A Distinct Metabolite Signature in Military Personnel Exposed to Repetitive Low-Level Blasts

Military Breachers and Range Staff (MBRS) are subjected to repeated sub-concussive blasts, and they often report symptoms that are consistent with a mild traumatic brain injury (mTBI). Biomarkers of blast injury would potentially aid blast injury diagnosis, surveillance and avoidance. Our objective was to identify plasma metabolite biomarkers in military personnel that were exposed to repeated low-level or sub-concussive blast overpressure. A total of 37 military members were enrolled (18 MBRS and 19 controls), with MBRS having participated in 8–20 breaching courses per year, with a maximum exposure of 6 blasts per day. The two cohorts were similar except that the number of blast exposures were significantly higher in the MBRS, and the MBRS cohort suffered significantly more post-concussive symptoms and poorer health on assessment. Metabolomics profiling demonstrated significant differences between groups with 74% MBRS classification accuracy (CA). Feature reduction identified 6 metabolites that resulted in a MBRS CA of 98%, and included acetic acid (23.7%), formate (22.6%), creatine (14.8%), acetone (14.2%), methanol (12,7%), and glutamic acid (12.0%). All 6 metabolites were examined with individual receiver operating characteristic (ROC) curve analyses and demonstrated areas-under-the-curve (AUCs) of 0.82–0.91 (P ≤ 0.001) for MBRS status. Several parsimonious combinations of three metabolites increased accuracy of ROC curve analyses to AUCs of 1.00 (P < 0.001), while a combination of volatile organic compounds (VOCs; acetic acid, acetone and methanol) yielded an AUC of 0.98 (P < 0.001). Candidate biomarkers for chronic blast exposure were identified, and if validated in a larger cohort, may aid surveillance and care of military personnel. Future point-of-care screening could be developed that measures VOCs from breath, with definitive diagnoses confirmed with plasma metabolomics profiling.

Pediatric severe traumatic brain injury mortality prediction determined with machine learning-based modeling

INTRODUCTION

Severe traumatic brain injury (sTBI) is a leading cause of mortality in children. As clinical prognostication is important in guiding optimal care and decision making, our goal was to create a highly discriminative sTBI outcome prediction model for mortality.

METHODS

Machine learning and advanced analytics were applied to the patient admission variables obtained from a comprehensive pediatric sTBI database. Demographic and clinical data, head CT imaging abnormalities and blood biochemical data from 196 children and adolescents admitted to a tertiary pediatric intensive care unit (PICU) with sTBI were integrated using feature ranking by way of a forest of randomized decision trees, and a model was generated from a reduced number of admission variables with maximal ability to discriminate outcome.

RESULTS

In total, 36 admission variables were analyzed using feature ranking with variable weighting to determine their predictive importance for mortality following sTBI. Reduction analysis utilizing Borata feature selection resulted in a parsimonious six-variable model with a mortality classification accuracy of 82%. The final admission variables that predicted mortality were: partial thromboplastin time (22%); motor Glasgow Coma Scale (21%); serum glucose (16%); fixed pupil(s) (16%); platelet count (13%) and creatinine (12%). Using only these six admission variables, a t-distributed stochastic nearest neighbor embedding algorithm plot demonstrated visual separation of sTBI patients that lived or died, with high mortality predictive ability of this model on the validation dataset (AUC = 0.90) which was confirmed with a conventional area-under-the-curve statistical approach on the total dataset (AUC = 0.91; P < 0.001).

CONCLUSIONS

Machine learning-based modeling identified the most clinically important prognostic factors resulting in a pragmatic, high performing prognostic tool for pediatric sTBI with excellent discriminative ability to predict mortality risk with 82% classification accuracy (AUC = 0.90). After external multicenter validation, our prognostic model might help to guide treatment decisions, aggressiveness of therapy and prepare family members and caregivers for timely end-of-life discussions and decision making.

LEVEL OF EVIDENCE

III; Prognostic.

