Longitudinal Description of the Disability Rating Scale for Individuals in the National Institute on Disability and Rehabilitation Research Traumatic Brain Injury Model Systems National Database

被引:15
|
作者
Pretz, Christopher R. [1 ,2 ]
Malec, James F. [3 ,4 ]
Hammond, Flora M. [3 ,4 ]
机构
[1] Craig Hosp, Englewood, CO 80132 USA
[2] Traumat Brain Injury Natl Stat & Data Ctr, Englewood, CO 80132 USA
[3] Indiana Univ Sch Med, Dept Phys Med & Rehabil, Indianapolis, IN 46202 USA
[4] Rehabil Hosp Indiana, Indianapolis, IN USA
来源
关键词
Disability Rating Scale; Longitudinal studies; Rehabilitation; Rehabilitation outcome; Traumatic brain injuries; FUNCTIONAL INDEPENDENCE MEASURE; OUTCOME MEASURES; MULTICENTER; COMMUNITY; MODERATE; COHORT;
D O I
10.1016/j.apmr.2013.06.019
中图分类号
R49 [康复医学];
学科分类号
100215 ;
摘要
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. Archives of Physical Medicine and Rehabilitation 2013;94:2478-85 (C) 2013 by the American Congress of Rehabilitation Medicine
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页码:2478 / 2485
页数:8
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