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

Modelling the inflammatory response of traumatic brain injury using human induced pluripotent stem cell derived microglia

The neuroinflammatory response after traumatic brain injury (TBI) is implicated as a key mediator of secondary injury in both the acute and chronic periods after primary injury. Microglia are the key innate immune cell in the central nervous system, responding to injury with the release of cytokines and chemokines. In this context, we aimed to characterise the downstream cytokine response of human induced pluripotent stem cell (iPSC)-derived microglia when stimulated with five separate cytokines identified following human TBI. iPSC-derived microglia were exposed to IL-1β, IL-4, IL-6, IL-10 and TNF in the concentration ranges identified in clinical TBI studies. The downstream cytokine response was measured against a panel of 37 separate cytokines over a 72-hour time-course. The secretome revealed concentration-, time- and combined concentration and time-dependent downstream responses. TNF appeared to be the strongest inducer of downstream cytokine changes (51), followed by IL-1β (26) and IL-4 (19). IL-10 (11) and IL-6 (10) produced fewer responses. We also compare these responses to our previous studies of iPSC-derived neuronal and astrocyte cultures and the in-vivo human TBI cytokine response. Notably, we found microglial culture to induce both a wider range of downstream cytokine responses and a greater fold change in concentration for those downstream responses, as compared to astrocyte and neuronal cultures. In summary, we present a dataset for human microglial cytokine responses specific to the secretome found in the clinical context of TBI. This reductionist approach complements our previous datasets for astrocyte and neuronal responses and will provide a platform to enable future studies to unravel the complex neuroinflammatory network activated after TBI

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

Modelling the inflammatory response of traumatic brain injury using human induced pluripotent stem cell derived microglia

The neuroinflammatory response after traumatic brain injury (TBI) is implicated as a key mediator of secondary injury in both the acute and chronic periods after primary injury. Microglia are the key innate immune cell in the central nervous system, responding to injury with the release of cytokines and chemokines. In this context, we aimed to characterise the downstream cytokine response of human induced pluripotent stem cell (iPSC)-derived microglia when stimulated with five separate cytokines identified following human TBI. iPSC-derived microglia were exposed to IL-1β, IL-4, IL-6, IL-10 and TNF in the concentration ranges identified in clinical TBI studies. The downstream cytokine response was measured against a panel of 37 separate cytokines over a 72-hour time-course. The secretome revealed concentration-, time- and combined concentration and time-dependent downstream responses. TNF appeared to be the strongest inducer of downstream cytokine changes (51), followed by IL-1β (26) and IL-4 (19). IL-10 (11) and IL-6 (10) produced fewer responses. We also compare these responses to our previous studies of iPSC-derived neuronal and astrocyte cultures and the in-vivo human TBI cytokine response. Notably, we found microglial culture to induce both a wider range of downstream cytokine responses and a greater fold change in concentration for those downstream responses, as compared to astrocyte and neuronal cultures. In summary, we present a dataset for human microglial cytokine responses specific to the secretome found in the clinical context of TBI. This reductionist approach complements our previous datasets for astrocyte and neuronal responses and will provide a platform to enable future studies to unravel the complex neuroinflammatory network activated after TBI

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 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

Kinfitr - an open-source tool for reproducible PET modelling : validation and evaluation of test-retest reliability

BACKGROUND: In positron emission tomography (PET) imaging, binding is typically estimated by fitting pharmacokinetic models to the series of measurements of radioactivity in the target tissue following intravenous injection of a radioligand. However, there are multiple different models to choose from and numerous analytical decisions that must be made when modelling PET data. Therefore, it is important that analysis tools be adapted to the specific circumstances, and that analyses be documented in a transparent manner. Kinfitr, written in the open-source programming language R, is a tool developed for flexible and reproducible kinetic modelling of PET data, i.e. performing all steps using code which can be publicly shared in analysis notebooks. In this study, we compared outcomes obtained using kinfitr with those obtained using PMOD: a widely used commercial tool. RESULTS: Using previously collected test-retest data obtained with four different radioligands, a total of six different kinetic models were fitted to time-activity curves derived from different brain regions. We observed good correspondence between the two kinetic modelling tools both for binding estimates and for microparameters. Likewise, no substantial differences were observed in the test-retest reliability estimates between the two tools. CONCLUSIONS: In summary, we showed excellent agreement between the open-source R package kinfitr, and the widely used commercial application PMOD. We, therefore, conclude that kinfitr is a valid and reliable tool for kinetic modelling of PET data

