A Solution to the Cerebral Perfusion Pressure Transducer Placement Conundrum in Neurointensive Care? The Dual Transducer.

Intracranial pressure is routinely monitored in most intensive care units caring for patients with severe neurological insults and, together with continuous arterial blood pressure measurement, allows for monitoring of cerebral perfusion pressure (CPP). CPP is the driving pressure of blood flow to the brain and is used to guide therapy. However, there is considerable inconsistency in the literature regarding how CPP is technically measured and, more specifically, the appropriate placement of the arterial pressure transducer. Depending on patient positioning and where the arterial pressure transducer is placed, the mean arterial pressure used for CPP calculation can vary widely by up to 15 mm Hg, which is greater than the acceptable variation in target ranges used clinically. Physiologically, the arterial pressure transducer should be placed at the level of the foramen of Monro for CPP measurement, but it is commonly set at the level of the right atrium for systematic measurement. Mean arterial pressure measurement at the level of the right atrium can lead to overestimation and potentially critically low actual CPP levels when the head is elevated, and measurement at the level of the foramen of Monro will underestimate systemic pressures, increasing the risk of excessive and unnecessary use of vasopressors and fluid. At the Karolinska University Hospital neurointensive care unit, we have used a split dual-transducer system, measuring arterial pressure both at the level of the foramen of Monro and at the level of the right atrium from a single arterial source. In doing so, we work with constants and can monitor and target optimum arterial pressures to better secure perfusion to all organs, with potentially less risk of cerebral ischemia or overuse of vasopressors and fluids, which may affect outcome.

Absolute Contusion Expansion Is Superior to Relative Expansion in Predicting Traumatic Brain Injury Outcomes: A Multi-Center Observational Cohort Study.

Contusion expansion (CE) is a potentially treatable outcome predictor in traumatic brain injury (TBI), and a suitable end-point for hemostatic therapy trials. However, there is no consensus on the definition of clinically relevant CE, both in terms of measurement criteria (absolute vs. relative volume increase) and cutoff values. In light of this, the aim of this study was to assess the predictive abilities of different CE definitions on outcome. We performed a multi-center observational cohort study of adults with moderate-to-severe TBI treated in an intensive care unit. The exposure of interest was CE, defined as the absolute and relative volume change between the first and second computed tomography scan. The primary outcome was the Glasgow Outcome Scale (GOS) at 6-12 months post-injury, dichotomized into unfavorable (GOS ≤3) or favorable (GOS ≥4). The secondary outcome was all-cause mortality. In total, 798 patients were included, with a median duration of 7.0 h between the first and second CT scan. The median absolute and relative CE was 1.5 mL (interquartile range [IQR] 0.1-8.3 mL) and 100% (IQR 10-530%), respectively. Both CE forms were independently associated with unfavorable GOS. Absolute CE outperformed relative CE in predicting both unfavorable GOS (area under the curve [AUC]: 0.65 vs. 0.60, p = 0.002) and all-cause mortality (AUC: 0.66 vs. 0.60, p = 0.003). For dichotomized CE, absolute cutoffs of 1-10 mL yielded the best results. We conclude that absolute CE demonstrates stronger outcome correlation than relative CE. In studies focusing on lesion progression in TBI, it may be advantageous to use absolute CE as the primary outcome metric. For dichotomized outcomes, cutoffs between 1 and 10 mL are suggested, depending on the desired sensitivity-specificity balance.

Clinical descriptors of disease trajectories in patients with traumatic brain injury in the intensive care unit (CENTER-TBI): a multicentre observational cohort study.

