Brown, Allen W.

This study sought to identify whether an anatomical indicator of injury severity as measured by multiparametric magnetic resonance imaging (MRI) including magnetic resonance elastography (MRE), is predictive of a clinical measure of injury severity after moderate-severe traumatic brain injury (TBI). Nine individuals who were admitted to acute inpatient rehabilitation after moderate-to-severe TBI completed a comprehensive MRI protocol prior to discharge from rehabilitation, which included conventional MRI with diffusion tensor imaging (DTI). Of those, five of nine also underwent brain MRE to measure the brain parenchyma stiffness. Clinical severity of injury was measured by the length of post-traumatic amnesia (PTA). MRI-assessed non-hemorrhage contusion score and hemorrhage score, DTI-measured white matter fractional anisotropy, and MRE-measured lesion stiffness were all assessed. A higher hemorrhagic score was significantly associated with a longer length of PTA ( p = 0.026). Participants with a longer PTA tended to have a higher non-hemorrhage contusion score and softer contusion lesions than the contralateral control side, although the small sample size did not allow for assessment of a significant association. To our knowledge, this is the first report applying MRI/MRE imaging protocol to quantitate altered brain anatomy after moderate-severe TBI and its association with PTA, a known clinical predictor of post-acute outcome. Future larger studies could lead to the development of prediction models that integrate clinical data with anatomical (MRI), structural (DTI), and mechanical (MRE) changes caused by TBI, to inform prognosis and care planning.

Background: Epidemiological studies examining associations between traumatic brain injury (TBI) and Alzheimer’s disease and related dementias (ADRD) have yielded conflicting results, which may be due to methodological differences. Objective: To examine the relationship between the presence and severity of TBI and risk of ADRD using a population-based cohort with medical record abstraction for confirmation of TBI and ADRD. Methods: All TBI events among Olmsted County, Minnesota residents aged > 40 years from 1985–1999 were confirmed by manual review and classified by severity. Each TBI case was randomly matched to two age-, sex-, and non-head injury population-based referents without TBI. For TBI events with non-head trauma, the Trauma Mortality Prediction Model was applied to assign an overall measure of non-head injury severity and corresponding referents were matched on this variable. Medical records were manually abstracted to confirm ADRD diagnosis. Cox proportional hazards models examined the relationship between TBI and severity with risk of ADRD. Results: A total of 1,418 residents had a confirmed TBI (865 Possible, 450 Probable, and 103 Definite) and were matched to 2,836 referents. When combining all TBI severities, the risk of any ADRD was significantly higher for those with a confirmed TBI compared to referents (HR = 1.32, 95% CI: 1.11, 1.58). Stratifying by TBI severity, Probable (HR = 1.42, 95% CI: 1.05, 1.92) and Possible (HR = 1.29, 95% CI: 1.02–1.62) TBI was associated with an increased risk of ADRD, but not Definite TBI (HR = 1.22, 95% CI: 0.68, 2.18). Conclusion: Our analyses support including TBI as a potential risk factor for developing ADRD.

Medical conditions co-occurring with traumatic brain injury (TBI) are associated with outcomes, and comorbidity indices such as Charlson and Elixhauser are used in TBI research, but they are not TBI specific. The purpose of this research was to develop an index or indices of medical conditions, identified in acute care after moderate to severe TBI, that are associated with outcomes at rehabilitation discharge. Using the TBI Model Systems National Database, the International Classification of Diseases, Ninth Revision (ICD-9) and Tenth Revision (ICD-10) codes of 8988 participants were converted to Healthcare Cost and Utilization Project (HCUP) diagnostic categories. Poisson regression models were built predicting Disability Rating Scale and Functional Independence Measure Cognitive and Motor subscale scores from HCUP categories after controlling for demographic and injury characteristics. Unweighted, weighted, and anchored indices based on the outcome models predicted 7.5–14.3% of the variance in the observed outcomes. When the indices were applied to a new validation sample of 1613 cases, however, only 2.6–6.6% of the observed outcomes were predicted. Therefore, no models or indices were recommended for future use, but several study findings are highlighted suggesting the importance and the potential for future research in this area.