scholarly journals The Mechanics of Traumatic Brain Injury: A Review of What We Know and What We Need to Know for Reducing Its Societal Burden

2014 ◽  
Vol 136 (2) ◽  
Author(s):  
David F. Meaney ◽  
Barclay Morrison ◽  
Cameron Dale Bass

Traumatic brain injury (TBI) is a significant public health problem, on pace to become the third leading cause of death worldwide by 2020. Moreover, emerging evidence linking repeated mild traumatic brain injury to long-term neurodegenerative disorders points out that TBI can be both an acute disorder and a chronic disease. We are at an important transition point in our understanding of TBI, as past work has generated significant advances in better protecting us against some forms of moderate and severe TBI. However, we still lack a clear understanding of how to study milder forms of injury, such as concussion, or new forms of TBI that can occur from primary blast loading. In this review, we highlight the major advances made in understanding the biomechanical basis of TBI. We point out opportunities to generate significant new advances in our understanding of TBI biomechanics, especially as it appears across the molecular, cellular, and whole organ scale.

2015 ◽  
Vol 9 (4) ◽  
pp. 356-368 ◽  
Author(s):  
Joana Ramalho ◽  
Mauricio Castillo

ABSTRACT Traumatic brain injury (TBI) represents a significant public health problem in modern societies. It is primarily a consequence of traffic-related accidents and falls. Other recently recognized causes include sports injuries and indirect forces such as shock waves from battlefield explosions. TBI is an important cause of death and lifelong disability and represents the most well-established environmental risk factor for dementia. With the growing recognition that even mild head injury can lead to neurocognitive deficits, imaging of brain injury has assumed greater importance. However, there is no single imaging modality capable of characterizing TBI. Current advances, particularly in MR imaging, enable visualization and quantification of structural and functional brain changes not hitherto possible. In this review, we summarize data linking TBI with dementia, emphasizing the imaging techniques currently available in clinical practice along with some advances in medical knowledge.


2014 ◽  
Vol 121 (5) ◽  
pp. 1219-1231 ◽  
Author(s):  
Samuel S. Shin ◽  
C. Edward Dixon ◽  
David O. Okonkwo ◽  
R. Mark Richardson

Traumatic brain injury (TBI) remains a significant public health problem and is a leading cause of death and disability in many countries. Durable treatments for neurological function deficits following TBI have been elusive, as there are currently no FDA-approved therapeutic modalities for mitigating the consequences of TBI. Neurostimulation strategies using various forms of electrical stimulation have recently been applied to treat functional deficits in animal models and clinical stroke trials. The results from these studies suggest that neurostimulation may augment improvements in both motor and cognitive deficits after brain injury. Several studies have taken this approach in animal models of TBI, showing both behavioral enhancement and biological evidence of recovery. There have been only a few studies using deep brain stimulation (DBS) in human TBI patients, and future studies are warranted to validate the feasibility of this technique in the clinical treatment of TBI. In this review, the authors summarize insights from studies employing neurostimulation techniques in the setting of brain injury. Moreover, they relate these findings to the future prospect of using DBS to ameliorate motor and cognitive deficits following TBI.


Neurosurgery ◽  
2017 ◽  
Vol 64 (CN_suppl_1) ◽  
pp. 264-265
Author(s):  
Molly E Hubbard ◽  
Abdullah Bin Zahid ◽  
Gabrielle Meyer ◽  
Kathleen Vonderhaar ◽  
David Y Balser ◽  
...  

