Journal of neurotrauma最新文献

Impairment in visual function is common after traumatic brain injury (TBI) in the clinical setting, a phenomenon that translates to pre-clinical animal models as well. In Morris et al. (2021), we reported histological changes following weight-drop-induced TBI in a rodent model including retinal ganglion cell (RGC) loss, decreased electroretinogram (ERG) evoked potential, optic nerve diameter reduction, induced inflammation and gliosis, and loss of myelin accompanied by markedly impaired visual acuity. In this review, we will describe several pre-clinical TBI models that result in injuries to the visual system, indicating that visual function may be impaired following brain injury induced by a number of different injury modalities. This underscores the importance of understanding the role of the visual system and the potential detrimental sequelae to this sensory modality post-TBI. Given that most commonly employed behavioral tests such as the Elevated Plus Maze and Morris Water Maze rely on an intact visual system, interpretation of functional deficits in diffuse models may be confounded by off- target effects on the visual system.

Traumatic brain injury (TBI) causes significant neurophysiological deficits and is typically associated with rapid head accelerations common in sports-related incidents and automobile accidents. There are over 1.5 million TBIs in the United States each year, with children aged 0-4 being particularly vulnerable. TBI diagnosis is currently achieved through interpretation of clinical signs and symptoms and neuroimaging; however, there is increasing interest in minimally invasive fluid biomarkers to detect TBI objectively across all ages. Pre-clinical porcine models offer controlled conditions to evaluate TBI with known biomechanical conditions and without comorbidities. The objective of the current study was to establish pediatric porcine healthy reference ranges (RRs) of common human serum TBI biomarkers and to report their acute time-course after nonimpact rotational head injury. A retrospective analysis was completed to quantify biomarker concentrations in porcine serum samples collected from 4-week-old female (n = 215) and uncastrated male (n = 6) Yorkshire piglets. Subjects were assigned to one of three experimental groups (sham, sagittal-single, sagittal-multiple) or to a baseline only group. A rapid nonimpact rotational head injury model was used to produce mild-to-moderate TBI in piglets following a single rotation and moderate-to-severe TBI following multiple rotations. The Quanterix Simoa Human Neurology 4-Plex A assay was used to quantify glial fibrillary acidic protein (GFAP), neurofilament light (Nf-L), tau, and ubiquitin carboxyl-terminal hydrolase L1 (UCH-L1). The 95% healthy RRs for females were calculated and validated for GFAP (6.3-69.4 pg/mL), Nf-L (9.5-67.2 pg/mL), and UCH-L1 (3.8-533.7 pg/mL). Rising early, GFAP increased significantly above the healthy RRs for sagittal-single (to 164 and 243 pg/mL) and increased significantly higher in sagittal-multiple (to 494 and 413 pg/mL) groups at 30 min and 1 h postinjury, respectively, returning to healthy RRs by 1-week postinjury. Rising later, Nf-L increased significantly above the healthy RRs by 1 day in sagittal-single (to 69 pg/mL) and sagittal-multiple groups (to 140 pg/mL) and rising further at 1 week (single = 231 pg/mL, multiple = 481 pg/mL). Sagittal-single and sagittal-multiple UCH-L1 serum samples did not differ from shams or the healthy RRs. Sex differences were observed but inconsistent. Serum GFAP and Nf-L levels had distinct time-courses following head rotations in piglets, and both corresponded to load exposure. We conclude that serum GFAP and Nf-L offer promise for early TBI diagnosis and intervention decisions for TBI and other neurological trauma.

