patients to mimic the patients’ stay in the unit. The algorithm performed with a sensitivity of 0.70 and a positive predictive value (PPV) of 0.74. The mean early warning time at this performance level was 582 ± 340 minutes.

(Abstract Control Number: 270)