The Traumatic Brain Injury Model Systems National Database: A Review of Published Research

Effectiveness of care models for chronic disease management: A scoping review of systematic reviews

OBJECTIVE

To conduct a scoping review of models of care for chronic disease management to identify potentially effective components for management of chronic traumatic brain injury (TBI).

METHODS

Information sources: Systematic searches of three databases (Ovid MEDLINE, Embase, and Cochrane Database of Systematic Reviews) from January 2010 to May 2021.

ELIGIBILITY CRITERIA

Systematic reviews and meta-analyses reporting on the effectiveness of the Chronic Care Model (CCM), collaborative/integrated care, and other chronic disease management models.

DATA

Target diseases, model components used (n = 11), and six outcomes (disease-specific, generic health-related quality of life and functioning, adherence, health knowledge, patient satisfaction, and cost/health care use).

SYNTHESIS

Narrative synthesis, including proportion of reviews documenting outcome benefits.

RESULTS

More than half (55%) of the 186 eligible reviews focused on collaborative/integrated care models, with 25% focusing on CCM and 20% focusing on other chronic disease management models. The most common health conditions were diabetes (n = 22), depression (n = 16), heart disease (n = 12), aging (n = 11), and kidney disease (n = 8). Other single medical conditions were the focus of 22 reviews, multiple medical conditions of 59 reviews, and other or mixed mental health/behavioral conditions of 20 reviews. Some type of quality rating for individual studies was conducted in 126 (68%) of the reviews. Of reviews that assessed particular outcomes, 80% reported disease-specific benefits, and 57% to 72% reported benefits for the other five types of outcomes. Outcomes did not differ by the model category, number or type of components, or target disease.

CONCLUSIONS

Although there is a paucity of evidence for TBI per se, care model components proven effective for other chronic diseases may be adaptable for chronic TBI care.

Predicting Functional Dependency in Patients with Disorders of Consciousness: A TBI-Model Systems and TRACK-TBI Study

OBJECTIVE

It is not currently possible to predict long-term functional dependency in patients with disorders of consciousness (DoC) after traumatic brain injury (TBI). Our objective was to fit and externally validate a prediction model for 1-year dependency in patients with DoC ≥ 2 weeks after TBI.

METHODS

We included adults with TBI enrolled in TBI Model Systems (TBI-MS) or Transforming Research and Clinical Knowledge in TBI (TRACK-TBI) studies who were not following commands at rehabilitation admission or 2 weeks post-injury, respectively. We fit a logistic regression model in TBI-MS and validated it in TRACK-TBI. The primary outcome was death or dependency at 1 year post-injury, defined using the Disability Rating Scale.

RESULTS

In the TBI-MS Discovery Sample, 1,960 participants (mean age 40 [18] years, 76% male, 68% white) met inclusion criteria, and 406 (27%) were dependent 1 year post-injury. In a TBI-MS held out cohort, the dependency prediction model's area under the receiver operating characteristic curve was 0.79 (95% CI 0.74-0.85), positive predictive value was 53% and negative predictive value was 86%. In the TRACK-TBI external validation (n = 124, age 40 [16] years, 77% male, 81% white), the area under the receiver operating characteristic curve was 0.66 (0.53, 0.79), equivalent to the standard IMPACTcore + CT score (p = 0.8).

INTERPRETATION

We developed a 1-year dependency prediction model using the largest existing cohort of patients with DoC after TBI. The sensitivity and negative predictive values were greater than specificity and positive predictive values. Accuracy was diminished in an external sample, but equivalent to the IMPACT model. Further research is needed to improve dependency prediction in patients with DoC after TBI. ANN NEUROL 2023;94:1008-1023.

Thalamic deep brain stimulation in traumatic brain injury: a phase 1, randomized feasibility study

Converging evidence indicates that impairments in executive function and information-processing speed limit quality of life and social reentry after moderate-to-severe traumatic brain injury (msTBI). These deficits reflect dysfunction of frontostriatal networks for which the central lateral (CL) nucleus of the thalamus is a critical node. The primary objective of this feasibility study was to test the safety and efficacy of deep brain stimulation within the CL and the associated medial dorsal tegmental (CL/DTTm) tract.Six participants with msTBI, who were between 3 and 18 years post-injury, underwent surgery with electrode placement guided by imaging and subject-specific biophysical modeling to predict activation of the CL/DTTm tract. The primary efficacy measure was improvement in executive control indexed by processing speed on part B of the trail-making test.All six participants were safely implanted. Five participants completed the study and one was withdrawn for protocol non-compliance. Processing speed on part B of the trail-making test improved 15% to 52% from baseline, exceeding the 10% benchmark for improvement in all five cases.CL/DTTm deep brain stimulation can be safely applied and may improve executive control in patients with msTBI who are in the chronic phase of recovery.ClinicalTrials.gov identifier: NCT02881151 .

World Health Organization Disability Assessment Schedule versus Functional Independence Measure in Traumatic Brain Injury

OBJECTIVE

In patients with traumatic brain injury, to compare functioning measured using the 12-item patient and proxy World Health Organization Disability Assessment Schedule (WHODAS-12) with assessments made by professionals.