The potential influence of pituitary-related hormones (including both pituitary gland and target gland hormones) on functional recovery after traumatic brain injury has been observed. However, the relationship between these hormones and the recovery of consciousness in patients with disorders of consciousness (DOC) remains unclear. In this retrospective and observational study, 208 patients with DOC were recruited. According to the Glasgow Outcome Scale (GOS) scores after 6 months, patients with DOC were categorized into two subgroups: a favorable prognosis subgroup (n = 38) comprising those who regained consciousness (GOS score ≥3), and a poor prognosis subgroup (n = 156) comprising those who remained in DOC (GOS score <3). Comparative analyses of pituitary-related hormone levels between the two subgroups were conducted. Further, a binary logistic regression analysis was conducted to assess the predictive value of pituitary-related hormones for the patients' prognosis. The favorable prognosis subgroup showed a significant increase in adrenocorticotropic hormone (ACTH) levels (p = 0.036). Moreover, higher ACTH levels and shorter days since injury were significantly associated with a better prognosis, with odds ratios (ORs) of 0.928 (95% confidence interval [CI] = 0.873-0.985, p = 0.014) and 1.015 (95% CI = 1.005-1.026, p = 0.005), respectively. A subsequent receiver operating characteristic (ROC) analysis demonstrated the potential to predict patients' prognosis with an area under the curve value of 0.78, an overall accuracy of 75.5%, a sensitivity of 77.5%, and a specificity of 66.7%. Our findings indicate that ACTH levels could serve as a clinically valuable and convenient predictor for patients' prognosis.

In previous studies, the incidence of traumatic intracranial aneurysms (TICAs) after civilian gunshot wound to the head (cGSWH) was ∼3%. Given the use of delayed vessel imaging, we hypothesize that a significant fraction of TICAs is missed on initial non-contrasted scans. This study was designed to characterize acute TICAs using admission computed tomographic angiography (aCTA) in cGSWH. Over the period from 2017 to 2022, 341 patients were admitted to R. Adams Cowley Shock Trauma Center with cGSWH; 136 subjects had aCTA ∼3 (standard deviation [SD] 3.5) h post-injury. Demographics, clinical findings, imaging techniques, endovascular/surgical interventions, and outcomes were analyzed. Mean age was 34.7 (SD 13.1), male:female ratio was 120:16. Average admission Glasgow Coma Scale (GCS) score was 6 (SD 3.9). Entry site was frontal in 41, temporal in 55, parietal in 18, occipital in 6, suboccipital in 9, temporo-parietal in 1, and frontobasal-temporal in 6. Projectiles crossed multiple dural compartments in 76 (55%) patients. 35 TICAs were diagnosed in 28 subject: 24 were located along the middle cerebral artery (MCA), 6 in the anterior cerebral artery (ACA), 3 in the internal carotid artery (ICA), 1 in the posterior cerebral artery (PCA), and 1 in the middle meningeal artery (MMA). Eleven TICAs resolved spontaneously in nine patients. Eight aneurysms were treated by endovascular means, two via combined endovascular/open approaches. Forty-nine patients died, 10 of whom had 15 TICAs. Eighty patients developed intracerebral hematoma s (ICHs). Regression models showed that the presence of an ICH was the main predictor of TICA in cGSWH. Larger ICHs (average 22.3 cc vs. 9.4 cc in patients with and without aneurysms, respectively) in patients with cGSWH suggest hidden TICAs. Nearly 30% of patients had spontaneous resolution within 1 week. When CTA was performed acutely, TICAs were 10 times more frequent in cGSWH than in previous literature, and those patients were more likely to proceed to surgery. Almost one third of patients in this series died from the devastating effects of cGSWH.

Traumatic brain injuries (TBIs) are a large societal and individual burden. In the first year of life, the vast majority of these injuries are the result of inflicted abusive events by a trusted caregiver. Abusive head trauma (AHT) in infants, formerly known as shaken baby syndrome, is the leading cause of inflicted mortality and morbidity in this population. In this review we address clinical diagnosis, symptoms, prognosis, and neuropathology of AHT, emphasizing the burden of repetitive AHT. Next, we consider existing animal models of AHT, and we evaluate key features of an ideal model, highlighting important developmental milestones in children most vulnerable to AHT. We draw on insights from other injury models, such as repetitive, mild TBIs (RmTBIs), post-traumatic epilepsy (PTE), hypoxic-ischemic injuries, and maternal neglect, to speculate on key knowledge gaps and underline important new opportunities in pre-clinical AHT research. Finally, potential treatment options to facilitate healthy development in children following an AHT are considered. Together, this review aims to drive the field toward optimized, well-characterized animal models of AHT, which will allow for greater insight into the underlying neuropathological and neurobehavioral consequences of AHT.