BACKGROUND: Patients with traumatic brain injury are a heterogeneous population, and the most severely injured individuals are often treated in an intensive care unit (ICU). The primary injury at impact, and the harmful secondary events that can occur during the first week of the ICU stay, will affect outcome in this vulnerable group of patients. We aimed to identify clinical variables that might distinguish disease trajectories among patients with traumatic brain injury admitted to the ICU. METHODS: We used data from the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) prospective observational cohort study. We included patients aged 18 years or older with traumatic brain injury who were admitted to the ICU at one of the 65 CENTER-TBI participating centres, which range from large academic hospitals to small rural hospitals. For every patient, we obtained pre-injury data and injury features, clinical characteristics on admission, demographics, physiological parameters, laboratory features, brain biomarkers (ubiquitin carboxy-terminal hydrolase L1 [UCH-L1], S100 calcium-binding protein B [S100B], tau, neurofilament light [NFL], glial fibrillary acidic protein [GFAP], and neuron-specific enolase [NSE]), and information about intracranial pressure lowering treatments during the first 7 days of ICU stay. To identify clinical variables that might distinguish disease trajectories, we applied a novel clustering method to these data, which was based on a mixture of probabilistic graph models with a Markov chain extension. The relation of clusters to the extended Glasgow Outcome Scale (GOS-E) was investigated. FINDINGS: Between Dec 19, 2014, and Dec 17, 2017, 4509 patients with traumatic brain injury were recruited into the CENTER-TBI core dataset, of whom 1728 were eligible for this analysis. Glucose variation (defined as the difference between daily maximum and minimum glucose concentrations) and brain biomarkers (S100B, NSE, NFL, tau, UCH-L1, and GFAP) were consistently found to be the main clinical descriptors of disease trajectories (ie, the leading variables contributing to the distinguishing clusters) in patients with traumatic brain injury in the ICU. The disease trajectory cluster to which a patient was assigned in a model was analysed as a predictor together with variables from the IMPACT model, and prediction of both mortality and unfavourable outcome (dichotomised GOS-E ≤4) was improved. INTERPRETATION: First-day ICU admission data are not the only clinical descriptors of disease trajectories in patients with traumatic brain injury. By analysing temporal variables in our study, variation of glucose was identified as the most important clinical descriptor that might distinguish disease trajectories in the ICU, which should direct further research. Biomarkers of brain injury (S100B, NSE, NFL, tau, UCH-L1, and GFAP) were also top clinical descriptors over time, suggesting they might be important in future clinical practice. FUNDING: European Union 7th Framework program, Hannelore Kohl Stiftung, OneMind, Integra LifeSciences Corporation, and NeuroTrauma Sciences.

Therapy Intensity Level Scale for Traumatic Brain Injury: Clinimetric Assessment on Neuro-Monitored Patients Across 52 European Intensive Care Units.

Intracranial pressure (ICP) data from traumatic brain injury (TBI) patients in the intensive care unit (ICU) cannot be interpreted appropriately without accounting for the effect of administered therapy intensity level (TIL) on ICP. A 15-point scale was originally proposed in 1987 to quantify the hourly intensity of ICP-targeted treatment. This scale was subsequently modified-through expert consensus-during the development of TBI Common Data Elements to address statistical limitations and improve usability. The latest 38-point scale (hereafter referred to as TIL) permits integrated scoring for a 24-h period and has a five-category, condensed version (TIL(Basic)) based on qualitative assessment. Here, we perform a total- and component-score analysis of TIL and TIL(Basic) to: 1) validate the scales across the wide variation in contemporary ICP management; 2) compare their performance against that of predecessors; and 3) derive guidelines for proper scale use. From the observational Collaborative European NeuroTrauma Effectiveness Research in TBI (CENTER-TBI) study, we extract clinical data from a prospective cohort of ICP-monitored TBI patients (n = 873) from 52 ICUs across 19 countries. We calculate daily TIL and TIL(Basic) scores (TIL24 and TIL(Basic)24, respectively) from each patient's first week of ICU stay. We also calculate summary TIL and TIL(Basic) scores by taking the first-week maximum (TILmax and TIL(Basic)max) and first-week median (TILmedian and TIL(Basic)median) of TIL24 and TIL(Basic)24 scores for each patient. We find that, across all measures of construct and criterion validity, the latest TIL scale performs significantly greater than or similarly to all alternative scales (including TIL(Basic)) and integrates the widest range of modern ICP treatments. TILmedian outperforms both TILmax and summarized ICP values in detecting refractory intracranial hypertension (RICH) during ICU stay. The RICH detection thresholds which maximize the sum of sensitivity and specificity are TILmedian ≥ 7.5 and TILmax ≥ 14. The TIL24 threshold which maximizes the sum of sensitivity and specificity in the detection of surgical ICP control is TIL24 ≥ 9. The median scores of each TIL component therapy over increasing TIL24 reflect a credible staircase approach to treatment intensity escalation, from head positioning to surgical ICP control, as well as considerable variability in the use of cerebrospinal fluid drainage and decompressive craniectomy. Since TIL(Basic)max suffers from a strong statistical ceiling effect and only covers 17% (95% confidence interval [CI]: 16-18%) of the information in TILmax, TIL(Basic) should not be used instead of TIL for rating maximum treatment intensity. TIL(Basic)24 and TIL(Basic)median can be suitable replacements for TIL24 and TILmedian, respectively (with up to 33% [95% CI: 31-35%] information coverage) when full TIL assessment is infeasible. Accordingly, we derive numerical ranges for categorising TIL24 scores into TIL(Basic)24 scores. In conclusion, our results validate TIL across a spectrum of ICP management and monitoring approaches. TIL is a more sensitive surrogate for pathophysiology than ICP and thus can be considered an intermediate outcome after TBI.