PATIENTS AND METHODS

At discharge from rehabilitation, 89 consecutive patients with traumatic brain injury (10 mild, 36 moderate, 43 severe) and their proxies completed the WHODAS-12. Professionals assessed functioning simultaneously using the WHO minimal generic set of domains of functioning and health and Functional Independence Measure (FIM).

RESULTS

From mild to severe traumatic brain injury, increasing disability was found in: sum, component and item scores of patient and proxy WHODAS, except for emotional functions in patients' ratings; in sum and item scores of the WHO minimal generic data-set, except for pain; and in FIM total score and sub-scores. The WHODAS participation component was more impaired than activities. Although proxies rated functioning more impaired than patients, the correlation between patient and proxy WHODAS was strong (0.74). The correlation between patient/proxy WHODAS and FIM was also strong (-0.56 and -0.78, respectively). Proxy WHODAS differentiated mild and moderate traumatic brain injury more accurately than the other assessments.

CONCLUSION

We recommend using the WHODAS-12 when planning patient- and family-oriented rehabilitation services after traumatic brain injury.

Prevalence of comorbidities post mild traumatic brain injuries: a traumatic brain injury model systems study

Traumatic brain injury (TBI) is associated with an increased risk of long-lasting health-related complications. Survivors of brain trauma often experience comorbidities which could further dampen functional recovery and severely interfere with their day-to-day functioning after injury. Of the three TBI severity types, mild TBI constitutes a significant proportion of total TBI cases, yet a comprehensive study on medical and psychiatric complications experienced by mild TBI subjects at a particular time point is missing in the field. In this study, we aim to quantify the prevalence of psychiatric and medical comorbidities post mild TBI and understand how these comorbidities are influenced by demographic factors (age, and sex) through secondary analysis of patient data from the TBI Model Systems (TBIMS) national database. Utilizing self-reported information from National Health and Nutrition Examination Survey (NHANES), we have performed this analysis on subjects who received inpatient rehabilitation at 5 years post mild TBI. Our analysis revealed that psychiatric comorbidities (anxiety, depression, and post-traumatic stress disorder (PTSD)), chronic pain, and cardiovascular comorbidities were common among survivors with mild TBI. Furthermore, depression exhibits an increased prevalence in the younger compared to an older cohort of subjects whereas the prevalence of rheumatologic, ophthalmological, and cardiovascular comorbidities was higher in the older cohort. Lastly, female survivors of mild TBI demonstrated increased odds of developing PTSD compared to male subjects. The findings of this study would motivate additional analysis and research in the field and could have broader implications for the management of comorbidities after mild TBI.

Predicting Functional Dependency in Patients with Disorders of Consciousness: A TBI-Model Systems and TRACK-TBI Study

Importance

There are currently no models that predict long-term functional dependency in patients with disorders of consciousness (DoC) after traumatic brain injury (TBI).

Objective

Fit, test, and externally validate a prediction model for 1-year dependency in patients with DoC 2 or more weeks after TBI.

Design

Secondary analysis of patients enrolled in TBI Model Systems (TBI-MS, 1988-2020, Discovery Sample) or Transforming Research and Clinical Knowledge in TBI (TRACK-TBI, 2013-2018, Validation Sample) and followed 1-year post-injury.

Setting

Multi-center study at USA rehabilitation hospitals (TBI-MS) and acute care hospitals (TRACK-TBI).

Participants

Adults with TBI who were not following commands at rehabilitation admission (TBI-MS; days post-injury vary) or 2-weeks post-injury (TRACK-TBI).

Exposures

In the TBI-MS database (model fitting and testing), we screened demographic, radiological, clinical variables, and Disability Rating Scale (DRS) item scores for association with the primary outcome.

Main Outcome

The primary outcome was death or complete functional dependency at 1-year post-injury, defined using a DRS-based binary measure (DRS Depend ), indicating need for assistance with all activities and concomitant cognitive impairment.

Results

In the TBI-MS Discovery Sample, 1,960 subjects (mean age 40 [18] years, 76% male, 68% white) met inclusion criteria and 406 (27%) were dependent at 1-year post-injury. A dependency prediction model had an area under the receiver operating characteristic curve (AUROC) of 0.79 [0.74, 0.85], positive predictive value of 53%, and negative predictive value of 86% for dependency in a held-out TBI-MS Testing cohort. Within the TRACK-TBI external validation sample (N=124, age 40 [16], 77% male, 81% white), a model modified to remove variables not collected in TRACK-TBI, had an AUROC of 0.66 [0.53, 0.79], equivalent to the gold-standard IMPACT core+CT score (0.68; 95% AUROC difference CI: -0.2 to 0.2, p=0.8).

Conclusions and Relevance

We used the largest existing cohort of patients with DoC after TBI to develop, test and externally validate a prediction model of 1-year dependency. The model’s sensitivity and negative predictive value were greater than specificity and positive predictive value. Accuracy was diminished in an external sample, but equivalent to the best-available models. Further research is needed to improve dependency prediction in patients with DoC after TBI.