Abstract INTRODUCTION Traumatic brain injury (TBI) is a leading cause of morbidity and mortality in the US. The effects of TBI on quality of life may not become apparent for years after the injury. There are conflicting reports in the literature regarding long term outcomes. Physicians are often asked to predict long term functional and cognitive outcomes, with limited data available. METHODS Patients with severe TBI (GCS = 9) who previously participated in a clinical trial during the 1980s were followed up with and compared to healthy controls without history of TBI. A health questionnaire, sports concussion assessment tool version 3 (SCAT3) and the Telephone Interview for Cognitive Status-modified (TICS-m) were completed over the phone and compared with controls using t-test. GCS at admission and 12-month GRS were used to predict to TICS-M at 30 years using linear regression. RESULTS >45 of the initial 168 subjects were confirmed alive, and 37 (13 females; mean age: 52.43 years S.D. 10.7) consented. Controls (n = 58; 23 females; mean age = 54 years, S.D. 11.5) had lower symptom severity score (6.7 S.D. 12.6 versus 20.6 S.D. 25.3; P = 0.005), lower total number of symptoms (3.4 S.D. 4.7 versus 7.12 S.D. 6.5; P = 0.006), higher standardized assessment of concussion score (25.6 S.D. 2.8 versus 21.2 S.D. 6.9; P = 0.001), and lower corrected MPAI-4 (22.3 S.D. 17.0 versus 43.7 S.D. 12.8; P < 0.001). GCS at admission did not predict cognitive status at 30-years assessed using TICS-M (P = 0.345). The Glasgow Outcome Scale score at 12-months was correlated to TICS-M at 30 years (R = 0.548, P < 0.001); each point decrease in GOS decreasing the score at TICS-M by 5.6 points. CONCLUSION Remote history of TBI disrupts the lives of survivors long after injury. Admission GCS does not predict cognitive status 30 years after TBI. The GOS at 12-months predicted the cognitive status assessed using TICS-M score at 30 years.


Neurosurgery ◽  
2019 ◽  
Vol 66 (Supplement_1) ◽  
Author(s):  
Kevin John ◽  
Aaron McPheters ◽  
Andrew Donovan ◽  
Nicolas K Khattar ◽  
Jacob R Shpilberg ◽  
...  

Abstract INTRODUCTION Acute subdural hematoma (aSDH) in the context of severe traumatic brain injury (TBI) is a neurosurgical emergency. Predictive models have been used in an attempt to modulate the morbidity and mortality of patient outcomes. We used machine learning (ML) to identify admission risk factors predictive of long-term morbidity in the severe TBI patient population with aSDH. METHODS Between 2013 and 2016, 85 patients with severe TBI and aSDH were included in the analysis. Random forest, ML architecture, was used to create a predictive model of long-term morbidity stratification. About 46 patients were included in the high morbidity group [Glasgow Outcome Scale (GOS) 1-2] and 39 patients were in the low morbidity group (GOS 3-5). We included 30 admission input variables including medical and surgical co-morbidities, neurological examination, laboratory values, and radiographic findings. RESULTS The predictive model showed a 78% precision. The highest scoring input variable was the pupillary examination in predicting high vs low morbidity (bilaterally unreactive vs symmetrically reactive; P < .0001). GCS on admission was higher in the low morbidity group (4 [3-7] vs 7 [3-7]; P < .0101). Rotterdam scores were higher in the high-morbidity group (3 [3-5] vs 4 [4-5]; P < .0032). GCS motor examination on admission was higher in the low-morbidity group (5 [1-5] vs. 2 [1-5]; P < .0106). The basal cisterns were found to be more patent in patients with the low-morbidity group (P = .0012). CONCLUSION ML is an efficient tool that can provide a reasonable level of accuracy in predicting long-term morbidity in patients with severe TBI and aSDH. Monitoring these admission criteria can help with risk-stratification of patients into higher and low risk tracks. Integration of ML into the treatment algorithm may allow the development of more refined guidelines to guide goal-directed therapy.


2020 ◽  
Author(s):  
Xiangyi Yin ◽  
Jie Wu ◽  
Lihui Zhou ◽  
Chunyan Ni ◽  
Minyan Xiao ◽  
...  

Abstract Background: Tracheostomy is very common in patients with severe traumatic brain injury (TBI), and long-term nursing care are needed for those patients. We aimed to evaluate the effects of hospital-community-home (HCH) nursing in those patients. Methods: Tracheostomy patients with severe TBI needing long-term care were included. All patients underwent two months long follow-up. Glasgow coma score (GCS), Karnofsky, Self-Anxiety Scale (SAS) (SAS) and Barthel assessment at the discharge and two months after discharge were evaluated. The tracheostomy related complications were recorded and compared.Results: A total of 60 patients were included. There weren’t significant differences between two groups in the GCS, Karnofsky, SAS and Barthel index at discharge((all p>0.05), the GCS, Karnofsky and Barthel index was all significantly increased after two months follow-up for two groups (all p<0.05), and the GCS, Karnofsky and Barthel index at two months follow-up in HCH group was significantly higher than that of control group(all p<0.05), but the SAS at two months follow-up in HCH group was significantly less than that of control group(p=0.009). The incidence of block of artificial tracheal cannula and readmission in HCH group were significant less than that of control group (all p<0.05).Conclusion: HCH nursing care is feasible in tracheostomy patients with severe TBI, future studies are needed to further evaluate the role of HCH nursing care.