Mining the contribution of intensive care clinical course to outcome after traumatic brain injury.

Existing methods to characterise the evolving condition of traumatic brain injury (TBI) patients in the intensive care unit (ICU) do not capture the context necessary for individualising treatment. Here, we integrate all heterogenous data stored in medical records (1166 pre-ICU and ICU variables) to model the individualised contribution of clinical course to 6-month functional outcome on the Glasgow Outcome Scale -Extended (GOSE). On a prospective cohort (n = 1550, 65 centres) of TBI patients, we train recurrent neural network models to map a token-embedded time series representation of all variables (including missing values) to an ordinal GOSE prognosis every 2 h. The full range of variables explains up to 52% (95% CI: 50-54%) of the ordinal variance in functional outcome. Up to 91% (95% CI: 90-91%) of this explanation is derived from pre-ICU and admission information (i.e., static variables). Information collected in the ICU (i.e., dynamic variables) increases explanation (by up to 5% [95% CI: 4-6%]), though not enough to counter poorer overall performance in longer-stay (>5.75 days) patients. Highest-contributing variables include physician-based prognoses, CT features, and markers of neurological function. Whilst static information currently accounts for the majority of functional outcome explanation after TBI, data-driven analysis highlights investigative avenues to improve the dynamic characterisation of longer-stay patients. Moreover, our modelling strategy proves useful for converting large patient records into interpretable time series with missing data integration and minimal processing.

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

BACKGROUND: 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.

Time-Dependent Changes in the Biofluid Levels of Neural Injury Markers in Severe Traumatic Brain Injury Patients-Cerebrospinal Fluid and Cerebral Microdialysates: A Longitudinal Prospective Pilot Study.

Monitoring protein biomarker levels in the cerebrospinal fluid (CSF) can help assess injury severity and outcome after traumatic brain injury (TBI). Determining injury-induced changes in the proteome of brain extracellular fluid (bECF) can more closely reflect changes in the brain parenchyma, but bECF is not routinely available. The aim of this pilot study was to compare time-dependent changes of S100 calcium-binding protein B (S100B), neuron-specific enolase (NSE), total Tau, and phosphorylated Tau (p-Tau) levels in matching CSF and bECF samples collected at 1, 3, and 5 days post-injury from severe TBI patients (n = 7; GCS 3-8) using microcapillary-based western analysis. We found that time-dependent changes in CSF and bECF levels were most pronounced for S100B and NSE, but there was substantial patient-to-patient variability. Importantly, the temporal pattern of biomarker changes in CSF and bECF samples showed similar trends. We also detected two different immunoreactive forms of S100B in both CSF and bECF samples, but the contribution of the different immunoreactive forms to total immunoreactivity varied from patient to patient and time point to time point. Our study is limited, but it illustrates the value of both quantitative and qualitative analysis of protein biomarkers and the importance of serial sampling for biofluid analysis after severe TBI.

