title: Identification of disease states associated with coagulopathy in trauma.
abstract: BACKGROUND
  Trauma is the leading cause of death between the ages of 1 to 44 in the United States. Blood loss is the primary cause of these deaths. The discrimination of states through which patients transition would be helpful in understanding the disease process, and in identification of critical states and appropriate interventions. Even though these states are strongly associated with patients' blood composition data, there has not been a way to directly identify them. Statistical tools such as hidden Markov models can be used to infer the discrete latent states from the blood composition data.
  
  
  METHODS
  We applied a hidden Markov model to time-series multivariate patient measurements from the UCSF/ San Francisco General Hospital and Trauma Center. Ten blood factor related measurements were used to identify the model: factors II, V, VII, VIII, IX, X, antithrombin III, protein C, prothrombin time and partial thromboplastin time. Missing data in the time-series dataset was considered in the hidden Markov model. The number of states was determined by minimizing the Bayesian information criterion across different numbers of states.
  
  
  RESULTS
  After preprocessing, 1090 patients with a total number of 2176 time point measurements were included in the analysis. The hidden Markov model identified 6 disease states and 3 stages. We analyzed their relationships to the blood composition data and the coagulation cascade. The states are very indicative of the disease progression status of patients.
  
  
  CONCLUSIONS
  Six disease states and 3 stages associated with Coagulopathy in trauma were identified in our study. The hidden Markov model can be useful in identifying latent states by using patients' time-series multivariate data. The information obtained from the states and stages can be useful in the clinical setting.
authors.affiliation: Department of Computer Science, University of California, Santa Barbara, USA. zhangyy1209@gmail.com.
authors.forename: Yuanyang
authors.identifier: http://orcid.org/0000-0002-5901-4242
authors.initials: Y
authors.lastname: Zhang
authors.affiliation: Department of Mechanical Engineering, University of California, Santa Barbara, USA.
authors.forename: Tie Bo
authors.initials: TB
authors.lastname: Wu
authors.affiliation: Departments of Biological Sciences and Computer Science, University of Memphis, Memphis, USA.
authors.forename: Bernie J
authors.initials: BJ
authors.lastname: Daigle
authors.affiliation: Department of Surgery, University of California, San Francisco, USA.
authors.forename: Mitchell
authors.initials: M
authors.lastname: Cohen
authors.affiliation: Department of Computer Science, University of California, Santa Barbara, USA.
authors.forename: Linda
authors.initials: L
authors.lastname: Petzold
keywords: Coagulopathy; Hidden Markov model; Missing data; State identification; Trauma