2019 ◽  
Vol 85 (22) ◽  
Author(s):  
Xiang Y. Han

ABSTRACTLegionellosis, an infection caused by the environmental bacteriaLegionellaspp., has become a significant public health problem in the United States in recent years; however, among the states, the incidence rates vary widely without a clear explanation. This study examined environmental effects on the 2014-to-2016 average annual legionellosis incidence rates in the U.S. states through correlative analyses with long-term precipitation, temperature, solar UV radiation, and sunshine hours. The continental states west of ∼95°W showed low incidence rates of 0.51 to 1.20 cases per 100,000 population, which corresponded to low precipitation, below 750 mm annually. For the eastern states, where precipitation was higher, solar effects were prominent and mixed, leading to wide incidence variation. Robust regressions suggested a dividing line at 40°N: north of this line, rising temperature, mainly from solar heat, raised legionellosis incidence to a peak of 4.25/100,000 in Ohio; south of the line, intensifying sunlight in terms of high UV indices and long sunshine hours prevailed to limit incidence gradually to 0.99/100,000 in Louisiana. On or near the 40°N line were 15 eastern states that had leading legionellosis incidence rates of >2.0/100,000. These states all showed modest environmental parameters. In contrast, the frigid climate in Alaska and the strong year-round solar UV in Hawaii explained the lowest U.S. incidences, 0.14/100,000 and 0.47/100,000, respectively, in these states. The findings of solar and climate effects explain the wide variation of legionellosis incidence rates in the United States and may offer insights into the potential exposure to and prevention of infection.IMPORTANCELegionellosis, caused by the environmental bacteriaLegionellaspp., has become a significant public health problem in the United States in recent years, with ∼6,000 cases annually. The present study showed, through a series of correlative analyses with long-term precipitation, temperature, solar UV radiation, and sunshine hours, that these environmental conditions strongly influence the legionellosis incidence rates across the United States in mixed and dynamic fashions. The incidence rates varied remarkably by region, with the highest in Ohio and New York and the lowest in Alaska. A precipitation threshold above 750 mm was required for elevated legionellosis activity. Regression models and dividing lines between regions were established to show the promotive effect of temperature, as well as the inhibitive effects of solar UV and sunshine hours. These findings explain the wide variation of legionellosis incidence rates in the United States. They may also offer insights into potential exposure to and prevention of infection.


2017 ◽  
Vol 24 (1) ◽  
pp. 11-21 ◽  
Author(s):  
Christianne Laliberté Durish ◽  
Keith Owen Yeates ◽  
Terry Stancin ◽  
H. Gerry Taylor ◽  
Nicolay C. Walz ◽  
...  

AbstractObjectives:This study examined the relationship of the home environment to long-term executive functioning (EF) following early childhood traumatic brain injury (TBI).Methods:Participants (N=134) were drawn from a larger parent study of 3- to 6-year-old children hospitalized for severe TBI (n=16), complicated mild/moderate TBI (n=44), or orthopedic injury (OI;n=74), recruited prospectively at four tertiary care hospitals in the United States and followed for an average of 6.8 years post-injury. Quality of the home environment, caregiver psychological distress, and general family functioning were assessed shortly after injury (i.e., early home) and again at follow-up (i.e., late home). Participants completed several performance-based measures of EF at follow-up. Hierarchical regression analyses examined the early and late home environment measures as predictors of EF, both as main effects and as moderators of group differences.Results:The early and late home environment were inconsistent predictors of long-term EF across groups. Group differences in EF were significant for only the TEA-Ch Walk/Don’t Walk subtest, with poorer performance in the severe TBI group. However, several significant interactions suggested that the home environment moderated group differences in EF, particularly after complicated mild/moderate TBI.Conclusions:The home environment is not a consistent predictor of long-term EF in children with early TBI and OI, but may moderate the effects of TBI on EF. The findings suggest that interventions designed to improve the quality of stimulation in children’s home environments might reduce the long-term effects of early childhood TBI on EF. (JINS, 2018,24, 11–21)


