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. 2017 Feb 10:2016:954-963.
eCollection 2016.

Predicting Prolonged Stay in the ICU Attributable to Bleeding in Patients Offered Plasma Transfusion

Che Ngufor  1 , Dennis Murphree  1 , Sudhi Upadhyaya  1 , Nageswar Madde  1 , Jyotishman Pathak  2 , Rickey Carter  1 , Daryl Kor  1
Affiliations

Predicting Prolonged Stay in the ICU Attributable to Bleeding in Patients Offered Plasma Transfusion

Che Ngufor et al. AMIA Annu Symp Proc. .

Abstract

In blood transfusion studies, plasma transfusion (PPT) and bleeding are known to be associated with risk of prolonged ICU length of stay (ICU-LOS). However, as patients can show significant heterogeneity in response to a treatment, there might exists subgroups with differential effects. The existence and characteristics of these subpopulations in blood transfusion has not been well-studied. Further, the impact of bleeding in patients offered PPT on prolonged ICU-LOS is not known. This study presents a causal and predictive framework to examine these problems. The two-step approach first estimates the effect of bleeding in PPT patients on prolonged ICU-LOS and then estimates risks of bleeding and prolonged ICU-LOS. The framework integrates a classification model for risks prediction and a regression model to predict actual LOS. Results showed that the effect of bleeding in PPT patients significantly increases risk of prolonged ICU-LOS (55%, p=0.00) while no bleeding significantly reduces ICU-LOS (4%, p=0.046).

Keywords: Blood transfusion; bleeding; classification; machine learning; perioperative.

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Figures

Figure 1:
Figure 1:
Two Level Predictive Model
Figure 2:
Figure 2:
ICU-LOS Distribution
See this image and copyright information in PMC

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