Sepsis prediction models are trained on labels that diverge from clinician-recommended treatment times

Many sepsis prediction models use the Sepsis-3 definition or its variants as a training label. However, among the few sepsis models ever deployed in practice, there is scant evidence that they offer clinically meaningful decision support at the bedside. As a potential mechanism to explain this limitation, we hypothesized that clinician-recommended treatment times for sepsis would diverge from onset time defined by Sepsis-3. We conducted an electronic survey that was completed by 153 clinicians at three large and geographically diverse medical centers using vignettes derived from eight real cases of sepsis. After reviewing these vignettes, participants suggested antibiotic treatment to start an average of 7.0 hours (95% confidence interval 5.3 to 8.8) before the Sepsis-3 definition onset. Thus, predicting Sepsis-3 onset as a treatment prompt could lead to inappropriate and delayed treatment recommendations. Building predictive decision support systems that identify outcomes aligned with bedside decisions would increase their clinical utility.

American Thoracic Society Research Foundation Grant in Critical Care
National Heart, Lung, and Blood Institute

Gary E Weissman, Rebecca A Hubbard, Blanca E Himes, Kelly L Goodman-O’Leary, Michael O Harhay, Jennifer C Ginestra, Rachel Kohn, Andrew J Admon, Stephanie Parks Taylor, Scott D Halpern