Comparison between ticagrelor and clopidogrel in myocardial infarction patients with high bleeding risk

Aims Ticagrelor is associated with a lower risk of ischemic events than clopidogrel. However, it is uncertain whether the benefits of more intensive anti-ischemic therapy outweigh the risks of major bleeding in patients who have a high bleeding risk (HBR). Therefore, this study compared ticagrelor and clopidogrel in myocardial infarction (MI) patients with HBR. Methods and results This study included all patients enrolled in the SWEDEHEART registry who were discharged with dual antiplatelet therapy using ticagrelor or clopidogrel following MI between 2010 and 2017. High bleeding risk was defined as a PRECISE-DAPT score &amp; GE;25. Information on ischemic events, major bleeding, and mortality was obtained from national registries, with 365 days of follow-up. Additional outcomes include major adverse cardiovascular events (MACE), a composite of MI, stroke and all-cause mortality, and net adverse clinical events (NACE), a composite of MACE and bleeding. This study included 25 042 HBR patients, of whom 11 848 were treated with ticagrelor. Ticagrelor was associated with a lower risk of MI, stroke, and MACE, but a higher risk of bleeding compared to clopidogrel. There were no significant differences in mortality and NACE. Additionally, when examining the relationship between antiplatelet therapy and bleeding risk in 69 040 MI patients, we found no statistically significant interactions between the PRECISE-DAPT score and treatment effect. Conclusions We observed no difference in NACE when comparing ticagrelor and clopidogrel in HBR patients. Moreover, we found no statistically significant interactions between bleeding risk and the comparative effectiveness of clopidogrel and ticagrelor in a larger population of MI patients.Funding Agencies|Stockholm County council</p

The impact of sedative and vasopressor agents on cerebrovascular reactivity in severe traumatic brain injury

Funder: Manitoba Public InsuranceFunder: Karolinska InstituteBackground: The aim of this study is to evaluate the impact of commonly administered sedatives (Propofol, Alfentanil, Fentanyl, and Midazolam) and vasopressor (Dobutamine, Ephedrine, Noradrenaline and Vasopressin) agents on cerebrovascular reactivity in moderate/severe TBI patients. Cerebrovascular reactivity, as a surrogate for cerebral autoregulation was assessed using the long pressure reactivity index (LPRx). We evaluated the data in two phases, first we assessed the minute-by-minute data relationships between different dosing amounts of continuous infusion agents and physiological variables using boxplots, multiple linear regression and ANOVA. Next, we assessed the relationship between continuous/bolus infusion agents and physiological variables, assessing pre-/post- dose of medication change in physiology using a Wilcoxon signed-ranked test. Finally, we evaluated sub-groups of data for each individual dose change per medication, focusing on key physiological thresholds and demographics. Results: Of the 475 patients with an average stay of 10 days resulting in over 3000 days of recorded information 367 (77.3%) were male with a median Glasgow coma score of 7 (4–9). The results of this retrospective observational study confirmed that the infusion of most administered agents do not impact cerebrovascular reactivity, which is confirmed by the multiple linear regression components having p value > 0.05. Incremental dose changes or bolus doses in these medications in general do not lead to significant changes in cerebrovascular reactivity (confirm by Wilcoxon signed-ranked p value > 0.05 for nearly all assessed relationships). Within the sub-group analysis that separated the data based on LPRx pre-dose, a significance between pre-/post-drug change in LPRx was seen, however this may be more of a result from patient state than drug impact. Conclusions: Overall, this study indicates that commonly administered agents with incremental dosing changes have no clinically significant influence on cerebrovascular reactivity in TBI (nor do they impair cerebrovascular reactivity). Though further investigation in a larger and more diverse TBI patient population is required

Modelling the inflammatory response of traumatic brain injury using human induced pluripotent stem cell derived microglia.

