Evaluating and Updating the IMPACT model to predict outcomes in two contemporary North American TBI cohorts.

The International Mission on Prognosis and Analysis of Clinical Trials in Traumatic Brain Injury (IMPACT) model is a widely recognized prognostic model applied after traumatic brain injury (TBI). However, it was developed with patient cohorts that may not reflect modern practice patterns in North America. We analyzed data from two sources: the placebo arm of the phase II double-blind, multicenter randomized controlled trial Prehospital Tranexamic Acid for TBI (TXA) cohort and data from an observational cohort with similar inclusion/exclusion criteria (Predictors of Low-risk Phenotypes after Traumatic Brain Injury Incorporating Proteomic Biomarker Signatures (PROTIPS) cohort). All three versions of the IMPACT model - core, extended, and laboratory - were evaluated for 6-month mortality (GOSE=1) and unfavorable outcomes (GOSE=1-4). Calibration (intercept and slope) and discrimination (ROC-AUC) were used to assess model performance. We then compared three model updating methods - recalibration in the large, logistic recalibration, and coefficient update - with the best update method determined by likelihood ratio tests.　 In our calibration analysis, recalibration improved both intercepts and slopes, indicating more accurate predicted probabilities when recalibration was done. Discriminative performance of the IMPACT models, measured by AUC, showed mortality prediction ROCs between 0.61 to 0.82 for the TXA cohort, with the coefficient updated Lab model achieving the highest at 0.84. Unfavorable outcomes had lower AUCs, ranging from 0.60 to 0.79. Similarly, in the PROTIPS cohort, AUCs for mortality ranged from 0.75 to 0.82, with the coefficient updated Lab model also showing superior performance (AUC 0.84). Unfavorable outcomes in this cohort presented AUCs from 0.67 to 0.73, consistently lower than mortality predictions. The closed testing procedure using likelihood ratio tests consistently identified the coefficient update model as superior, outperforming the original and recalibrated models across all cohorts. In our comprehensive evaluation of the IMPACT model, the coefficient updated models were the best-performing across all cohorts through a structured closed testing procedure. Thus, standardization of model updating procedures is needed to reproducibly determine the best performing versions of IMPACT that reflect the specific characteristics of a dataset.

Predicting Progression of Intracranial Hemorrhage in the Prehospital TXA for TBI Trial.

Progression of intracranial hemorrhage is a common, potentially devastating complication after moderate/severe traumatic brain injury (TBI). Clinicians have few tools to predict which patients with traumatic intracranial hemorrhage on their initial head computed tomography (hCT) scan will progress. The objective of this investigation was to identify clinical, imaging, and/or protein biomarkers associated with progression of intracranial hemorrhage (PICH) after moderate/severe TBI and to create an accurate predictive model of PICH based on clinical features available at presentation. We analyzed a subset of subjects from the phase II double-blind, multi-center, randomized "Prehospital Tranexamic Acid Use for TBI" trial. This subset was limited to the placebo arm of the parent trial with evidence of hemorrhage on the initial hCT and a follow-up hCT 6 h after. PICH was defined as an increase in hemorrhage size by 30% or more, or the development of new hemorrhage in the intra- and extra-axial intracranial vault between the initial and the follow-up hCT. Two independent radiologists evaluated each hCT, and conflicts were adjudicated by a third. Clinical and radiographic characteristics were collected, along with plasma protein biomarkers at admission. Principal component analysis (PCA) was performed, and each principal component (PC) was interrogated for its association with PICH. Finally, expert opinion and recursive feature extraction (RFE) were used to select input features for the construction of several supervised classification models. Their ability to predict PICH was quantified and compared. In this subset of subjects (n = 104), 46% (n = 48) demonstrated PICH. Univariate analyses showed no association between PICH and age, sex, admission Glasgow Coma Scale (GCS), GCS motor subscore, presence of midline shift, admission platelet count or admission INR. Radiographic severity scores (Marshall score [p = 0.007], Rotterdam score [p = 0.004]), and initial hematoma volume [p = 0.005] were associated with PICH. Higher levels of admission glial fibrillary acidic protein (p < 0.001) and MAP (p = 0.011) were also associated with PICH. Of the PCs, PC1 was significantly associated with PICH (p = 0.0125). Using multimodal data input, machine learning classifiers successfully discriminated patients with or without PICH. Models composed of machine-selected features performed better than models composed of expert-selected variables (reaching an average of 77% accuracy, AUC = 0.78 versus AUC = 0.68 for the expert-selected variables). Predictive models utilizing variables measured at admission can accurately predict PICH, confirmed by the 6-hour follow-up hCT. Our best-performing models must now be externally validated in a separate cohort of TBI patients with low GCS and initial hCT positive for hemorrhage.