Transmembrane protein 135 regulates lipid homeostasis through its role in peroxisomal DHA metabolism.

Transmembrane protein 135 (TMEM135) is thought to participate in the cellular response to increased intracellular lipids yet no defined molecular function for TMEM135 in lipid metabolism has been identified. In this study, we performed a lipid analysis of tissues from Tmem135 mutant mice and found striking reductions of docosahexaenoic acid (DHA) across all Tmem135 mutant tissues, indicating a role of TMEM135 in the production of DHA. Since all enzymes required for DHA synthesis remain intact in Tmem135 mutant mice, we hypothesized that TMEM135 is involved in the export of DHA from peroxisomes. The Tmem135 mutation likely leads to the retention of DHA in peroxisomes, causing DHA to be degraded within peroxisomes by their beta-oxidation machinery. This may lead to generation or alteration of ligands required for the activation of peroxisome proliferator-activated receptor a (PPARa) signaling, which in turn could result in increased peroxisomal number and beta-oxidation enzymes observed in Tmem135 mutant mice. We confirmed this effect of PPARa signaling by detecting decreased peroxisomes and their proteins upon genetic ablation of Ppara in Tmem135 mutant mice. Using Tmem135 mutant mice, we also validated the protective effect of increased peroxisomes and peroxisomal beta-oxidation on the metabolic disease phenotypes of leptin mutant mice which has been observed in previous studies. Thus, we conclude that TMEM135 has a role in lipid homeostasis through its function in peroxisomes.

Time Course and Clinical Significance of Hematoma Expansion in Moderate-to-Severe Traumatic Brain Injury: An Observational Cohort Study.

BACKGROUND: Preventing intracranial hematoma expansion has been advertised as a possible treatment opportunity in traumatic brain injury (TBI). However, the time course of hematoma expansion, and whether the expansion affects outcome, remains poorly understood. In light of this, the aim of this study was to use 3D volume rendering to determine how traumatic intracranial hematomas expand over time and evaluate its impact on outcome. METHODS: Single-center, population-based, observational cohort study of adults with moderate-to-severe TBI. Hematoma expansion was defined as the change in hematoma volume from the baseline computed tomography scan until the lesion had stopped progressing. Volumes were calculated by using semiautomated volumetric segmentation. Functional outcome was measured by using the 12 month Glasgow outcome scale (GOS). RESULTS: In total, 643 patients were included. The mean baseline hematoma volume was 4.2 ml, and the subsequent mean hematoma expansion was 3.8 ml. Overall, 33% of hematomas had stopped progressing within 3 h, and 94% of hematomas had stopped progressing within 24 h of injury. Contusions expanded significantly more, and for a longer period of time, than extra-axial hematomas. There was a significant dose-response relationship between hematoma expansion and 12 month GOS, even after adjusting for known outcome predictors, with every 1-ml increase in hematoma volume associated with a 6% increased risk of 1-point GOS deduction. CONCLUSIONS: Hematoma expansion is a driver of unfavorable outcome in TBI, with small changes in hematoma volume also impacting functional outcome. This study also proposes a wider window of opportunity to prevent lesion progression than what has previously been suggested.

The leap to ordinal: Detailed functional prognosis after traumatic brain injury with a flexible modelling approach.

