Current state of high-fidelity multimodal monitoring in traumatic brain injury

Introduction Multimodality monitoring of patients with severe traumatic brain injury (TBI) is primarily performed in neurocritical care units to prevent secondary harmful brain insults and facilitate patient recovery. Several metrics are commonly monitored using both invasive and non-invasive techniques. The latest Brain Trauma Foundation guidelines from 2016 provide recommendations and thresholds for some of these. Still, high-level evidence for several metrics and thresholds is lacking. Methods Regarding invasive brain monitoring, intracranial pressure (ICP) forms the cornerstone, and pressures above 22 mmHg should be avoided. From ICP, cerebral perfusion pressure (CPP) (mean arterial pressure (MAP)-ICP) and pressure reactivity index (PRx) (a correlation between slow waves MAP and ICP as a surrogate for cerebrovascular reactivity) may be derived. In terms of regional monitoring, partial brain tissue oxygen pressure (PbtO(2)) is commonly used, and phase 3 studies are currently ongoing to determine its added effect to outcome together with ICP monitoring. Cerebral microdialysis (CMD) is another regional invasive modality to measure substances in the brain extracellular fluid. International consortiums have suggested thresholds and management strategies, in spite of lacking high-level evidence. Although invasive monitoring is generally safe, iatrogenic hemorrhages are reported in about 10% of cases, but these probably do not significantly affect long-term outcome. Non-invasive monitoring is relatively recent in the field of TBI care, and research is usually from single-center retrospective experiences. Near-infrared spectrometry (NIRS) measuring regional tissue saturation has been shown to be associated with outcome. Transcranial doppler (TCD) has several tentative utilities in TBI like measuring ICP and detecting vasospasm. Furthermore, serial sampling of biomarkers of brain injury in the blood can be used to detect secondary brain injury development. Conclusions In multimodal monitoring, the most important aspect is data interpretation, which requires knowledge of each metric's strengths and limitations. Combinations of several modalities might make it possible to discern specific pathologic states suitable for treatment. However, the cost-benefit should be considered as the incremental benefit of adding several metrics has a low level of evidence, thus warranting additional research.Peer reviewe

Monthlong Intubated Patient with Life-Threatening COVID-19 and Cerebral Microbleeds Suffers Only Mild Cognitive Sequelae at 8-Month Follow-up: A Case Report.

OBJECTIVE: To elaborate on possible cognitive sequelae related to COVID-19, associated cerebrovascular injuries as well as the general consequences from intensive care. COVID-19 is known to have several, serious CNS-related consequences, but neuropsychological studies of severe COVID-19 are still rare. METHODS: M., a 45-year-old man, who survived a severe COVID-19 disease course including Acute Respiratory Distress Syndrome (ARDS), cerebral microbleeds, and 35 days of mechanical ventilation, is described. We elaborate on M's recovery and rehabilitation process from onset to the 8-month follow-up. The cognitive functions were evaluated with a comprehensive screening battery at 4 weeks after extubation and at the 8-month follow-up. RESULTS: Following extubation, M. was delirious, reported visual hallucinations, and had severe sleeping difficulties. At about 3 months after COVID-19 onset, M. showed mild to moderate deficits on tests measuring processing speed, working memory, and attention. At assessments at 8 months, M. performed better, with results above average on tests measuring learning, memory, word fluency, and visuospatial functions. Minor deficits were still found regarding logical reasoning, attention, executive functioning, and processing speed. There were no lingering psychiatric symptoms. While M. had returned to a part-time job, he was not able to resume previous work-tasks. CONCLUSION: This case-study demonstrates possible cognitive deficits after severe COVID-19 and emphasizes the need of a neuropsychological follow-up, with tests sensitive to minor deficits. The main findings of this report provide some support that the long-term prognosis for cognition in severe COVID-19 may be hopeful

Cellular infiltration in traumatic brain injury

Abstract: 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

Extended Analysis of Axonal Injuries Detected Using Magnetic Resonance Imaging in Critically Ill Traumatic Brain Injury Patients