Neurological Health in Sexual and Gender Minority Individuals.

Despite representing a significant proportion of the U.S. population, there is a paucity of population-based research on the health status and health needs of sexual and gender minority (SGM) individuals in neurology. Compared with heterosexual peers, some SGM populations have a higher burden of chronic health conditions. In parallel, SGM individuals are more likely to experience stigma and discrimination producing psychological distress, which may contribute to and be compounded by reduced health care access and utilization. In this narrative review, we summarize the existing literature on common neurological health conditions such as stroke, headache, epilepsy, movement disorders, and traumatic brain injury through the lens of intersection of SGM identity. Special focus is attuned to social determinants of health and gender-affirming hormonal therapy. Given the limitations in the available literature, there is an urgent unmet need for datasets that include sexual orientation and gender identity information, as well as funding for research that will characterize the prevalence of neurological conditions, unique risk factors, and health outcomes in SGM populations. In the health care community, providers should address deficiencies in their professional training and integrate inclusive language into their clinical skillset to build trust with SGM patients. There is an opportunity in neurology to proactively engage SGM communities, collaborate to remove barriers to care, promote resilience, and develop targeted interventions to ensure high-quality, culturally competent care for SGM populations to improve neurological health for all.

Common Data Elements for Disorders of Consciousness: Recommendations from the Working Group on Biospecimens and Biomarkers.

BACKGROUND: In patients with disorders of consciousness (DoC), laboratory and molecular biomarkers may help define endotypes, identify therapeutic targets, prognosticate outcomes, and guide patient selection in clinical trials. We performed a systematic review to identify common data elements (CDEs) and key design elements (KDEs) for future coma and DoC research. METHODS: The Curing Coma Campaign Biospecimens and Biomarkers work group, composed of seven invited members, reviewed existing biomarker and biospecimens CDEs and conducted a systematic literature review for laboratory and molecular biomarkers using predetermined search words and standardized methodology. Identified CDEs and KDEs were adjudicated into core, basic, supplemental, or experimental CDEs per National Institutes of Health classification based on level of evidence, reproducibility, and generalizability across different diseases through a consensus process. RESULTS: Among existing National Institutes of Health CDEs, those developed for ischemic stroke, traumatic brain injury, and subarachnoid hemorrhage were most relevant to DoC and included. KDEs were common to all disease states and included biospecimen collection time points, baseline indicator, biological source, anatomical location of collection, collection method, and processing and storage methodology. Additionally, two disease core, nine basic, 24 supplemental, and 59 exploratory biomarker CDEs were identified. Results were summarized and generated into a Laboratory Data and Biospecimens Case Report Form (CRF) and underwent public review. A final CRF version 1.0 is reported here. CONCLUSIONS: Exponential growth in biomarkers development has generated a growing number of potential experimental biomarkers associated with DoC, but few meet the quality, reproducibility, and generalizability criteria to be classified as core and basic biomarker and biospecimen CDEs. Identification and adaptation of KDEs, however, contribute to standardizing methodology to promote harmonization of future biomarker and biospecimens studies in DoC. Development of this CRF serves as a basic building block for future DoC studies.

Blood-Based Biomarkers for Neuroprognostication in Acute Brain Injury.

Acute brain injury causes loss of functionality in patients that often is devastating. Predicting the degree of functional loss and overall prognosis requires a multifaceted approach to help patients, and more so their families, make important decisions regarding plans and goals of care. A variety of blood-based markers have been studied as one aspect of this determination. In this review, we discuss CNS-derived and systemic markers that have been studied for neuroprognostication purposes. We discuss the foundation of each protein, the conditions in which it has been studied, and how the literature has used these markers for interpretation. We also discuss challenges to using each marker in each section as well.

Hypoxanthine is a pharmacodynamic marker of ischemic brain edema modified by glibenclamide.