When a patient is admitted to the intensive care unit (ICU) after a traumatic brain injury (TBI), an early prognosis is essential for baseline risk adjustment and shared decision making. TBI outcomes are commonly categorised by the Glasgow Outcome Scale-Extended (GOSE) into eight, ordered levels of functional recovery at 6 months after injury. Existing ICU prognostic models predict binary outcomes at a certain threshold of GOSE (e.g., prediction of survival [GOSE > 1]). We aimed to develop ordinal prediction models that concurrently predict probabilities of each GOSE score. From a prospective cohort (n = 1,550, 65 centres) in the ICU stratum of the Collaborative European NeuroTrauma Effectiveness Research in TBI (CENTER-TBI) patient dataset, we extracted all clinical information within 24 hours of ICU admission (1,151 predictors) and 6-month GOSE scores. We analysed the effect of two design elements on ordinal model performance: (1) the baseline predictor set, ranging from a concise set of ten validated predictors to a token-embedded representation of all possible predictors, and (2) the modelling strategy, from ordinal logistic regression to multinomial deep learning. With repeated k-fold cross-validation, we found that expanding the baseline predictor set significantly improved ordinal prediction performance while increasing analytical complexity did not. Half of these gains could be achieved with the addition of eight high-impact predictors to the concise set. At best, ordinal models achieved 0.76 (95% CI: 0.74-0.77) ordinal discrimination ability (ordinal c-index) and 57% (95% CI: 54%- 60%) explanation of ordinal variation in 6-month GOSE (Somers' Dxy). Model performance and the effect of expanding the predictor set decreased at higher GOSE thresholds, indicating the difficulty of predicting better functional outcomes shortly after ICU admission. Our results motivate the search for informative predictors that improve confidence in prognosis of higher GOSE and the development of ordinal dynamic prediction models.

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.

Clustering identifies endotypes of traumatic brain injury in an intensive care cohort: a CENTER-TBI study.

BACKGROUND: While the Glasgow coma scale (GCS) is one of the strongest outcome predictors, the current classification of traumatic brain injury (TBI) as 'mild', 'moderate' or 'severe' based on this fails to capture enormous heterogeneity in pathophysiology and treatment response. We hypothesized that data-driven characterization of TBI could identify distinct endotypes and give mechanistic insights. METHODS: We developed an unsupervised statistical clustering model based on a mixture of probabilistic graphs for presentation (< 24 h) demographic, clinical, physiological, laboratory and imaging data to identify subgroups of TBI patients admitted to the intensive care unit in the CENTER-TBI dataset (N = 1,728). A cluster similarity index was used for robust determination of optimal cluster number. Mutual information was used to quantify feature importance and for cluster interpretation. RESULTS: Six stable endotypes were identified with distinct GCS and composite systemic metabolic stress profiles, distinguished by GCS, blood lactate, oxygen saturation, serum creatinine, glucose, base excess, pH, arterial partial pressure of carbon dioxide, and body temperature. Notably, a cluster with 'moderate' TBI (by traditional classification) and deranged metabolic profile, had a worse outcome than a cluster with 'severe' GCS and a normal metabolic profile. Addition of cluster labels significantly improved the prognostic precision of the IMPACT (International Mission for Prognosis and Analysis of Clinical trials in TBI) extended model, for prediction of both unfavourable outcome and mortality (both p < 0.001). CONCLUSIONS: Six stable and clinically distinct TBI endotypes were identified by probabilistic unsupervised clustering. In addition to presenting neurology, a profile of biochemical derangement was found to be an important distinguishing feature that was both biologically plausible and associated with outcome. Our work motivates refining current TBI classifications with factors describing metabolic stress. Such data-driven clusters suggest TBI endotypes that merit investigation to identify bespoke treatment strategies to improve care. Trial registration The core study was registered with ClinicalTrials.gov, number NCT02210221 , registered on August 06, 2014, with Resource Identification Portal (RRID: SCR_015582).

The Karolinska NeuroCOVID study protocol: Neurocognitive impairment, biomarkers and advanced imaging in critical care survivors.

BACKGROUND: This is the study plan of the Karolinska NeuroCOVID study, a study of neurocognitive impairment after severe COVID-19, relating post-intensive care unit (ICU) cognitive and neurological deficits to biofluid markers and MRI. The COVID-19 pandemic has posed enormous health challenges to individuals and health-care systems worldwide. An emerging feature of severe COVID-19 is that of temporary and extended neurocognitive impairment, exhibiting a myriad of symptoms and signs. The causes of this symptomatology have not yet been fully elucidated. METHODS: In this study, we aim to investigate patients treated for severe COVID-19 in the ICU, as to describe and relate serum-, plasma- and cerebrospinal fluid-borne molecular and cellular biomarkers of immune activity, coagulopathy, cerebral damage, neuronal inflammation, and degeneration, to the temporal development of structural and functional changes within the brain as evident by serial MRI and extensive cognitive assessments at 3-12 months after ICU discharge. RESULTS: To date, we have performed 51 3-month follow-up MRIs in the ICU survivors. Of these, two patients (~4%) have had incidental findings on brain MRI findings requiring activation of the Incidental Findings Management Plan. Furthermore, the neuropsychological and neurological examinations have so far revealed varying and mixed patterns. Several patients expressed cognitive and/or mental concerns and fatigue, complaints closely related to brain fog. CONCLUSION: The study goal is to gain a better understanding of the pathological mechanisms and neurological consequences of this new disease, with a special emphasis on neurodegenerative and neuroinflammatory processes, in order to identify targets of intervention and rehabilitation.