Publisher Copyright: © Jonathan Tjerkaski et al., 2022; Published by Mary Ann Liebert, Inc. 2022.Studies show conflicting results regarding the prognostic significance of traumatic axonal injuries (TAI) in patients with traumatic brain injury (TBI). Therefore, we documented the presence of TAI in several brain regions, using different magnetic resonance imaging (MRI) sequences, and assessed their association to patient outcomes using machine learning. Further, we created a novel MRI-based TAI grading system with the goal of improving outcome prediction in TBI. We subsequently evaluated the performance of several TAI grading systems. We used a genetic algorithm to identify TAI that distinguish favorable from unfavorable outcomes. We assessed the discriminatory performance (area under the curve [AUC]) and goodness-of-fit (Nagelkerke pseudo-R2) of the novel Stockholm MRI grading system and the TAI grading systems of Adams and associates, Firsching and coworkers. and Abu Hamdeh and colleagues, using both univariate and multi-variate logistic regression. The dichotomized Glasgow Outcome Scale was considered the primary outcome. We examined the MRI scans of 351 critically ill patients with TBI. The TAI in several brain regions, such as the midbrain tegmentum, were strongly associated with unfavorable outcomes. The Stockholm MRI grading system exhibited the highest AUC (0.72 vs. 0.68-0.69) and Nagelkerke pseudo-R2 (0.21 vs. 0.14-0.15) values of all TAI grading systems. These differences in model performance, however, were not statistically significant (DeLong test, p > 0.05). Further, all included TAI grading systems improved outcome prediction relative to established outcome predictors of TBI, such as the Glasgow Coma Scale (likelihood-ratio test, p < 0.001). Our findings suggest that the detection of TAI using MRI is a valuable addition to prognostication in TBI.Peer reviewe

Prognostic performance of computerized tomography scoring systems in civilian penetrating traumatic brain injury : an observational study

Background The prognosis of penetrating traumatic brain injury (pTBI) is poor yet highly variable. Current computerized tomography (CT) severity scores are commonly not used for pTBI prognostication but may provide important clinical information in these cohorts. Methods All consecutive pTBI patients from two large neurotrauma databases (Helsinki 1999-2015, Stockholm 2005-2014) were included. Outcome measures were 6-month mortality and unfavorable outcome (Glasgow Outcome Scale 1-3). Admission head CT scans were assessed according to the following: Marshall CT classification, Rotterdam CT score, Stockholm CT score, and Helsinki CT score. The discrimination (area under the receiver operating curve, AUC) and explanatory variance (pseudo-R-2) of the CT scores were assessed individually and in addition to a base model including age, motor response, and pupil responsiveness. Results Altogether, 75 patients were included. Overall 6-month mortality and unfavorable outcome were 45% and 61% for all patients, and 31% and 51% for actively treated patients. The CT scores' AUCs and pseudo-R(2)s varied between 0.77-0.90 and 0.35-0.60 for mortality prediction and between 0.85-0.89 and 0.50-0.57 for unfavorable outcome prediction. The base model showed excellent performance for mortality (AUC 0.94, pseudo-R-2 0.71) and unfavorable outcome (AUC 0.89, pseudo-R-2 0.53) prediction. None of the CT scores increased the base model's AUC (p > 0.05) yet increased its pseudo-R-2 (0.09-0.15) for unfavorable outcome prediction. Conclusion Existing head CT scores demonstrate good-to-excellent performance in 6-month outcome prediction in pTBI patients. However, they do not add independent information to known outcome predictors, indicating that a unique score capturing the intracranial severity in pTBI may be warranted.Peer reviewe

TRAJECTORY CLUSTERING USING LATENT CLASS MODELS FOR UNSUPERVISED TBI BIOMARKER TEMPORAL PHENOTYPE DISCOVER

Background: TBI biomarkers display population-level time-varying kinetics [1] which may be a rich source of pathobiological information [2]. At an individual level, deviations from stereotypical trajectories may represent different pathological processes or secondary insults. A method for discovering such phenotypes may be useful in in- dividualising treatments in real-time. Methods: Serial blood (12hourly) and CSF (6hourly) samples were obtained from seventeen adult patients with severe TBI (Stockholm ethics committee approval #2009/1112-31). S100B and neuron-specific enolase (NSE) concentrations were measured along with blood:CSF albumin quotient Qa as a measure of blood-brain-barrier (BBB) integrity. S100B and NSE concentrations were log-transformed: Equivalent to the assumption of baseline exponential decay. We used trajectory modeling combining a quadratic mixed effects model with latent group analysis to search for characteristic trajectories in the measured parameter. Results: For serum S100B, we discovered two phenotypes with fast and slow kinetics. The fast group corresponded with patients with more severe extracranial injury. For serum NSE, again two phenotypes were discovered; a time-decaying group and another with a peak around day 4. CSF analysis yielded two latent groups for both S100B and NSE: a time-decaying group and another displaying prolonged elevation over several days. Qa data clustered into three groups: two with fast, slow decay and another with prolonged elevation. The group with prolonged BBB permeability had corresponding poorer outcomes. Conclusions: Small numbers prevent statistical comparison, but trajectory modeling identified a number of phenotypes with plausible pathobiological significance. In particular the technique revealed a group of patients with secondary serum NSE release and another with sustained BBB permeability. Such groups seem to relate to injury profile and outcome suggesting biological relevance. To our knowledge this is the first use of an unsupervised clustering technique in kinetic phenotype discovery. References: [1] Ercole A, Thelin EP, Holst A, Bellander BM, Nelson DW. Kinetic modelling of serum S100b after traumatic brain injury. BMC Neurol. 2016;16:93. [2] Thelin EP, Zeiler FA, Ercole A, Mondello S, Büki A, Bellander BM, Helmy A, Menon DK, Nelson DW. Serial Sampling of Serum Protein Biomarkers for Monitoring Human Traumatic Brain Injury Dynamics: A Systematic Review. Front Neurol. 2017;8:300