Brain edema after a large stroke causes significant morbidity and mortality. Here, we seek to identify pharmacodynamic markers of edema that are modified by intravenous (i.v.) glibenclamide (glyburide; BIIB093) treatment. Using metabolomic profiling of 399 plasma samples from patients enrolled in the phase 2 Glyburide Advantage in Malignant Edema and Stroke (GAMES)-RP trial, 152 analytes are measured using liquid chromatography-tandem mass spectrometry. Associations with midline shift (MLS) and the matrix metalloproteinase-9 (MMP-9) level that are further modified by glibenclamide treatment are compared with placebo. Hypoxanthine is the only measured metabolite that associates with MLS and MMP-9. In sensitivity analyses, greater hypoxanthine levels also associate with increased net water uptake (NWU), as measured on serial head computed tomography (CT) scans. Finally, we find that treatment with i.v. glibenclamide reduces plasma hypoxanthine levels across all post-treatment time points. Hypoxanthine, which has been previously linked to inflammation, is a biomarker of brain edema and a treatment response marker of i.v. glibenclamide treatment.

Mass Spectrometry-Based Approaches for Clinical Biomarker Discovery in Traumatic Brain Injury.

Purpose of Review: Precision treatments to address the multifaceted pathophysiology of traumatic brain injury (TBI) are desperately needed, which has led to the intense study of fluid-based protein biomarkers in TBI. Mass Spectrometry (MS) is increasingly being applied to biomarker discovery and quantification in neurological disease to explore the proteome, allowing for more flexibility in biomarker discovery than commonly encountered antibody-based assays. In this narrative review, we will provide specific examples of how MS technology has advanced translational research in traumatic brain injury (TBI) focusing on clinical studies, and looking ahead to promising emerging applications of MS to the field of Neurocritical Care. Recent Findings: Proteomic biomarker discovery using MS technology in human subjects has included the full range of injury severity in TBI, though critically ill patients can offer more options to biofluids given the need for invasive monitoring. Blood, urine, cerebrospinal fluid, brain specimens, and cerebral extracellular fluid have all been sources for analysis. Emerging evidence suggests there are distinct proteomic profiles in radiographic TBI subtypes, and that biomarkers may be used to distinguish patients sustaining TBI from healthy controls. Metabolomics may offer a window into the perturbations of ongoing cerebral insults in critically ill patients after severe TBI. Summary: Emerging MS technologies may offer biomarker discovery and validation opportunities not afforded by conventional means due to its ability to handle the complexities associated with the proteome. While MS techniques are relatively early in development in the neurosciences space, the potential applications to TBI and neurocritical care are likely to accelerate in the coming decade.

Proceedings of the First Curing Coma Campaign NIH Symposium: Challenging the Future of Research for Coma and Disorders of Consciousness.

Coma and disorders of consciousness (DoC) are highly prevalent and constitute a burden for patients, families, and society worldwide. As part of the Curing Coma Campaign, the Neurocritical Care Society partnered with the National Institutes of Health to organize a symposium bringing together experts from all over the world to develop research targets for DoC. The conference was structured along six domains: (1) defining endotype/phenotypes, (2) biomarkers, (3) proof-of-concept clinical trials, (4) neuroprognostication, (5) long-term recovery, and (6) large datasets. This proceedings paper presents actionable research targets based on the presentations and discussions that occurred at the conference. We summarize the background, main research gaps, overall goals, the panel discussion of the approach, limitations and challenges, and deliverables that were identified.

Antibody-Free Mass Spectrometry Identification of Vascular Integrity Markers in Major Trauma.

Antibody mediated strategies for protein biomarker detection are common, but may limit discovery. We hypothesized that the use of antibody-free proteomics is feasible for detecting protein biomarkers in plasma of patients sustaining major trauma. A subset of subjects with major trauma from a prospective observational trial were analyzed. Patients were assigned to one of four groups based on their presenting Abbreviated Injury Severity Score (AIS). Sensitive, antibody-free selective reaction monitoring (SRM) mass spectrometry (MS), with spiked-in isotopically labeled synthetic peptides, was used for targeted protein quantification of a panel of 10 prospective targets. An overall tiered sensitivity analytical approach was used for peptide detection and quantification based upon plasma immunoaffinity depletion and PRISM fractionation. Forty-four patients were included in the analysis, of which 82% were men with a mean age of 50 (±19) years. Half had isolated head injury (n = 22), with the remaining patients experiencing multiple injuries or polytrauma (n = 14), isolated body injury (n = 2), or minor injury (n = 6). Peptides from 3 proteins (vascular adhesion molecule 1 [VCAM1], intercellular adhesion molecule 1 [ICAM1], and matrix metalloproteinase 9 [MMP9]) were detected and quantified in non-depleted processed plasma. Peptides from 2 proteins (angiopoietin 2 [Ang2] and plasminogen activator inhibitor-1 [PAI1]) were detected and quantification in depleted plasma, whereas the remaining 5 of the 10 prospective targets were undetected. VCAM1 (p = 0.02) and MMP9 (p = 0.03) were significantly upregulated in in the major trauma groups (1-3) versus mild injury group (4), whereas the others were not. There were no differences in protein expression between patients with traumatic brain injury (TBI; groups 1 and 2) versus those without TBI (groups 3 and 4). We detected non-specific upregulation of proteins reflecting blood-brain barrier breakdown in severely injured patients, indicating label-free MS techniques are feasible and may be informative.