Putative Concussion Biomarkers Identified in Adolescent Male Athletes Using Targeted Plasma Proteomics

Sport concussions can be difficult to diagnose and if missed, they can expose athletes to greater injury risk and long-lasting neurological disabilities. Discovery of objective biomarkers to aid concussion diagnosis is critical to protecting athlete brain health. To this end, we performed targeted proteomics on plasma obtained from adolescent athletes suffering a sports concussion. A total of 11 concussed male athletes were enrolled at our academic Sport Medicine Concussion Clinic, as well as 24 sex-, age- and activity-matched healthy control subjects. Clinical evaluation was performed and blood was drawn within 72 h of injury. Proximity extension assays were performed for 1,472 plasma proteins; a total of six proteins were considered significantly different between cohorts (P < 0.01; five proteins decreased and one protein increased). Receiver operating characteristic curves on the six individual protein biomarkers identified had areas-under-the-curves (AUCs) for concussion diagnosis ≥0.78; antioxidant 1 copper chaperone (ATOX1; AUC 0.81, P = 0.003), secreted protein acidic and rich in cysteine (SPARC; AUC 0.81, P = 0.004), cluster of differentiation 34 (CD34; AUC 0.79, P = 0.006), polyglutamine binding protein 1 (PQBP1; AUC 0.78, P = 0.008), insulin-like growth factor-binding protein-like 1 (IGFBPL1; AUC 0.78, P = 0.008) and cytosolic 5'-nucleotidase 3A (NT5C3A; AUC 0.78, P = 0.009). Combining three of the protein biomarkers (ATOX1, SPARC and NT5C3A), produced an AUC of 0.98 for concussion diagnoses (P < 0.001; 95% CI: 0.95, 1.00). Despite a paucity of studies on these three identified proteins, the available evidence points to their roles in modulating tissue inflammation and regulating integrity of the cerebral microvasculature. Taken together, our exploratory data suggest that three or less novel proteins, which are amenable to a point-of-care immunoassay, may be future candidate biomarkers for screening adolescent sport concussion. Validation with protein assays is required in larger cohorts.

Magnetic Resonance Imaging Findings Are Associated with Long-Term Global Neurological Function or Death after Traumatic Brain Injury in Critically Ill Children

The identification of children with traumatic brain injury (TBI) who are at risk of death or poor global neurological functional outcome remains a challenge. Magnetic resonance imaging (MRI) can detect several brain pathologies that are a result of TBI; however, the types and locations of pathology that are the most predictive remain to be determined. Forty-two critically ill children with TBI were recruited prospectively from pediatric intensive care units at five Canadian children's hospitals. Pathologies detected on subacute phase MRIs included cerebral hematoma, herniation, cerebral laceration, cerebral edema, midline shift, and the presence and location of cerebral contusion or diffuse axonal injury (DAI) in 28 regions of interest were assessed. Global functional outcome or death more than 12 months post-injury was assessed using the Pediatric Cerebral Performance Category score. Linear modeling was employed to evaluate the utility of an MRI composite score for predicting long-term global neurological function or death after injury, and nonlinear Random Forest modeling was used to identify which MRI features have the most predictive utility. A linear predictive model of favorable versus unfavorable long-term outcomes was significantly improved when an MRI composite score was added to clinical variables. Nonlinear Random Forest modeling identified five MRI variables as stable predictors of poor outcomes: presence of herniation, DAI in the parietal lobe, DAI in the subcortical white matter, DAI in the posterior corpus callosum, and cerebral contusion in the anterior temporal lobe. Clinical MRI has prognostic value to identify children with TBI at risk of long-term unfavorable outcomes.

Proteinase 3 contributes to endothelial dysfunction in an experimental model of sepsis

In sepsis-induced inflammation, polymorphonuclear neutrophils (PMNs) contribute to vascular dysfunction. The serine proteases proteinase 3 (PR3) and human leukocyte elastase (HLE) are abundant in PMNs and are released upon degranulation. While HLE's role in inflammation-induced endothelial dysfunction is well studied, PR3's role is largely uninvestigated. We hypothesized that PR3, similarly to HLE, contributes to vascular barrier dysfunction in sepsis. Plasma PR3 and HLE concentrations and their leukocyte mRNA levels were measured by ELISA and qPCR, respectively, in sepsis patients and controls. Exogenous PR3 or HLE was applied to human umbilical vein endothelial cells (HUVECs) and HUVEC dysfunction was assessed by FITC-dextran permeability and electrical resistance. Both PR3 and HLE protein and mRNA levels were significantly increased in sepsis patients (P < 0.0001 and P < 0.05, respectively). Additionally, each enzyme independently increased HUVEC monolayer FITC-dextran permeability (P < 0.01), and decreased electrical resistance in a time- and dose-dependent manner (P < 0.001), an effect that could be ameliorated by novel treatment with carbon monoxide-releasing molecule 3 (CORM-3). The serine protease PR3, in addition to HLE, lead to vascular dysfunction and increased endothelial permeability, a hallmark pathological consequence of sepsis-induced inflammation. CORMs may offer a new strategy to reduce serine protease-induced vascular dysfunction.

