title: Group-Based Trajectory Modeling of Suppression Ratio After Cardiac Arrest.
abstract: Existing studies of quantitative electroencephalography (qEEG) as a prognostic tool after cardiac arrest (CA) use methods that ignore the longitudinal pattern of qEEG data, resulting in significant information loss and precluding analysis of clinically important temporal trends. We tested the utility of group-based trajectory modeling (GBTM) for qEEG classification, focusing on the specific example of suppression ratio (SR).
  
  
  
  We included comatose CA patients hospitalized from April 2010 to October 2014, excluding CA from trauma or neurological catastrophe. We used Persyst®v12 to generate SR trends and used semi-quantitative methods to choose appropriate sampling and averaging strategies. We used GBTM to partition SR data into different trajectories and regression associate trajectories with outcome. We derived a multivariate logistic model using clinical variables without qEEG to predict survival, then added trajectories and/or non-longitudinal SR estimates, and assessed changes in model performance.
  
  
  
  Overall, 289 CA patients had ≥36 h of EEG yielding 10,404 h of data (mean age 57 years, 81 % arrested out-of-hospital, 33 % shockable rhythms, 31 % overall survival, 17 % discharged to home or acute rehabilitation). We identified 4 distinct SR trajectories associated with survival (62, 26, 12, and 0 %, P < 0.0001 across groups) and CPC (35, 10, 4, and 0 %, P < 0.0001 across groups). Adding trajectories significantly improved model performance compared to adding non-longitudinal data.
  
  
  
  Longitudinal analysis of continuous qEEG data using GBTM provides more predictive information than analysis of qEEG at single time-points after CA.
authors.affiliation: Department of Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA, USA. elmerjp@upmc.edu.|Department of Emergency Medicine, University of Pittsburgh, Iroquois Building, Suite 400A, 3600 Forbes Avenue, Pittsburgh, PA, 15213, USA. elmerjp@upmc.edu.
authors.forename: Jonathan
authors.initials: J
authors.lastname: Elmer
authors.affiliation: Epidemiology Data Center, Department of Epidemiology, University of Pittsburgh, Pittsburgh, PA, USA.
authors.forename: John J
authors.initials: JJ
authors.lastname: Gianakas
authors.affiliation: Department of Emergency Medicine, University of Pittsburgh, Iroquois Building, Suite 400A, 3600 Forbes Avenue, Pittsburgh, PA, 15213, USA.
authors.forename: Jon C
authors.initials: JC
authors.lastname: Rittenberger
authors.affiliation: Department of Neurology, VA Pittsburgh Healthcare System, Pittsburgh, PA, USA.
authors.forename: Maria E
authors.initials: ME
authors.lastname: Baldwin
authors.affiliation: Department of Emergency Medicine, University of Pittsburgh, Iroquois Building, Suite 400A, 3600 Forbes Avenue, Pittsburgh, PA, 15213, USA.
authors.forename: John
authors.initials: J
authors.lastname: Faro
authors.affiliation: Division of Clinical Neurophysiology, University of Pittsburgh Medical Center, Pittsburgh, PA, USA.
authors.forename: Cheryl
authors.initials: C
authors.lastname: Plummer
authors.affiliation: Department of Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA, USA.|Department of Neurology, University of Pittsburgh, Pittsburgh, PA, USA.|Department of Neurosurgery, University of Pittsburgh, Pittsburgh, PA, USA.
authors.forename: Lori A
authors.initials: LA
authors.lastname: Shutter
authors.affiliation: Department of Pathology and Laboratory Medicine, College of Medicine, University of Vermont, Burlington, VT, USA.
authors.forename: Christina L
authors.initials: CL
authors.lastname: Wassel
authors.affiliation: Department of Emergency Medicine, University of Pittsburgh, Iroquois Building, Suite 400A, 3600 Forbes Avenue, Pittsburgh, PA, 15213, USA.
authors.forename: Clifton W
authors.initials: CW
authors.lastname: Callaway
authors.affiliation: Epidemiology Data Center, Department of Epidemiology, University of Pittsburgh, Pittsburgh, PA, USA.
authors.forename: Anthony
authors.initials: A
authors.lastname: Fabio
mesh_terms: D000328:Adult; D000368:Aged; D003128:Coma / Q000503:physiopathology*; D004569:Electroencephalography / Q000379:methods*; D005260:Female; D006323:Heart Arrest / Q000503:physiopathology*; D006801:Humans; D002534:Hypoxia, Brain / Q000503:physiopathology*; D008297:Male; D008875:Middle Aged; D008959:Models, Neurological; D011379:Prognosis
keywords: Anoxic brain injury; Cardiac arrest; Prognosis; Quantitative electroencephalography; Suppression ratio