Browsing by Author "Pretz, Christopher R."

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    A Multidimensional Rasch Analysis of the Functional Independence Measure Based on the National Institute on Disability, Independent Living, and Rehabilitation Research Traumatic Brain Injury Model Systems National Database
    (Mary Ann Liebert, 2016-07-15) Pretz, Christopher R.; Kean, Jacob; Heinemann, Allen W.; Kozlowski, Allan J.; Bode, Rita K.; Gebhardt, Eveline; Physical Medicine and Rehabilitation, School of Medicine
    A number of studies have evaluated the psychometric properties of the Functional Independence Measure (FIM™) using Rasch analysis, although none has done so using the National Institute on Disability, Independent Living, and Rehabilitation Research Traumatic Brain Injury Model Systems National Database, a longitudinal database that captures demographic and outcome information on persons with moderate to severe traumatic brain injury across the United States. In the current study, we examine the psychometric properties of the FIM as represented by persons within this database and demonstrate that the FIM comprises three subscales representing cognitive, self-care, and mobility domains. These subscales were analyzed simultaneously using a multivariate Rasch model in combination with a time dependent concurrent calibration scheme with the goal of creating a raw score-to-logit transformation that can be used to improve the accuracy of parametric statistical analyses. The bowel and bladder function items were removed because of misfit with the motor and cognitive items. Some motor items exhibited step disorder, which was addressed by collapsing Categories 1-3 for Toileting, Stairs, Locomotion, Tub/Shower Transfers; Categories 1 and 2 for Toilet and Bed Transfers; and Categories 2 and 3 for Grooming. The strong correlations (r = 0.82-0.96) among the three subscales suggest they should be modeled together. Coefficient alpha of 0.98 indicates high internal consistency. Keyform maps are provided to enhance clinical interpretation and application of study results.
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    Predictive utility of an adapted Marshall head CT classification scheme after traumatic brain injury
    (Taylor & Francis, 2019-01-19) Brown, Allen W.; Pretz, Christopher R.; Bell, Kathleen R.; Hammond, Flora M.; Arciniegas, David B.; Bodien, Yelena G.; Dams-O’Connor, Kristen; Giacino, Joseph T.; Hart, Tessa; Johnson-Greene, Douglas; Kowalski, Robert G.; Walker, William C.; Weintraub, Alan; Zafonte, Ross; Physical Medicine and Rehabilitation, School of Medicine
    Objective: To study the predictive relationship among persons with traumatic brain injury (TBI) between an objective indicator of injury severity (the adapted Marshall computed tomography [CT] classification scheme) and clinical indicators of injury severity in the acute phase, functional outcomes at inpatient rehabilitation discharge, and functional and participation outcomes at 1 year after injury, including death.Participants: The sample involved 4895 individuals who received inpatient rehabilitation following acute hospitalization for TBI and were enrolled in the Traumatic Brain Injury Model Systems National Database between 1989 and 2014.Design: Head CT variables for each person were fit into adapted Marshall CT classification categories I through IV.Main Measures: Prediction models were developed to determine the amount of variability explained by the CT classification categories compared with commonly used predictors, including a clinical indicator of injury severity.Results: The adapted Marshall classification categories aided only in the prediction of craniotomy or craniectomy during acute hospitalization, otherwise making no meaningful contribution to variance in the multivariable models predicting outcomes at any time point after injury.Conclusion: Results suggest that head CT findings classified in this manner do not inform clinical discussions related to functional prognosis or rehabilitation planning after TBI.