Epitope-specific antibody responses differentiate COVID-19 outcomes and variants of concern

BACKGROUNDThe role of humoral immunity in COVID-19 is not fully understood, owing, in large part, to the complexity of antibodies produced in response to the SARS-CoV-2 infection. There is a pressing need for serology tests to assess patient-specific antibody response and predict clinical outcome.METHODSUsing SARS-CoV-2 proteome and peptide microarrays, we screened 146 COVID-19 patients' plasma samples to identify antigens and epitopes. This enabled us to develop a master epitope array and an epitope-specific agglutination assay to gauge antibody responses systematically and with high resolution.RESULTSWe identified linear epitopes from the spike (S) and nucleocapsid (N) proteins and showed that the epitopes enabled higher resolution antibody profiling than the S or N protein antigen. Specifically, we found that antibody responses to the S-811-825, S-881-895, and N-156-170 epitopes negatively or positively correlated with clinical severity or patient survival. Moreover, we found that the P681H and S235F mutations associated with the coronavirus variant of concern B.1.1.7 altered the specificity of the corresponding epitopes.CONCLUSIONEpitope-resolved antibody testing not only affords a high-resolution alternative to conventional immunoassays to delineate the complex humoral immunity to SARS-CoV-2 and differentiate between neutralizing and non-neutralizing antibodies, but it also may potentially be used to predict clinical outcome. The epitope peptides can be readily modified to detect antibodies against variants of concern in both the peptide array and latex agglutination formats.FUNDINGOntario Research Fund (ORF) COVID-19 Rapid Research Fund, Toronto COVID-19 Action Fund, Western University, Lawson Health Research Institute, London Health Sciences Foundation, and Academic Medical Organization of Southwestern Ontario (AMOSO) Innovation Fund.

A Proteinase 3 Contribution to Juvenile Idiopathic Arthritis-Associated Cartilage Damage

A full understanding of the molecular mechanisms implicated in the etiopathogenesis of juvenile idiopathic arthritis (JIA) is lacking. A critical role for leukocyte proteolytic activity (e.g., elastase and cathepsin G) has been proposed. While leukocyte elastase’s (HLE) role has been documented, the potential contribution of proteinase 3 (PR3), a serine protease present in abundance in neutrophils, has not been evaluated. In this study we investigated: (1) PR3 concentrations in the synovial fluid of JIA patients using ELISA and (2) the cartilage degradation potential of PR3 by measuring the hydrolysis of fluorescently labeled collagen II in vitro. In parallel, concentrations and collagen II hydrolysis by HLE were assessed. Additionally, the levels of the co-secreted primary granule protein myeloperoxidase (MPO) were assessed in synovial fluid of patients diagnosed with JIA. We report the following levels of analytes in JIA synovial fluid: PR3—114 ± 100 ng/mL (mean ± SD), HLE—1272 ± 1219 ng/mL, and MPO—1129 ± 1659 ng/mL, with a very strong correlation between the PR3 and HLE concentrations (r_s = 0.898, p < 1 × 10^–6). Importantly, PR3 hydrolyzed fluorescently labeled collagen II as efficiently as HLE. Taken together, these novel findings suggest that PR3 (in addition to HLE) contributes to JIA-associated joint damage.

Novel severe traumatic brain injury blood outcome biomarkers identified with proximity extension assay

OBJECTIVES

Severe traumatic brain injury (sTBI) patients suffer high mortality. Accurate prognostic biomarkers have not been identified. In this exploratory study, we performed targeted proteomics on plasma obtained from sTBI patients to identify potential outcome biomarkers.