Sleep-wake disturbances (SWDs) are one of the most common complaints following traumatic brain injury (TBI). The high prevalence and socioeconomic burden of SWDs post-TBI have only been recognized in the past decade. Common SWDs induced by TBI include excessive daytime sleepiness (EDS), hypersomnia, insomnia, obstructive sleep apnea (OSA), and circadian rhythm sleep disorders. Sleep disturbances can significantly compromise quality of life, strain interpersonal relationships, diminish work productivity, exacerbate other clinical conditions, and impede the rehabilitation process of TBI patients. Consequently, the prompt regulation and enhancement of sleep homeostasis in TBI patients is of paramount importance. Although studies have shown that abnormal neural network function, neuroendocrine changes, disturbance of sleep-wake regulators, and immune inflammatory responses related to brain structural damage induced by TBI are involved in the development of SWDs, the exact neuropathological mechanisms are still poorly understood. Therefore, we systematically review the current clinical and experimental studies on the characteristics and possible neural mechanisms of post-TBI SWDs. Elucidating the neural underpinnings of post-TBI SWDs holds the potential to diversify and enhance therapeutic approaches for these conditions. Such advancements could hasten the recuperation of TBI patients and ameliorate their overall quality of life. It is our aspiration that departments specializing in neurosurgery, rehabilitation, and neuropsychiatry will be able to recognize and address these conditions promptly, thereby facilitating the healing journey of affected individuals.

Traumatic brain injuries (TBIs) can lead to long-lasting cognitive impairments, and some survivors experience cognitive decline post-recovery. Early detection of decline is important for care planning, and understanding risk factors for decline can elucidate targets for prevention. While neuropsychological testing is the gold standard approach to characterizing cognitive function, there is a need for brief, scalable tools that are capable of detecting clinically significant changes in post-TBI cognition. This study examines whether a clinically significant change can be detected using the Brief Test of Adult Cognition by Telephone (BTACT) in a sample of individuals with chronic TBI and investigates whether potentially modifiable factors are associated with cognitive decline. Ninety participants aged 40 or older with complicated mild-to-severe TBI participated in two telephone-based study visits ∼1 year apart. Demographic, head trauma exposure, comorbid medical conditions, physical, and psychosocial functioning data were collected via self-report. The BTACT, a brief measure of global cognitive function, was used to assess cognitive performance across six domains. A reliable change index for quantifying clinically significant changes in BTACT performance was calculated. Results revealed cognitive decline in 10-27% of participants across various cognitive domains. More specifically, only depressive symptoms, including depressed affect and anhedonia, were significantly associated with cognitive decline after correcting for multiple comparisons using false discovery rate (FDR). Other factors such as the number of blows to the head, male gender, dyspnea, increased anxiety symptoms, seizures, illicit drug use, and fewer cardiovascular comorbidities should be considered hypothesis generating. Importantly, age was not a significant predictor of cognitive decline, which challenges the assumption that cognitive decline is solely related to the natural aging process. It suggests that there are unique factors associated with TBI that impact cognitive function, and these factors can affect individuals across the lifespan. The BTACT is a brief and sensitive tool for identifying clinically meaningful changes in cognitive function over a relatively brief period (i.e., 1 year) in a sample of individuals in the chronic stages of TBI (i.e., x̄ = 6.7 years post-TBI). Thus, the BTACT may be useful in surveillance efforts aimed at understanding and detecting decline, particularly in situations where in-person cognitive screening is impractical or unfeasible. We also identified potentially modifiable targets for the prevention of post-TBI cognitive decline. These findings can offer insights into treatment goals and preventive strategies for individuals at risk for cognitive decline, as well as help to facilitate early identification efforts.