Contrasting recruitment of skin-associated adipose depots during cold challenge of mouse and human.

KEY POINTS: Several distinct strategies produce and conserve heat to maintain the body temperature of mammals, each associated with unique physiologies, with consequences for wellness and disease susceptibility Highly regulated properties of skin offset the total requirement for heat production  We hypothesize that the adipose component of skin is primarily responsible for modulating heat flux; here we evaluate the relative regulation of adipose depots in mouse and human, to test their recruitment to heat production and conservation We found that insulating mouse dermal white adipose tissue accumulates in response to environmentally and genetically induced cool stress; this layer is one of two adipose depots closely apposed to mouse skin, where the subcutaneous mammary gland fat pads are actively recruited to heat production In contrast, the body-wide adipose depot associated with human skin produces heat directly, potentially creating an alternative to the centrally regulated brown adipose tissue ABSTRACT: Mammalian skin impacts metabolic efficiency system-wide, controlling the rate of heat loss and consequent heat production. Here we compare the unique fat depots associated with mouse and human skin, to determine whether they have corresponding functions and regulation. For humans, we assay a skin-associated fat (SAF) body-wide depot to distinguish it from the subcutaneous fat pads characteristic of the abdomen and upper limbs. We show that the thickness of SAF is not related to general adiposity; it is much thicker (1.6-fold) in women than men, and highly subject-specific. We used molecular and cellular assays of ß-adrenergic-induced lipolysis and found that dermal white adipose tissue (dWAT) in mice is resistant to lipolysis; in contrast, the body-wide human SAF depot becomes lipolytic, generating heat in response to ß-adrenergic stimulation. In mice challenged to make more heat to maintain body temperature (either environmentally or genetically), there is a compensatory increase in thickness of dWAT: a corresponding ß-adrenergic stimulation of human skin adipose (in vivo or in explant) depletes adipocyte lipid content. We summarize the regulation of skin-associated adipocytes by age, sex and adiposity, for both species. We conclude that the body-wide dWAT depot of mice shows unique regulation that enables it to be deployed for heat preservation; combined with the actively lipolytic subcutaneous mammary fat pads they enable thermal defence. The adipose tissue that covers human subjects produces heat directly, providing an alternative to the brown adipose tissues.

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

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.

Discovery of inhibition of Burkholderia cenocepacia, Pseudomonas aeruginosa and Stenotrophomonas maltophilia by the Brown Rot Basidiomycete Fungus, Postia placenta.

