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Traumatic brain injury leads to cellular damage which in turn results in the rapid release of damage-associated molecular patterns (DAMPs) that prompt resident cells to release cytokines and chemokines. These in turn rapidly recruit neutrophils, which assist in limiting the spread of injury and removing cellular debris. Microglia continuously survey the CNS (central nervous system) compartment and identify structural abnormalities in neurons contributing to the response. After some days, when neutrophil numbers start to decline, activated microglia and astrocytes assemble at the injury site—segregating injured tissue from healthy tissue and facilitating restorative processes. Monocytes infiltrate the injury site to produce chemokines that recruit astrocytes which successively extend their processes towards monocytes during the recovery phase. In this fashion, monocytes infiltration serves to help repair the injured brain. Neurons and astrocytes also moderate brain inflammation via downregulation of cytotoxic inflammation. Depending on the severity of the brain injury, T and B cells can also be recruited to the brain pathology sites at later time points.

To purpose was to assess and compare the health-related quality of life (HRQoL) and risk of depression two years after trauma, between patients with and without traumatic brain injury (TBI) in a mixed Swedish trauma cohort. In this prospective cohort study, TBI and non-TBI trauma patients included in the Swedish Trauma registry 2019 at a level II trauma center in Stockholm, Sweden, were contacted two years after admission. HRQoL was assessed with RAND-36 and EQ-5D-3L, and depression with Montgomery Åsberg depression Rating Scale self-report (MADRS-S). Abbreviated Injury Score (AIS) head was used to grade TBI severity, and American Society of Anesthesiologists (ASA) score was used to assess comorbidities. Data were compared using Chi-squared test, Mann Whitney U test and ordered logistic regression, and Bonferroni correction was applied. A total of 170 of 737 eligible patients were included. TBI was associated with higher scores in 5/8 domains of RAND-36 and 3/5 domains of EQ-5D (p < 0.05). No significant difference in MADRS-S. An AIS (head) of three or higher was associated with lower scores in five domains of RAND-36 and two domains of EQ-5D but not for MADRS-S. An ASA-score of three was associated with lower scores in all domains of both RAND-36 (p < 0.05, except mental health) and EQ-5D (p < 0.001, except anxiety/depression), but not for MADRS-S. In conclusion, patients without TBI reported a lower HRQoL than TBI patients two years after trauma. TBI severity assessed according to AIS (head) was associated with HRQoL, and ASA-score was found to be a predictor of HRQoL, emphasizing the importance of considering pre-injury health status when assessing outcomes in TBI patients.

Matrix metalloproteinases (MMPs) are extracellular enzymes involved in the degradation of extracellular matrix (ECM) proteins. Increased expression of MMPs have been described in traumatic brain injury (TBI) and may contribute to additional tissue injury and blood–brain barrier damage. The objectives of this study were to determine longitudinal changes in cerebrospinal fluid (CSF) concentrations of MMPs after acute TBI and in relation to clinical outcomes, with patients with idiopathic normal pressure hydrocephalus (iNPH) serving as a contrast group. The study included 33 TBI patients with ventricular CSF serially sampled, and 38 iNPH patients in the contrast group. Magnetic bead-based immunoassays were utilized to measure the concentrations of eight MMPs in ventricular human CSF. CSF concentrations of MMP-1, MMP-3 and MMP-10 were increased in TBI patients (at baseline) compared with the iNPH group (p < 0.001), while MMP-2, MMP-9 and MMP-12 did not differ between the groups. MMP-1, MMP-3 and MMP-10 concentrations decreased with time after trauma (p = 0.001–0.04). Increased concentrations of MMP-2 and MMP-10 in CSF at baseline were associated with an unfavourable TBI outcome (p = 0.002–0.02). Observed variable pattern of changes in MMP concentrations indicates that specific MMPs serve different roles in the pathophysiology following TBI, and are in turn associated with clinical outcomes.

