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

Che Ngufor, Dennis Murphree, Sudhi Upadhyaya, Nageswar Madde, Jyotishman Pathak, Rickey E. Carter, Daryl J Kor

Research output: Contribution to journalArticle

2 Scopus citations

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).

Original languageEnglish (US)
Pages (from-to)954-963
Number of pages10
JournalAMIA ... Annual Symposium proceedings. AMIA Symposium
Volume2016
StatePublished - 2016

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Keywords

  • bleeding
  • Blood transfusion
  • classification
  • machine learning
  • perioperative

ASJC Scopus subject areas

  • Medicine(all)

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