• Christopher R Pretz, James F Malec, and Flora M Hammond.
• Craig Hospital, Englewood, CO; Traumatic Brain Injury National Statistical and Data Center, Englewood, CO. Electronic address: cpretz@craighospital.org.
• Arch Phys Med Rehabil. 2013 Dec 1;94(12):2478-85.

ObjectiveTo develop a detailed understanding of temporal change (ie, estimated trajectories) at the individual level as measured by the Disability Rating Scale (DRS).DesignIndividual growth curve (IGC) analysis of retrospective data obtained from the National Institute on Disability and Rehabilitation Research Traumatic Brain Injury (TBI) Model Systems National Database.SettingMulticenter longitudinal database study.ParticipantsIndividuals with TBI (N=8816) participating in the TBI Model Systems National Database project.InterventionsNot applicable.Main Outcome Measure Drs ResultsThe negative exponential consisting of 3 growth parameters (pseudointercept, asymptote, rate) was successfully used to predict trajectory of recovery on the DRS qualified by the following covariates: race, sex, level of education and age at admission, rehabilitation length of stay, and cognitive and motor FIM scores at rehabilitation admission. Based on these results, an interactive tool was developed to allow prediction of the trajectory of recovery for individuals and subgroups with specified characteristics on the selected covariates.ConclusionsWith the use of IGC analysis, the longitudinal trajectory of recovery on the DRS for individuals sharing common characteristics and traits can be described. This methodology allows researchers and clinicians to predict numerous individual-level trajectories through use of a web-based computer automated interactive tool.Copyright © 2013 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

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