State variable effects in graphical event models
Debarun Bhattacharjya, Dharmashankar Subramanian, et al.
IJCAI 2020
Objective: In septic patients, multiple retrospective studies show an association between large volumes of fluids administered in the first 24 h and mortality, suggesting a benefit to fluid restrictive strategies. However, these studies do not directly estimate the causal effects of fluid-restrictive strategies, nor do their analyses properly adjust for time-varying confounding by indication. In this study, we used causal inference techniques to estimate mortality outcomes that would result from imposing a range of arbitrary limits ("caps") on fluid volume administration during the first 24 h of intensive care unit (ICU) care. Design: Retrospective cohort study Setting: ICUs at the Beth Israel Deaconess Medical Center, 2008-2012 Patients: One thousand six hundred thirty-nine septic patients (defined by Sepsis-3 criteria) 18 years and older, admitted to the ICU from the emergency department (ED), who received less than 4 L fluids administered prior to ICU admission Measurements and main results: Data were obtained from the Medical Information Mart for Intensive Care III (MIMIC-III). We employed a dynamic Marginal Structural Model fit by inverse probability of treatment weighting to obtain confounding adjusted estimates of mortality rates that would have been observed had fluid resuscitation volume caps between 4 L-12 L been imposed on the population. The 30-day mortality in our cohort was 17%. We estimated that caps between 6 and 10 L on 24 h fluid volume would have reduced 30-day mortality by - 0.6 to - 1.0%, with the greatest reduction at 8 L (- 1.0% mortality, 95% CI [- 1.6%, - 0.3%]). Conclusions: We found that 30-day mortality would have likely decreased relative to observed mortality under current practice if these patients had been subject to "caps" on the total volume of fluid administered between 6 and 10 L, with the greatest reduction in mortality rate at 8 L.
Debarun Bhattacharjya, Dharmashankar Subramanian, et al.
IJCAI 2020
Somin Wadhwa, Oktie Hassanzadeh, et al.
ISWC 2024
Futoshi Iwama, Miki Enoki, et al.
SMDS 2021
Debarun Bhattacharjya, Oktie Hassanzadeh, et al.
IJCAI 2023