Comparison of Common Outcome Measures for Assessing Independence in Patients Diagnosed with Disorders of Consciousness: A Traumatic Brain Injury Model Systems Study

Patients with disorders of consciousness (DoC) after traumatic brain injury (TBI) recover to varying degrees of functional dependency. Dependency is difficult to measure but critical for interpreting clinical trial outcomes and prognostic counseling. In participants with DoC (i.e., not following commands) enrolled in the TBI Model Systems National Database (TBIMS NDB), we used the Functional Independence Measure (FIM^®) as the reference to evaluate how accurately the Glasgow Outcome Scale-Extended (GOSE) and Disability Rating Scale (DRS) assess dependency. Using the established FIM-dependency cut-point of <80, we measured the classification performance of literature-derived GOSE and DRS cut-points at 1-year post-injury. We compared the area under the receiver operating characteristic curve (AUROC) between the DRS_Depend, a DRS-derived marker of dependency, and the data-derived optimal GOSE and DRS cut-points. Of 18,486 TBIMS participants, 1483 met inclusion criteria (mean [standard deviation (SD)] age = 38 [18] years; 76% male). The sensitivity of GOSE cut-points of ≤3 and ≤4 (Lower Severe and Upper Severe Disability, respectively) for identifying FIM-dependency were 97% and 98%, but specificities were 73% and 51%, respectively. The sensitivity of the DRS cut-point of ≥12 (Severe Disability) for identifying FIM-dependency was 60%, but specificity was 100%. The DRS_Depend had a sensitivity of 83% and a specificity of 94% for classifying FIM-dependency, with a greater AUROC than the data-derived optimal GOSE (≤3, p = 0.01) and DRS (≥10, p = 0.008) cut-points. Commonly used GOSE and DRS cut-points have limited specificity or sensitivity for identifying functional dependency. The DRS_Depend identifies FIM-dependency more accurately than the GOSE and DRS cut-points, but requires further validation.

Application of Second-Order Growth Mixture Modeling (SO-GMM) to Longitudinal TBI Outcome Research: 15-year Trajectories of Life Satisfaction in Adolescents and Young Adults (AYA) as an Example

OBJECTIVE

To demonstrate the application of Second-Order Growth Mixture Modeling using life satisfaction among adolescents and young adults with TBI up to 15 years post-injury.

DESIGN

SO-GMM, a data-driven modeling approach that accounts for measurement errors, was adopted to uncover distinct growth trajectories of life satisfaction over 15 years post-injury. Membership in growth trajectories was then linked with baseline characteristics to understand the contributing factors to distinct growth over time.

SETTING

Traumatic Brain Injury Model System National Database PARTICIPANTS: 3,756 AYAs with TBI aged 16 - 25 (M_age=20.49, SD_age=2.66; 27.24% female) INTERVENTIONS: Not Applicable MAIN OUTCOME MEASURES: Satisfaction with Life Scale RESULTS: Four quadratic growth trajectories were identified: low-stable (16.6%) that had low initial life satisfaction and remained low over time; high-stable (49.3%) that had high life satisfaction at the baseline and stayed high over time; high-decreasing (15.8%) that started with high life satisfaction but decreased over time; and low-increasing (18.2%) that started with low life satisfaction but increased over time. Sex, race, pre-injury employment status, age, and FIM cognition were associated with group assignment.

CONCLUSION

This study applied SO-GMM to a national TBI database and identified four longitudinal trajectories of life satisfaction among AYAs with TBI. Findings provided data-driven evidence for development of future interventions that are tailored at both temporal and personalized levels for improved health outcomes among AYAs with TBI.

The impact of cigarette smoking and nicotine on traumatic brain injury: a review

INTRODUCTION

Traumatic Brain Injury (TBI) and tobacco smoking are both serious public health problems. Many people with TBI also smoke. Nicotine, a component of tobacco smoke, has been identified as a premorbid neuroprotectant in other neurological disorders. This study aims to provide better understanding of relationships between tobacco smoking and nicotine use and effect on outcome/recovery from TBI.

METHODS

PubMed database, SCOPUS, and PTSDpub were searched for relevant English-language papers.

RESULTS

Twenty-nine human clinical studies and nine animal studies were included. No nicotine-replacement product use in human TBI clinical studies were identified. While smoking tobacco prior to injury can be harmful primarily due to systemic effects that can compromise brain function, animal studies suggest that nicotine as a pharmacological agent may augment recovery of cognitive deficits caused by TBI.

CONCLUSIONS

While tobacco smoking before or after TBI has been associated with potential harms, many clinical studies downplay correlations for most expected domains. On the other hand, nicotine could provide potential treatment for cognitive deficits following TBI by reversing impaired signaling pathways in the brain including those involving nAChRs, TH, and dopamine. Future studies regarding the impact of cigarette smoking and vaping on patients with TBI are needed .