• Benjamin Dummitt, Angelique Zeringue, Ashok Palagiri, Christopher Veremakis, Benjamin Burch, and Byron Yount.
• Mercy Virtual Care Center, 15740 S. Outer Forty, Chesterfield, MO 63017, USA. Electronic address: benjamin.dummitt@mercy.net.
• J Crit Care. 2018 Dec 1; 48: 339-344.

PurposeTo determine the efficacy of survival analysis for predicting septic shock onset in ICU patients.Materials And MethodsWe performed a retrospective analysis on ICU cases from Mercy Hospital St. Louis from 2012 to 2016. As part of the procedure for inclusion in the Apache Outcomes database, each case is reviewed by critical care clinicians to identify septic shock patients as well as the time of septic shock onset. We used survival analysis to predict septic shock onset in these cases and employed lagging to compensate for uncertainties in septic shock onset time.ResultsSurvival analysis was highly effective at predicting septic shock onset, producing AUC values of >0.87. The methodology was robust to lag times as well as the specific method of survival analysis used.ConclusionsThis methodology has the potential to be implemented in the ICU for real time prediction and can be used as a building block to expand the approach to other hospital wards or care environments.Copyright © 2018 Elsevier Inc. All rights reserved.

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