2017 ◽  
Vol 07 (01) ◽  
pp. 033-038
Author(s):  
Panagiotis Poulos ◽  
Maria Kazantzi ◽  
Panagiotis Kalampalikis ◽  
Dimitrios Rallis

AbstractDecompressive craniectomy (DC) is considered a rescue therapy in patients with traumatic brain injury (TBI) with increased intracranial pressure (ICP). In this retrospective study, we examined the impact of craniectomy on ICP in children with severe TBI and their neurological outcome. A total of 14 patients were enrolled. Peak ICP was significantly lower (31 ± 2.9 to 19 ± 4.6, p < 0.001) and minimum cerebral perfusion pressure (CPP) higher (41 ± 10.5 to 58 ± 11.4, p < 0.001) postcraniectomy. The survival rate was 71%. However, 57% of our cohort had a poor neurological outcome at 6 months postinjury. In conclusion, although rescue DC was effective in controlling ICP and CPP, the long-term neurological outcome remained poor.


2019 ◽  
Vol 7 (3) ◽  
pp. 47 ◽  
Author(s):  
Michael Oberholzer ◽  
René M. Müri

Traumatic brain injury (TBI) and its potential long-term consequences are of major concern for public health. Neurorehabilitation of affected individuals has some specific characteristics in contrast to neurorehabilitation of patients with acquired brain lesions of other aetiology. This review will deal with the clinical consequences of the distinct lesions of TBI. In severe TBI, clinical course often follows a typical initial sequence of coma; followed by disturbed consciousness; later, post-traumatic agitation and amnesia; and finally, recovery of function occurs. In the different phases of neurorehabilitation, physicians should be aware of typical medical complications such as paroxysmal sympathetic hyperactivity, posttraumatic hydrocephalus, and posttraumatic neuroendocrine dysfunctions. Furthermore, we address questions on timing and on existing evidence for different rehabilitation programmes and for holistic neuropsychological rehabilitation approaches.


2017 ◽  
Vol 08 (S 01) ◽  
pp. S023-S026 ◽  
Author(s):  
Jose D. Charry ◽  
Jesus D. Falla ◽  
Juan D. Ochoa ◽  
Miguel A. Pinzón ◽  
Jorman H. Tejada ◽  
...  

ABSTRACT Introduction: Traumatic brain injury (TBI) is a public health problem. It is a pathology that causes significant mortality and disability in Colombia. Different calculators and prognostic models have been developed to predict the neurological outcomes of these patients. The Rotterdam computed tomography (CT) score was developed for prognostic purposes in TBI. We aimed to examine the accuracy of the prognostic discrimination and prediction of mortality of the Rotterdam CT score in a cohort of trauma patients with severe TBI in a university hospital in Colombia. Materials and Methods: We analyzed 127 patients with severe TBI treated in a regional trauma center in Colombia over a 2-year period. Bivariate and multivariate analyses were used. The discriminatory power of the score, its accuracy, and precision were assessed by logistic regression and as the area under the receiver operating characteristic curve. Shapiro–Wilk, Chi-square, and Wilcoxon tests were used to compare the real outcomes in the cohort against the predicted outcomes. Results: The median age of the patient cohort was 33 years, and 84.25% were male. The median injury severity score was 25, the median Glasgow Coma Scale motor score was 3, the basal cisterns were closed in 46.46% of the patients, and a midline shift of >5 mm was seen in 50.39%. The 6-month mortality was 29.13%, and the Rotterdam CT score predicted a mortality of 26% (P < 0.0001) (area under the curve: 0.825; 95% confidence interval: 0.745–0.903). Conclusions: The Rotterdam CT score predicted mortality at 6 months in patients with severe head trauma in a university hospital in Colombia. The Rotterdam CT score is useful for predicting early death and the prognosis of patients with TBI.


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