Mortality Risk Profiles for Sepsis: A Novel Longitudinal and Multivariable Approach Academic Article uri icon

  •  
  • Overview
  •  
  • Research
  •  
  • Identity
  •  
  • Additional Document Info
  •  
  • View All
  •  

abstract

  • To determine if a set of time-varying biological indicators can be used to: 1) predict the sepsis mortality risk over time and 2) generate mortality risk profiles. Design: Prospective observational study. Setting: Nine Canadian ICUs. Subjects: Three-hundred fifty-six septic patients. Interventions: None. Measurements and Main Results: Clinical data and plasma levels of biomarkers were collected longitudinally. We used a complementary log-log model to account for the daily mortality risk of each patient until death in ICU/hospital, discharge, or 28 days after admission. The model, which is a versatile version of the Cox model for gaining longitudinal insights, created a composite indicator (the daily hazard of dying) from the "day 1" and "change" variables of six time-varying biological indicators (cell-free DNA, protein C, platelet count, creatinine, Glasgow Coma Scale score, and lactate) and a set of contextual variables (age, presence of chronic lung disease or previous brain injury, and duration of stay), achieving a high predictive power (conventional area under the curve, 0.90; 95% CI, 0.86-0.94). Including change variables avoided misleading inferences about the effects of day 1 variables, signifying the importance of the longitudinal approach. We then generated mortality risk profiles that highlight the relative contributions among the time-varying biological indicators to overall mortality risk. The tool was validated in 28 nonseptic patients from the same ICUs who became septic later and was subject to 10-fold cross-validation, achieving similarly high area under the curve. Conclusions: Using a novel version of the Cox model, we created a prognostic tool for septic patients that yields not only a predicted probability of dying but also a mortality risk profile that reveals how six time-varying biological indicators differentially and longitudinally account for the patient's overall daily mortality risk.

authors

  • Liaw, Patricia C
  • Fox-Robichaud, Alison E
  • Liaw, Kao-Lee
  • McDonald, Ellen
  • Dwivedi, Dhruva J
  • Zamir, Nasim M
  • Pepler, Laura
  • Gould, Travis J
  • Xu, Michael
  • Zytaruk, Nicole
  • Medeiros, Sarah K
  • McIntyre, Lauralyn
  • Tsang, Jennifer
  • Dodek, Peter M
  • Winston, Brent W
  • Martin, Claudio
  • Fraser, Douglas D
  • Weitz, Jeffrey I
  • Lellouche, Francois
  • Cook, Deborah
  • Marshall, John

publication date

  • August 2019