The neuroinflammatory response after traumatic brain injury (TBI) is implicated as a key mediator of secondary injury in both the acute and chronic periods after primary injury. Microglia are the key innate immune cell in the central nervous system, responding to injury with the release of cytokines and chemokines. In this context, we aimed to characterise the downstream cytokine response of human induced pluripotent stem cell (iPSC)-derived microglia when stimulated with five separate cytokines identified following human TBI. iPSC-derived microglia were exposed to IL-1β, IL-4, IL-6, IL-10 and TNF in the concentration ranges identified in clinical TBI studies. The downstream cytokine response was measured against a panel of 37 separate cytokines over a 72-hour time-course. The secretome revealed concentration-, time- and combined concentration and time-dependent downstream responses. TNF appeared to be the strongest inducer of downstream cytokine changes (51), followed by IL-1β (26) and IL-4 (19). IL-10 (11) and IL-6 (10) produced fewer responses. We also compare these responses to our previous studies of iPSC-derived neuronal and astrocyte cultures and the in-vivo human TBI cytokine response. Notably, we found microglial culture to induce both a wider range of downstream cytokine responses and a greater fold change in concentration for those downstream responses, as compared to astrocyte and neuronal cultures. In summary, we present a dataset for human microglial cytokine responses specific to the secretome found in the clinical context of TBI. This reductionist approach complements our previous datasets for astrocyte and neuronal responses and will provide a platform to enable future studies to unravel the complex neuroinflammatory network activated after TBI

The impact of sedative and vasopressor agents on cerebrovascular reactivity in severe traumatic brain injury.

Funder: Manitoba Public InsuranceFunder: Karolinska InstituteBACKGROUND: The aim of this study is to evaluate the impact of commonly administered sedatives (Propofol, Alfentanil, Fentanyl, and Midazolam) and vasopressor (Dobutamine, Ephedrine, Noradrenaline and Vasopressin) agents on cerebrovascular reactivity in moderate/severe TBI patients. Cerebrovascular reactivity, as a surrogate for cerebral autoregulation was assessed using the long pressure reactivity index (LPRx). We evaluated the data in two phases, first we assessed the minute-by-minute data relationships between different dosing amounts of continuous infusion agents and physiological variables using boxplots, multiple linear regression and ANOVA. Next, we assessed the relationship between continuous/bolus infusion agents and physiological variables, assessing pre-/post- dose of medication change in physiology using a Wilcoxon signed-ranked test. Finally, we evaluated sub-groups of data for each individual dose change per medication, focusing on key physiological thresholds and demographics. RESULTS: Of the 475 patients with an average stay of 10 days resulting in over 3000 days of recorded information 367 (77.3%) were male with a median Glasgow coma score of 7 (4-9). The results of this retrospective observational study confirmed that the infusion of most administered agents do not impact cerebrovascular reactivity, which is confirmed by the multiple linear regression components having p value > 0.05. Incremental dose changes or bolus doses in these medications in general do not lead to significant changes in cerebrovascular reactivity (confirm by Wilcoxon signed-ranked p value > 0.05 for nearly all assessed relationships). Within the sub-group analysis that separated the data based on LPRx pre-dose, a significance between pre-/post-drug change in LPRx was seen, however this may be more of a result from patient state than drug impact. CONCLUSIONS: Overall, this study indicates that commonly administered agents with incremental dosing changes have no clinically significant influence on cerebrovascular reactivity in TBI (nor do they impair cerebrovascular reactivity). Though further investigation in a larger and more diverse TBI patient population is required