Assistance from Automated ASPECTS Software Improves Reader Performance.

PURPOSE: To compare physicians' ability to read Alberta Stroke Program Early CT Score (ASPECTS) in patients with a large vessel occlusion within 6 hours of symptom onset when assisted by a machine learning-based automatic software tool, compared with their unassisted score. MATERIALS AND METHODS: 50 baseline CT scans selected from two prior studies (CRISP and GAMES-RP) were read by 3 experienced neuroradiologists who were provided access to a follow-up MRI. The average ASPECT score of these reads was used as the reference standard. Two additional neuroradiologists and 6 non-neuroradiologist readers then read the scans both with and without assistance from the software reader-augmentation program and reader improvement was determined. The primary hypothesis was that the agreement between typical readers and the consensus of 3 expert neuroradiologists would be improved with software augmented vs. unassisted reads. Agreement was based on the percentage of the individual ASPECT regions (50 cases, 10 regions each; N=500) where agreement was achieved. RESULTS: Typical non-neuroradiologist readers agreed with the expert consensus read in 72% of the 500 ASPECTS regions, evaluated without software assistance. The automated software alone agreed in 77%. When the typical readers read the scan in conjunction with the software, agreement improved to 78% (P<0.0001, test of proportions). The software program alone achieved correlations for total ASPECT scores that were similar to the expert readers who had access to the follow-up MRI scan to help enhance the quality of their reads. CONCLUSION: Typical readers had statistically significant improvement in their scoring of scans when the scan was read in conjunction with the automated software, achieving agreement rates that were comparable to neuroradiologists.

Incorporating Immunoproteins in the Development of Classification Models of Progression of Intracranial Hemorrhage After Traumatic Brain Injury.

OBJECTIVE: To define clinical, radiographic, and blood-based biomarker features to be incorporated into a classification model of progression of intracranial hemorrhage (PICH), and to provide a pilot assessment of those models. METHODS: Patients with hemorrhage on admission head computed tomography were identified from a prospectively enrolled cohort of subjects with traumatic brain injury. Initial and follow-up images were interpreted both by 2 independent readers, and disagreements adjudicated. Admission plasma samples were analyzed and principal components (PCs) composed of the immune proteins (IPs) significantly associated with the outcome of interest were selected for further evaluation. A series of logistic regression models were constructed based on (1) clinical variables (CV) and (2) clinical variables + immune proteins (CV+IP). Error rates of these models for correct classification of PICH were estimated; significance was set at P < .05. RESULTS: We identified 106 patients, 36% had PICH. Dichotomized admission Glasgow Coma Scale (P = .004), Marshall score (P = .004), and 3 PCs were significantly associated with PICH. For the CV only model, sensitivity was 1.0 and specificity was 0.29 (95% CI, 0.07-0.67). The CV+IP model performed significantly better, with a sensitivity of 0.93 (95% CI, 0.64-0.99) and a specificity of 1.0 (P = .008). Adjustments to refine the definition of PICH and better define radiographic predictors of PICH did not significantly improve the models' performance. CONCLUSIONS: In this pilot investigation, we observed that composites of IPs may improve PICH classification models when combined with CVs. However, overall model performance must be further optimized; results will inform feature inclusion included in follow-up models.

Osmotherapy for malignant cerebral edema in a phase 2 prospective, double blind, randomized, placebo-controlled study of IV glibenclamide.