Antimicrobial resistance (AMR) has now emerged as a major global public health problem. Certain bacterial pathogens, particularly Gram negative organisms associated with patients with cystic fibrosis (CF), have become resistant to several classes of antibiotics resulting in pan-resistance, which creates a clinical treatment dilemma. This study wished to explore the production of antibacterial extracellular metabolites from plant pathogenic fungi. Fungal Culture Extracts (FCEs) were prepared from 10 fungi (Armillaria gallica, Clitocybe nebularis, Fusarium coeruleum, Fusarium oxysporum, Fusarium poae, Hymenoscyphus fraxineus, Nectria fuckeliana, Phytophthora infestans, Phytophthora ramorum, Postia placenta), which were tested for activity against the CF pathogens, Pseudomonas aeruginosa (PA) (n=8), Burkholderia cenocepacia (n=2) and Stenotrophomonas maltophilia (n=2). In addition, FCE were assessed for their ability to alter antibiotic susceptibility in PA (n=8), with six antipseudomonal antibiotics (ceftazidime, ciprofloxacin, colistin, meropenem, piperacillin/tazobactam, tobramycin). None of the FCEs showed inhibitory activity to the 12 bacterial isolates tested, with the exception of the FCE from Postia placenta, which showed inhibition against all 12 bacteria. An antagonistic interaction was observed, where a statistically significant decrease in mean zone sizes was noted with Armillaria gallica (p=0.03) and Phytophthora infestans (p=0.03) FCEs and their interaction with the fluoroquinolone antibiotic, ciprofloxacin. Given the increase in clinical morbidity and mortality associated with chronic lung infections with Pseudomonas aeruginosa, Burkholderia cenocepacia and Stenotrophomonas maltophilia, coupled with the difficulty in treating such chronic infection due to overwhelming antimicrobial resistance, any novel substance showing inhibition of these organisms merits further investigation as a potential future antimicrobial agent, with potential clinical therapeutic application.

Imputation strategies for missing baseline neurological assessment covariates after traumatic brain injury: A CENTER-TBI study.

Statistical models for outcome prediction are central to traumatic brain injury research and critical to baseline risk adjustment. Glasgow coma score (GCS) and pupil reactivity are crucial covariates in all such models but may be measured at multiple time points between the time of injury and hospital and are subject to a variable degree of unreliability and/or missingness. Imputation of missing data may be undertaken using full multiple imputation or by simple substitution of measurements from other time points. However, it is unknown which strategy is best or which time points are more predictive. We evaluated the pseudo-R2 of logistic regression models (dichotomous survival) and proportional odds models (Glasgow Outcome Score-extended) using different imputation strategies on the The Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) study dataset. Substitution strategies were easy to implement, achieved low levels of missingness (<< 10%) and could outperform multiple imputation without the need for computationally costly calculations and pooling multiple final models. While model performance was sensitive to imputation strategy, this effect was small in absolute terms and clinical relevance. A strategy of using the emergency department discharge assessments and working back in time when these were missing generally performed well. Full multiple imputation had the advantage of preserving time-dependence in the models: the pre-hospital assessments were found to be relatively unreliable predictors of survival or outcome. The predictive performance of later assessments was model-dependent. In conclusion, simple substitution strategies for imputing baseline GCS and pupil response can perform well and may be a simple alternative to full multiple imputation in many cases.

Cerebrospinal fluid cell count variability is a major confounding factor in external ventricular drain-associated infection surveillance diagnostics: a prospective observational study.

BACKGROUND: External ventricular drain (EVD)-related infections (EVDIs) are feared complications that are difficult to rapidly and correctly diagnose, which can lead to unnecessary treatment with broad-spectrum antibiotics. No readily available diagnostic parameters have been identified to reliably predict or identify EVDIs. Moreover, intraventricular hemorrhage is common and affect cerebrospinal fluid (CSF) cellularity. The relationship between leukocytes and erythrocytes is often used to identify suspected infection and triggers the use of antibiotics pending results of cultures, which may take days. Cell count based surveillance diagnostics assumes a homogeneous distribution of cells in the CSF. Given the intraventricular sedimentation of erythrocytes on computed tomography scans this assumption may be erroneous and could affect diagnostics. AIMS: To evaluate the consistency of cell counts in serially sampled CSF from EVDs, with and without patient repositioning, to assess the effect on infection diagnostics. METHODS: We performed a prospective single-center study where routine CSF sampling was followed by a second sample after 10 min, allocated around a standard patient repositioning, or not. Changes in absolute and pairwise cell counts and ratios were analyzed, including mixed regression models. RESULTS: Data from 51 patients and 162 paired samples were analyzed. We observed substantial changes in CSF cellularity as the result of both resampling and repositioning, with repositioning found to be an independent predictor of bidirectional cellular change. Glucose and lactate levels were affected, however clinically non-significant. No positive CSF cultures were seen during the study. Thirty percent (30%) of patients changed suspected EVDI status, as defined by the cell component of local and national guidelines, when resampling after repositioning. CONCLUSIONS: CSF cell counts are not consistent and are affected by patient movement suggesting a heterogeneity in the intraventricular space. The relationship between leukocytes and erythrocytes was less affected than absolute changes. Importantly, cell changes are found to increase with increased cellularity, often leading to changes in suspected EVDI status. Faster and more precise diagnostics are needed, and methods such as emerging next generation sequencing techniques my provide tools to more timely and accurately guide antibiotic treatment. Trial Registration NCT04736407, Clinicaltrials.gov, retrospectively registered 2nd February 2021.