Therapeutic management during the acute phase of traumatic brain injury (TBI) relies on continuous multimodal cerebral physiologic monitoring to detect and prevent secondary injury. These high-resolution data streams come from various invasive/non-invasive sensor technologies and challenge clinicians, as they are difficult to integrate into management algorithms and prognostic models. Data reduction techniques, like moving average filters, simplify data but may fail to address statistical autocorrelation and could introduce new properties, affecting model utility and interpretation. This study uses the CAnadian High-Resolution TBI (CAHR-TBI) dataset to examine the impact of temporal resolution changes (1 min to 24 h) on autoregressive integrated moving average (ARIMA) modeling for raw and derived cerebral physiologic signals. Stationarity tests indicated that the majority of the signals required first-order differencing to address persistent trends. A grid search identified optimal ARIMA parameters (p,d,q) for each signal and resolution. Subgroup analyses revealed population-specific differences in temporal structure, and small-scale forecasting using optimal parameters confirmed model adequacy. Variations in optimal structures across signals and patients highlight the importance of tailoring ARIMA models for precise interpretation and performance. Findings show that both raw and derived indices exhibit intrinsic ARIMA components regardless of resolution. Ignoring these features risks compromising the significance of models developed from such data. This underscores the need for careful resolution considerations in temporal modeling for TBI care.

Purpose This study aimed to investigate whether incorporating pre-injury health status, measured by the American Society of Anesthesiologists (ASA) score, improves outcome prediction models for moderate-to-severe traumatic brain injury (msTBI) patients. Methods We conducted a retrospective single-center study of msTBI patients (2005–2021). The primary outcome was 1-year Glasgow Outcome Scale (GOS, dichotomized as GOS1-3 (unfavorable) vs. 4–5 (favorable)), and secondary outcome was 90-day mortality. Logistic regression evaluated the contribution of ASA score to the International Mission for Prognosis and Clinical Trials in Traumatic Brain Injury (IMPACT) core + CT outcome prediction model incorporating age, admission GCS, pupillary reactivity, Marshall CT classification, hypoxia, hypotension, epidural hematoma, and subarachnoid hemorrhage. Results Among the 720 adult patients that were included 51% had an unfavorable GOS at 1 year. The 90-day mortality was 19%. ASA score and TRISS were independently associated with both outcomes ( p  < 0.001). Incorporating the ASA score to our IMPACT model significantly enhanced its explanatory value of dichotomized GOS (35% vs. 32% variance explained, p  < 0.001) and improved the model’s prognostic accuracy. Conclusion In this retrospective single-center cohort study, we found that ASA score improves existing prognostic models for msTBI. Incorporating this simple comorbidity measure could enhance outcome prediction and support more personalized acute management. Future prospective studies are needed to validate these results.

Intensive care for patients with traumatic brain injury (TBI) aims to optimize intracranial pressure (ICP) and cerebral perfusion pressure (CPP). The transformation of ICP and CPP time-series data into a dynamic prediction model could aid clinicians to make more data-driven treatment decisions. We retrained and externally validated a machine learning model to dynamically predict the risk of mortality in patients with TBI. Retraining was done in 686 patients with 62,000 h of data and validation was done in two international cohorts including 638 patients with 60,000 h of data. The area under the receiver operating characteristic curve increased with time to 0.79 and 0.73 and the precision recall curve increased with time to 0.57 and 0.64 in the Swedish and American validation cohorts, respectively. The rate of false positives decreased to ≤2.5%. The algorithm provides dynamic mortality predictions during intensive care that improved with increasing data and may have a role as a clinical decision support tool.