BACKGROUND/OBJECTIVE: Malignant edema can be a life-threatening complication of large hemispheric infarction (LHI), and is often treated with osmotherapy. In this exploratory analysis of data from the GAMES-RP study, we hypothesized that patients receiving osmotherapy had symptomatic cerebral edema, and that treatment with intravenous (IV) glibenclamide would modify osmotherapy use as compared with placebo. METHODS: GAMES-RP was a phase 2 multi-center prospective, double blind, randomized, placebo-controlled study in LHI. Patients were randomized to IV glibenclamide (e.g. IV glyburide) or placebo. Cerebral edema therapies included osmotherapy and/or decompressive craniectomy at the discretion of the treating team. Total bolus osmotherapy dosing was quantified by "osmolar load". Radiographic edema was defined by dichotomizing midline shift at 24 h. Clinical changes were defined as any increase in NIHSS1a. RESULTS: Osmotherapy was administered to 40 of the 77 patients at a median of 39 [27-55] h after stroke onset. The median baseline DWI lesion volume was significantly larger in the osmotherapy treated group (167 [146-211] mL v. 139 [112-170] mL; P=0.046). Adjudicated malignant edema (75% v. 16%; P<0.001) was more common in the osmotherapy treated group. There were no differences in the proportion of patients receiving osmotherapy or the median total osmolar load between treatment arms. Most patients (76%) had a decrease in consciousness (NIHSS item 1A ≥1) on the day they began receiving osmotherapy. CONCLUSIONS: In the GAMES-RP trial, osmolar therapies were most often administered in response to clinical symptoms of decreased consciousness. However, the optimal timing of administration and impact on outcome after LHI have yet to be defined.

Effect of formulation and inhaler parameters on the dispersion of spray freeze dried voriconazole particles.

Spray freeze drying is a particle engineering technique that allows the production of porous particles of low density with excellent aerosol performance for inhalation. There are a number of operating parameters that can be manipulated in order to optimise the powder properties. In this study, a two-fluid nozzle was used to prepare spray freeze dried formulation of voriconazole, a triazole antifungal agent for the treatment of pulmonary aspergillosis. A full factorial design approach was adopted to explore the effects of drug concentration, atomisation gas flow rate and primary drying temperature. The aerosol performance of the spray freeze dried powder was evaluated using the next generation impactor (NGI) operated with different inhaler devices and flow rates. The results showed that the primary drying temperature played an important role in determining the aerosol properties of the powder. In general, the higher the primary drying temperature, the lower the emitted fraction (EF) and the higher the fine particle fraction (FPF). Formulations that contained the highest voriconazole concentration (80% w/w) and prepared at a high primary drying temperature (-10 °C) exhibited the best aerosol performance under different experimental conditions. The high concentration of the hydrophobic voriconazole reduced surface energy and cohesion, hence better powder dispersibility. The powders produced with higher primary drying temperature had a smaller particle size after dispersion and improved aerosol property, possibly due to the faster sublimation rate in the freeze-drying step that led to the formation of less aggregating or more fragile particles. Moreover, Breezhaler®, which has a low intrinsic resistance, was able to generate the best aerosol performance of the spray freeze dried voriconazole powders in terms of FPF.

Inhaled powder formulation of naked siRNA using spray drying technology with l-leucine as dispersion enhancer.

Pulmonary delivery of short interfering RNA (siRNA) has been widely studied in both animal and clinical studies to treat various respiratory diseases by gene silencing through RNA interference. Some of these studies showed that the administration of naked siRNA (without the use of any delivery vectors) could achieve satisfactory gene silencing effect, a unique feature to pulmonary delivery. Liquid aerosols were mostly used with very limited studies on the use of powder aerosols for siRNA. In this study, siRNA was co-spray dried with mannitol and l-leucine, the latter being a dispersion enhancer. To the best of our knowledge, this is the first time that siRNA in its naked form was formulated into an inhalable dry powder using spray drying technology. The aerosol performance of the powder was evaluated by Next Generation Impactor (NGI). The presence of l-leucine in the formulation could improve the aerosolization of siRNA-containing powders. Results from the X-ray photoelectron spectroscopy (XPS) suggested that l-leucine was enriched on the particle surface and promote powder dispersion. Among the different siRNA formulations being examined, the one that contained 50% w/w of l-leucine exhibited the best aerodynamic performance, with a high emitted fraction (EF) of around 80% and a modest fine particle fraction (FPF) of 45%. Importantly, the integrity of siRNA was successfully retained as evaluated by gel retardation assay and high performance liquid chromatography (HPLC).