Assessing quality of care is essential for improving the management of patients experiencing traumatic brain injury (TBI). This study aimed at devising a rigorous framework to evaluate the quality of TBI care provided by intensive care units (ICUs) and applying it to the Collaborative Research on Acute Traumatic Brain Injury in Intensive Care Medicine in Europe (CREACTIVE) consortium, which involved 83 ICUs from seven countries. The performance of the centers was assessed in terms of patients' outcomes, as measured by the 6-month Glasgow Outcome Scale-Extended (GOS-E). To account for the between-center differences in the characteristics of the admitted patients, we developed a multinomial logistic regression model estimating the probability of a four-level categorization of the GOS-E: good recovery (GR), moderate disability (MD), severe disability (SD), and death or vegetative state (D/VS). A total of 5928 patients admitted to the participating ICUs between March 2014 and March 2019 were analyzed. The model included 11 predictors and demonstrated good discrimination (area under the receiver operating characteristic [ROC] curve in the validation set for GR: 0.836, MD: 0.802, SD: 0.706, D/VS: 0.890) and calibration, both overall (Hosmer-Lemeshow test p value: 0.87) and in several subgroups, defined by prognostically relevant variables. The model was used as a benchmark for assessing quality of care by comparing the observed number of patients experiencing GR, MD, SD, and D/VS to the corresponding numbers expected in each category by the model, computing observed/expected (O/E) ratios. The four center-specific ratios were assembled with polar representations and used to provide a multidimensional assessment of the ICUs, overcoming the loss of information consequent to the traditional dichotomizations of the outcome in TBI research. The proposed framework can help in identifying strengths and weaknesses of current TBI care, triggering the changes that are necessary to improve patient outcomes.

Accurate early diagnosis of concussion is useful to prevent sequelae and improve neurocognitive outcomes. Early after head impact, concussion diagnosis may be doubtful in persons whose neurological, neuroradiological, and/or neurocognitive examinations are equivocal. Such individuals can benefit from novel accurate assessments that complement clinical diagnostics. We introduce a Bayesian machine learning classifier to identify concussion through cortico-cortical connectome mapping from magnetic resonance imaging in persons with quasi-normal cognition and without neuroradiological findings. Classifier features are generated from connectivity matrices specifying the mean fractional anisotropy of white matter connections linking brain structures. Each connection's saliency to classification was quantified by training individual classifier instantiations using a single feature type. The classifier was tested on a discovery sample of 92 healthy controls (HCs; 26 females, age μ ± σ: 39.8 ± 15.5 years) and 471 adult mTBI patients (158 females, age μ ± σ: 38.4 ± 5.9 years). Results were replicated in an independent validation sample of 256 HCs (149 females, age μ ± σ: 55.3 ± 12.1 years) and 126 patients with concussion (46 females, age μ ± σ: 39.0 ± 17.7 years). Classifier accuracy exceeds 99% in both samples, suggesting robust generalizability to new samples. Notably, 13 bilateral cortico-cortical connection pairs predict diagnostic status with accuracy exceeding 99% in both discovery and validation samples. Many such connection pairs are between prefrontal cortex structures, fronto-limbic and fronto-subcortical structures, and occipito-temporal structures in the ventral ("what") visual stream. This and related connectivity form a highly salient network of brain connections that is particularly vulnerable to concussion. Because these connections are important in mediating cognitive control, memory, and attention, our findings explain the high frequency of cognitive disturbances after concussion. Our classifier was trained and validated on concussed participants with cognitive profiles very similar to those of HCs. This suggests that the classifier can complement current diagnostics by providing independent information in clinical contexts where patients have quasi-normal cognition but where concussion diagnosis stands to benefit from additional evidence.