The cerebrospinal fluid proteome of preterm infants predicts neurodevelopmental outcome

BackgroundSurvival rate increases for preterm infants, but long-term neurodevelopmental outcome predictors are lacking. Our primary aim was to determine whether a specific proteomic profile in cerebrospinal fluid (CSF) of preterm infants differs from that of term infants and to identify novel biomarkers of neurodevelopmental outcome in preterm infants.MethodsTwenty-seven preterm infants with median gestational age 27 w + 4 d and ten full-term infants were enrolled prospectively. Protein profiling of CSF were performed utilizing an antibody suspension bead array. The relative levels of 178 unique brain derived proteins and inflammatory mediators, selected from the Human Protein Atlas, were measured.ResultsThe CSF protein profile of preterm infants differed from that of term infants. Increased levels of brain specific proteins that are associated with neurodevelopment and neuroinflammatory pathways made up a distinct protein profile in the preterm infants. The most significant differences were seen in proteins involved in neurodevelopmental regulation and synaptic plasticity, as well as components of the innate immune system. Several proteins correlated with favorable outcome in preterm infants at 18–24 months corrected age. Among the proteins that provided strong predictors of outcome were vascular endothelial growth factor C, Neurocan core protein and seizure protein 6, all highly important in normal brain development.ConclusionOur data suggest a vulnerability of the preterm brain to postnatal events and that alterations in protein levels may contribute to unfavorable neurodevelopmental outcome

Dynamic prediction of mortality after traumatic brain injury using a machine learning algorithm

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 toPeer reviewe

The cerebrospinal fluid proteome of preterm infants predicts neurodevelopmental outcome

Funding Information: This study was funded by the Karolinska Institutet, the University Hospital of Iceland and the Swedish Society for Medical Research, the Swedish Brain Foundation (FO2019-0087 and FO2019-0006), Strategic Research Area Neuroscience (StratNeuro), Ehrling-Person Family Foundation, Axel Tielmans, Freemasons Children’s House, the Swedish National Heart and Lung (20180505) Foundations, the Swedish Research Council (2019-01157), and the Stockholm County Council (20190400). KJ received funding from the Swiss National Science Foundation (Postdoc Mobility Fellowship, P400PM_194474. The funders did not participate in the design or conduct of the study. Publisher Copyright: Copyright © 2022 Leifsdottir, Jost, Siljehav, Thelin, Lassarén, Nilsson, Haraldsson, Eksborg and Herlenius.Background: Survival rate increases for preterm infants, but long-term neurodevelopmental outcome predictors are lacking. Our primary aim was to determine whether a specific proteomic profile in cerebrospinal fluid (CSF) of preterm infants differs from that of term infants and to identify novel biomarkers of neurodevelopmental outcome in preterm infants. Methods: Twenty-seven preterm infants with median gestational age 27 w + 4 d and ten full-term infants were enrolled prospectively. Protein profiling of CSF were performed utilizing an antibody suspension bead array. The relative levels of 178 unique brain derived proteins and inflammatory mediators, selected from the Human Protein Atlas, were measured. Results: The CSF protein profile of preterm infants differed from that of term infants. Increased levels of brain specific proteins that are associated with neurodevelopment and neuroinflammatory pathways made up a distinct protein profile in the preterm infants. The most significant differences were seen in proteins involved in neurodevelopmental regulation and synaptic plasticity, as well as components of the innate immune system. Several proteins correlated with favorable outcome in preterm infants at 18–24 months corrected age. Among the proteins that provided strong predictors of outcome were vascular endothelial growth factor C, Neurocan core protein and seizure protein 6, all highly important in normal brain development. Conclusion: Our data suggest a vulnerability of the preterm brain to postnatal events and that alterations in protein levels may contribute to unfavorable neurodevelopmental outcome.Peer reviewe

Cerebrovascular pressure reactivity and brain tissue oxygen monitoring provide complementary information regarding the lower and upper limits of cerebral blood flow control in traumatic brain injury : a CAnadian High Resolution-TBI (CAHR-TBI) cohort study

Background: Brain tissue oxygen tension (PbtO2) and cerebrovascular pressure reac-tivity monitoring have emerged as potential modalities to individualize care in moder-ate 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 PbtO(2) and cerebral perfusion pressure (CPP) and how this relationship is modified by the state of cerebrovascular pressure reactivity.Methods: A 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 pres-sure (ICP), arterial blood pressure (ABP), and PbtO(2) 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).Results: A 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.Conclusions: In this exploratory analysis of a multi-institution high-resolution physiology TBI database, PbtO(2) 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.Peer reviewe