Mortality Risk Profiles for Sepsis: A Novel Longitudinal and Multivariable Approach

Mortality Risk Profiles for Sepsis: A Novel Longitudinal and Multivariable Approach

Objectives:. 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....

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Autores principales: Patricia C. Liaw, PhD, Alison E. Fox-Robichaud, MSc, MD, FRCPC, Kao-Lee Liaw, PhD, Ellen McDonald, RN, Dhruva J. Dwivedi, PhD, Nasim M. Zamir, MD, Laura Pepler, PhD, Travis J. Gould, PhD, Michael Xu, MSc, Nicole Zytaruk, RN, Sarah K. Medeiros, BSc, Lauralyn McIntyre, MD, FRCPC, Jennifer Tsang, MD, PhD, FRCPC, Peter M. Dodek, MD, MHSc, Brent W. Winston, MD, FRCPC, Claudio Martin, MSc, MD, FRCPC, Douglas D. Fraser, MD, PhD, FRCPC, Jeffrey I. Weitz, MD, FRCPC, Francois Lellouche, MD, PhD, Deborah J. Cook, MD, FRCPC, John Marshall, MD, FRCPC, for the Canadian Critical Care Translational Biology Group (CCCTBG) and the Canadian Critical Care Trials Group (CCCTG), Jamie Hutchison, Jane Batt, Emmanuel Charbonney, Jean-Francois Cailhier, Rob Fowler, Paul Hebert, Kusum Menon, Karen Burns, Shane English, John Drover, Bram Rochwerg, Dominique Piquette, Margaret Herridge, Sylvie Debigare, Srinivas Murthy, Michelle Kho, Danae Tassy
Formato: article
Lenguaje:EN
Publicado: Wolters Kluwer 2019
Materias:
Medical emergencies. Critical care. Intensive care. First aid
RC86-88.9
Acceso en línea:https://doaj.org/article/322866702a8847a9bc12e98249ff2dbb
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Sumario:Objectives:. 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.

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