Christopher R Pretz1, James F Malec, Flora M Hammond. 1. Craig Hospital, Englewood, CO; Traumatic Brain Injury National Statistical and Data Center, Englewood, CO. Electronic address: cpretz@craighospital.org.
Abstract
OBJECTIVE: To develop a detailed understanding of temporal change (ie, estimated trajectories) at the individual level as measured by the Disability Rating Scale (DRS). DESIGN: Individual 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. SETTING: Multicenter longitudinal database study. PARTICIPANTS: Individuals with TBI (N=8816) participating in the TBI Model Systems National Database project. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURE DRS RESULTS: The 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. CONCLUSIONS: With 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.
OBJECTIVE: To develop a detailed understanding of temporal change (ie, estimated trajectories) at the individual level as measured by the Disability Rating Scale (DRS). DESIGN: Individual 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. SETTING: Multicenter longitudinal database study. PARTICIPANTS: Individuals with TBI (N=8816) participating in the TBI Model Systems National Database project. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURE DRS RESULTS: The 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. CONCLUSIONS: With 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.
Authors: Raquel C Gardner; Jing Cheng; Adam R Ferguson; Ross Boylan; John Boscardin; Ross D Zafonte; Geoffrey T Manley Journal: J Neurotrauma Date: 2019-05-24 Impact factor: 5.269