Christopher R Pretz1, Kristen Dams-O'Connor2. 1. Craig Hospital, Englewood CO; Traumatic Brain Injury National Statistical and Data Center, Englewood CO. Electronic address: cpretz@craighospital.org. 2. Mount Sinai School of Medicine, New York, NY.
Abstract
OBJECTIVE: To comprehensively describe the temporal patterns of global outcome after traumatic brain injury (TBI) in the Traumatic Brain Injury Model Systems National Database (TBIMS NDB). DESIGN: Longitudinal prospective cohort study. SETTING: TBI Model Systems centers. PARTICIPANTS: Patients (N=3870) ≥16 years of age with moderate or severe TBI enrolled in the TBIMS NDB. INTERVENTIONS: None. MAIN OUTCOME MEASURE: Glasgow Outcome Scale-Extended (GOS-E). RESULTS: The trajectory of the GOS-E scores is best described with a model of quadratic change, in which scores initially increase and peak approximately 10 years after the first GOS-E assessment, and then decrease. Change occurs most rapidly in the initial and final years of the timeline. There was significant variability in each growth parameter (P<.05). A reduced multilevel model was built, including all covariates (age at first GOS-E assessment, FIM, race, sex, rehabilitation length of stay) that related significantly to the growth parameters. An interactive tool was created to generate individual level trajectories based on various combinations of covariate values. Results provide an individual level account of the chronological progression of TBI outcomes, as measured by the GOS-E. CONCLUSIONS: Individual growth curve analysis is a statistically rigorous approach to describe temporal change with respect to the GOS-E at the individual level for participants within the TBIMS NDB. Results indicated that, for individuals in the TBIMS NDB as a group, functional status as measured by the GOS-E initially improves, plateaus, and then begins to decline. Factors such as age at first GOS-E assessment, race, FIM score at rehabilitation admission, and rehabilitation length of stay were found to influence baseline GOS-E scores, as well as the rate and extent of both improvement and decline over time. Additional research may be required to determine the generalizability of these findings and the usefulness of this tool for clinical applications.
OBJECTIVE: To comprehensively describe the temporal patterns of global outcome after traumatic brain injury (TBI) in the Traumatic Brain Injury Model Systems National Database (TBIMSNDB). DESIGN: Longitudinal prospective cohort study. SETTING: TBI Model Systems centers. PARTICIPANTS: Patients (N=3870) ≥16 years of age with moderate or severe TBI enrolled in the TBIMSNDB. INTERVENTIONS: None. MAIN OUTCOME MEASURE: Glasgow Outcome Scale-Extended (GOS-E). RESULTS: The trajectory of the GOS-E scores is best described with a model of quadratic change, in which scores initially increase and peak approximately 10 years after the first GOS-E assessment, and then decrease. Change occurs most rapidly in the initial and final years of the timeline. There was significant variability in each growth parameter (P<.05). A reduced multilevel model was built, including all covariates (age at first GOS-E assessment, FIM, race, sex, rehabilitation length of stay) that related significantly to the growth parameters. An interactive tool was created to generate individual level trajectories based on various combinations of covariate values. Results provide an individual level account of the chronological progression of TBI outcomes, as measured by the GOS-E. CONCLUSIONS: Individual growth curve analysis is a statistically rigorous approach to describe temporal change with respect to the GOS-E at the individual level for participants within the TBIMSNDB. Results indicated that, for individuals in the TBIMSNDB as a group, functional status as measured by the GOS-E initially improves, plateaus, and then begins to decline. Factors such as age at first GOS-E assessment, race, FIM score at rehabilitation admission, and rehabilitation length of stay were found to influence baseline GOS-E scores, as well as the rate and extent of both improvement and decline over time. Additional research may be required to determine the generalizability of these findings and the usefulness of this tool for clinical applications.
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