Background Astrocytes respond to injury and disease through a process known as reactive astrogliosis, of which inflammatory signaling is one subset. This inflammatory response is heterogeneous with respect to the inductive stimuli and the afflicted central nervous system region. This is of plausible importance in e.g. traumatic axonal injury (TAI), where lesions in the brainstem carries a particularly poor prognosis. In fact, astrogliotic forebrain astrocytes were recently suggested to cause neuronal death following axotomy. We therefore sought to assess if ventral brainstem- or rostroventral spinal astrocytes exert similar effects on motor neurons in vitro. Methods We derived brainstem/rostroventral spinal astrocyte-like cells (ES-astrocytes) and motor neurons using directed differentiation of mouse embryonic stem cells (ES). We activated the ES-astrocytes using the neurotoxicity-eliciting cytokines interleukin- (IL-) 1α and tumor necrosis factor-(TNF-)α and clinically relevant inflammatory mediators. In co-cultures with reactive ES-astrocytes and motor neurons, we assessed neurotoxic ES-astrocyte activity, similarly to what has previously been shown for other central nervous system (CNS) regions. Results We confirmed the brainstem/rostroventral ES-astrocyte identity using RNA-sequencing, immunocytochemistry, and by comparison with primary subventricular zone-astrocytes. Following cytokine stimulation, the c-Jun N-terminal kinase pathway down-stream product phosphorylated c-Jun was increased, thus demonstrating ES-astrocyte reactivity. These reactive ES-astrocytes conferred a contact-dependent neurotoxic effect upon co-culture with motor neurons. When exposed to IL-1β and IL-6, two neuroinflammatory cytokines found in the cerebrospinal fluid and serum proteome following human severe traumatic brain injury (TBI), ES-astrocytes exerted similar effects on motor neurons. Activation of ES-astrocytes by these cytokines was associated with pathways relating to endoplasmic reticulum stress and altered regulation of MYC. Conclusions Ventral brainstem and rostroventral spinal cord astrocytes differentiated from mouse ES can exert neurotoxic effects in vitro. This highlights how neuroinflammation following CNS lesions can exert region- and cell-specific effects. Our in vitro model system, which uniquely portrays astrocytes and neurons from one niche, allows for a detailed and translationally relevant model system for future studies on how to improve neuronal survival in particularly vulnerable CNS regions following e.g. TAI.

BackgroundBrain tissue oxygen tension (PbtO2) and cerebrovascular pressure reactivity monitoring have emerged as potential modalities to individualize care in moderate and severe traumatic brain injury (TBI). The relationship between these modalities has had limited exploration. The aim of this study was to examine the relationship between PbtO2 and cerebral perfusion pressure (CPP) and how this relationship is modified by the state of cerebrovascular pressure reactivity.MethodsA retrospective multi-institution cohort study utilizing prospectively collected high-resolution physiologic data from the CAnadian High Resolution-TBI (CAHR-TBI) Research Collaborative database collected between 2011 and 2021 was performed. Included in the study were critically ill TBI patients with intracranial pressure (ICP), arterial blood pressure (ABP), and PbtO2 monitoring treated in any one of three CAHR-TBI affiliated adult intensive care units (ICU). The outcome of interest was how PbtO2 and CPP are related over a cohort of TBI patients and how this relationship is modified by the state of cerebrovascular reactivity, as determined using the pressure reactivity index (PRx).ResultsA total of 77 patients met the study inclusion criteria with a total of 377,744 min of physiologic data available for the analysis. PbtO2 produced a triphasic curve when plotted against CPP like previous population-based plots of cerebral blood flow (CBF) versus CPP. The triphasic curve included a plateau region flanked by regions of relative ischemia (hypoxia) and hyperemia (hyperoxia). The plateau region shortened when cerebrovascular pressure reactivity was disrupted compared to when it was intact.ConclusionsIn this exploratory analysis of a multi-institution high-resolution physiology TBI database, PbtO2 seems to have a triphasic relationship with CPP, over the entire cohort. The CPP range over which the plateau exists is modified by the state of cerebrovascular reactivity. This indicates that in critically ill TBI patients admitted to ICU, PbtO2 may be reflective of CBF.

