title: Developing Artificial Neural Network Models to Predict Functioning One Year After Traumatic Spinal Cord Injury.
abstract: OBJECTIVE
  To develop mathematical models for predicting level of independence with specific functional outcomes 1 year after discharge from inpatient rehabilitation for spinal cord injury.
  
  
  METHODS
  Statistical analyses using artificial neural networks and logistic regression.
  
  
  METHODS
  Retrospective analysis of data from the national, multicenter Spinal Cord Injury Model Systems (SCIMS) Database.
  
  
  METHODS
  Subjects (N=3142; mean age, 41.5y) with traumatic spinal cord injury who contributed data for the National SCIMS Database longitudinal outcomes studies.
  
  
  METHODS
  Not applicable.
  
  
  METHODS
  Self-reported ambulation ability and FIM-derived indices of level of assistance required for self-care activities (ie, bed-chair transfers, bladder and bowel management, eating, toileting).
  
  
  RESULTS
  Models for predicting ambulation status were highly accurate (>85% case classification accuracy; areas under the receiver operating characteristic curve between .86 and .90). Models for predicting nonambulation outcomes were moderately accurate (76%-86% case classification accuracy; areas under the receiver operating characteristic curve between .70 and .82). The performance of models generated by artificial neural networks closely paralleled the performance of models analyzed using logistic regression constrained by the same independent variables.
  
  
  CONCLUSIONS
  After further prospective validation, such predictive models may allow clinicians to use data available at the time of admission to inpatient spinal cord injury rehabilitation to accurately predict longer-term ambulation status, and whether individual patients are likely to perform various self-care activities with or without assistance from another person.
authors.affiliation: Psychology Department, Hospital for Special Care, New Britain, CT. Electronic address: tbelliveau@hfsc.org.
authors.forename: Timothy
authors.initials: T
authors.lastname: Belliveau
authors.affiliation: Department of Health Policy and Management, Boston University School of Public Health, Boston, MA.
authors.forename: Alan M
authors.initials: AM
authors.lastname: Jette
authors.affiliation: Physical Medicine and Rehabilitation Department, Hartford Hospital, Hartford, CT.
authors.forename: Subramani
authors.initials: S
authors.lastname: Seetharama
authors.affiliation: Information Technology Department, Hospital for Special Care, New Britain, CT.
authors.forename: Jeffrey
authors.initials: J
authors.lastname: Axt
authors.affiliation: Physical Medicine and Rehabilitation Department, Gaylord Hospital, Wallingford, CT.
authors.forename: David
authors.initials: D
authors.lastname: Rosenblum
authors.affiliation: Department of Mathematical Sciences, Central Connecticut State University, New Britain, CT.
authors.forename: Daniel
authors.initials: D
authors.lastname: Larose
authors.affiliation: Department of Health Policy and Management, Boston University School of Public Health, Boston, MA.
authors.forename: Bethlyn
authors.initials: B
authors.lastname: Houlihan
authors.affiliation: Department of Health Policy and Management, Boston University School of Public Health, Boston, MA.
authors.forename: Mary
authors.initials: M
authors.lastname: Slavin
authors.affiliation: School of Business, State University of New York at New Paltz, New Paltz, NY.
authors.forename: Chantal
authors.initials: C
authors.lastname: Larose
mesh_terms: D000203:Activities of Daily Living; D005260:Female; D006801:Humans; D016015:Logistic Models; D008297:Male; D008962:Models, Theoretical; D016571:Neural Networks, Computer; D026741:Physical Therapy Modalities; D020127:Recovery of Function; D015203:Reproducibility of Results; D012189:Retrospective Studies; D012648:Self Care; D013119:Spinal Cord Injuries / Q000534:rehabilitation*; D016138:Walking / Q000502:physiology
keywords: Activities of daily living; Decision support techniques; Medical informatics; Rehabilitation; Spinal cord injuries