Variability in Serum Sodium Concentration and Prognostic Significance in Severe Traumatic Brain Injury: A Multicenter Observational Study.

BACKGROUND/OBJECTIVE: Dysnatremia is common in severe traumatic brain injury (TBI) patients and may contribute to mortality. However, serum sodium variability has not been studied in TBI patients. We hypothesized that such variability would be independently associated with mortality. METHODS: We collected 6-hourly serum sodium levels for the first 7 days of ICU admission from 240 severe TBI patients in 14 neurotrauma ICUs in Europe and Australia. We evaluated the association between daily serum sodium standard deviation (dNaSD), an index of variability, and 28-day mortality. RESULTS: Patients were 46 ± 19 years of age with a median initial GCS of 6 [4-8]. Overall hospital mortality was 28%. Hypernatremia and hyponatremia occurred in 64% and 24% of patients, respectively. Over the first 7 days in ICU, serum sodium standard deviation was 2.8 [2.0-3.9] mmol/L. Maximum daily serum sodium standard deviation (dNaSD) occurred at a median of 2 [1-4] days after admission. There was a significant progressive decrease in dNaSD over the first 7 days (coefficient - 0.15 95% CI [- 0.18 to - 0.12], p < 0.001). After adjusting for baseline TBI severity, diabetes insipidus, the use of osmotherapy, the occurrence of hypernatremia, and hyponatremia and center, dNaSD was significantly independently associated with 28-day mortality (HR 1.27 95% CI (1.01-1.61), p = 0.048). CONCLUSIONS: Our study demonstrates that daily serum sodium variability is an independent predictor of 28-day mortality in severe TBI patients. Further prospective investigations are necessary to confirm the significance of sodium variability in larger cohorts of TBI patients and test whether attenuating such variability confers outcome benefits to such patients.

Impact of duration and magnitude of raised intracranial pressure on outcome after severe traumatic brain injury: A CENTER-TBI high-resolution group study.

Magnitude of intracranial pressure (ICP) elevations and their duration have been associated with worse outcomes in patients with traumatic brain injuries (TBI), however published thresholds for injury vary and uncertainty about these levels has received relatively little attention. In this study, we have analyzed high-resolution ICP monitoring data in 227 adult patients in the CENTER-TBI dataset. Our aim was to identify thresholds of ICP intensity and duration associated with worse outcome, and to evaluate the uncertainty in any such thresholds. We present ICP intensity and duration plots to visualize the relationship between ICP events and outcome. We also introduced a novel bootstrap technique to evaluate uncertainty of the equipoise line. We found that an intensity threshold of 18 ± 4 mmHg (2 standard deviations) was associated with worse outcomes in this cohort. In contrast, the uncertainty in what duration is associated with harm was larger, and safe durations were found to be population dependent. The pressure and time dose (PTD) was also calculated as area under the curve above thresholds of ICP. A relationship between PTD and mortality could be established, as well as for unfavourable outcome. This relationship remained valid for mortality but not unfavourable outcome after adjusting for IMPACT core variables and maximum therapy intensity level. Importantly, during periods of impaired autoregulation (defined as pressure reactivity index (PRx)>0.3) ICP events were associated with worse outcomes for nearly all durations and ICP levels in this cohort and there was a stronger relationship between outcome and PTD. Whilst caution should be exercised in ascribing causation in observational analyses, these results suggest intracranial hypertension is poorly tolerated in the presence of impaired autoregulation. ICP level guidelines may need to be revised in the future taking into account cerebrovascular autoregulation status considered jointly with ICP levels.