Background: The cerebral compliance (or compensatory reserve) index, RAP, is a critical yet underutilized physiological marker in the management of moderate-to-severe traumatic brain injury (TBI). While RAP offers promise as a continuous bedside metric, its broader cerebral physiological context remains partly understood. This study aims to characterize the burden of impaired RAP in relation to other key components of cerebral physiology. Methods: Archived data from 379 moderate-to-severe TBI patients were analyzed using descriptive and threshold-based methods across three RAP states (impaired, intact/transitional, and exhausted). Agglomerative hierarchical clustering, principal component analysis, and kernel-based clustering were applied to explore multivariate covariance structures. Then, high-frequency temporal analyses, including vector autoregressive integrated moving average impulse response functions (VARIMA IRF), cross-correlation, and Granger causality, were performed to assess dynamic coupling between RAP and other physiological signals. Results: Impaired and exhausted RAP states were associated with elevated intracranial pressure (p = 0.021). Regarding AMP, impaired RAP was associated with elevated levels, while exhausted RAP was associated with reduced pulse amplitude (p = 3.94 × 10−9). These two RAP states were also associated with compromised autoregulation and diminished perfusion. Clustering analyses consistently grouped RAP with its constituent signals (ICP and AMP), followed by brain oxygenation parameters (brain tissue oxygenation (PbtO2) and regional cerebral oxygen saturation (rSO2)). Cerebral autoregulation (CA) indices clustered more closely with RAP under impaired autoregulatory states. Temporal analyses revealed that RAP exhibited comparatively stronger responses to ICP and arterial blood pressure (ABP) at 1-min resolution. Moreover, when comparing ICP-derived and near-infrared spectroscopy (NIRS)-derived CA indices, they clustered more closely to RAP, and RAP demonstrated greater sensitivity to changes in these ICP-derived CA indices in high-frequency temporal analyses. These trends remained consistent at lower temporal resolutions as well. Conclusion: RAP relationships with other parameters remain consistent and differ meaningfully across compliance states. Integrating RAP into patient trajectory modelling and developing predictive frameworks based on these findings across different RAP states can map the evolution of cerebral physiology over time. This approach may improve prognostication and guide individualized interventions in TBI management. Therefore, these findings support RAP’s potential as a valuable metric for bedside monitoring and its prospective role in guiding patient trajectory modeling and interventional studies in TBI.

Brain tissue oxygen tension (PbtO2) has emerged as a cerebral monitoring modality following traumatic brain injury (TBI). Near-infrared spectroscopy (NIRS)-based regional cerebral oxygen saturation (rSO2) can non-invasively examine cerebral oxygen content and has the potential for high spatial resolution. Past studies examining the relationship between PbtO2 and NIRS-based parameters have had conflicting results with varying degrees of correlation. Understanding this relationship will help guide multimodal monitoring practices and impact patient care. The aim of this study is to examine the relationship between PbtO2 and rSO2 in a cohort of TBI patients by leveraging contemporary statistical methods. A multi-institutional retrospective cohort study of prospectively collected data was performed. Moderate-to-severe adult TBI patients were included with concurrent rSO2 and PbtO2 monitoring during their stay in the intensive care unit (ICU). The high-resolution data were analyzed utilizing time series techniques to examine signal stationarity as well as the cross-correlation relationship between the change in PbtO2 and the change in rSO2 signals. Finally, modeling of the change in PbtO2 by the change in rSO2 was attempted utilizing linear methods that account for the autocorrelative nature of the data signals. A total of 20 subjects were included in the study. Cross-correlative analysis found that changes in PbtO2 were most significantly correlated with changes in rSO2 one minute earlier. Through mixed-effects and time series modeling of parameters, changes in rSO2 were found to often have a statistically significant linear relationship with changes in PbtO2 that occurred a minute later. However, changes in rSO2 were inadequate to predict changes in PbtO2. In this study, changes in PbtO2 were found to correlate most with changes in rSO2 approximately one minute earlier. While changes in rSO2 were found to contain information about future changes in PbtO2, they were not found to adequately model them. This strengthens the body of literature indicating that NIRS-based rSO2 is not an adequate substitute for PbtO2 in the management of TBI.