METHODS

Blood sample was collected from patients admitted to the ICU suffering a sTBI, using standardized clinical and computerized tomography (CT) imaging criteria. Age- and sex-matched healthy control subjects and sTBI patients were enrolled. Targeted proteomics was performed on plasma with proximity extension assays (1,161 proteins).

RESULTS

Cohorts were well-balanced for age and sex. The majority of sTBI patients were injured in motor vehicle collisions and the most frequent head CT finding was subarachnoid hemorrhage. Mortality rate for sTBI patients was 40%. Feature selection identified the top performing 15 proteins for identifying sTBI patients from healthy control subjects with a classification accuracy of 100%. The sTBI proteome was dominated by markers of vascular pathology, immunity/inflammation, cell survival and macrophage/microglia activation. Receiver operating characteristic (ROC) curve analyses demonstrated areas-under-the-curves (AUC) for identifying sTBI that ranged from 0.870-1.000 (p≤0.005). When mortality was used as outcome, ROC curve analyses identified the top 3 proteins as Willebrand factor (vWF), Wnt inhibitory factor-1 (WIF-1), and colony stimulating factor-1 (CSF-1). Combining vWF with either WIF-1 or CSF-1 resulted in excellent mortality prediction with AUC of 1.000 for both combinations (p=0.011).

CONCLUSIONS

Targeted proteomics with feature classification and selection distinguished sTBI patients from matched healthy control subjects. Two protein combinations were identified that accurately predicted sTBI patient mortality. Our exploratory findings require confirmation in larger sTBI patient populations.

Biomarkers of coagulation, endothelial function, and fibrinolysis in critically ill patients with COVID-19: A single-center prospective longitudinal study

BACKGROUND

Immunothrombosis and coagulopathy in the lung microvasculature may lead to lung injury and disease progression in coronavirus disease 2019 (COVID-19). We aim to identify biomarkers of coagulation, endothelial function, and fibrinolysis that are associated with disease severity and may have prognostic potential.

METHODS

We performed a single-center prospective study of 14 adult COVID-19(+) intensive care unit patients who were age- and sex-matched to 14 COVID-19(-) intensive care unit patients, and healthy controls. Daily blood draws, clinical data, and patient characteristics were collected. Baseline values for 10 biomarkers of interest were compared between the three groups, and visualized using Fisher's linear discriminant function. Linear repeated-measures mixed models were used to screen biomarkers for associations with mortality. Selected biomarkers were further explored and entered into an unsupervised longitudinal clustering machine learning algorithm to identify trends and targets that may be used for future predictive modelling efforts.

RESULTS

Elevated D-dimer was the strongest contributor in distinguishing COVID-19 status; however, D-dimer was not associated with survival. Variable selection identified clot lysis time, and antigen levels of soluble thrombomodulin (sTM), plasminogen activator inhibitor-1 (PAI-1), and plasminogen as biomarkers associated with death. Longitudinal multivariate k-means clustering on these biomarkers alone identified two clusters of COVID-19(+) patients: low (30%) and high (100%) mortality groups. Biomarker trajectories that characterized the high mortality cluster were higher clot lysis times (inhibited fibrinolysis), higher sTM and PAI-1 levels, and lower plasminogen levels.

CONCLUSIONS

Longitudinal trajectories of clot lysis time, sTM, PAI-1, and plasminogen may have predictive ability for mortality in COVID-19.

Proceedings From the Ice Hockey Summit III: Action on Concussion

OBJECTIVES

The Ice Hockey Summit III provided updated scientific evidence on concussions in hockey to inform these 5 objectives: (1) describe sport related concussion (SRC) epidemiology; (2) classify prevention strategies; (3) define objective, diagnostic tests; (4) identify treatment; and (5) integrate science and clinical care into prioritized action plans and policy.

METHODS

Our action plan evolved from 40 scientific presentations. The 155 attendees (physicians, athletic trainers, physical therapists, nurses, neuropsychologists, scientists, engineers, coaches, and officials) voted to prioritize these action items in the final Summit session.

RESULTS

To (1) establish a national and international hockey database for SRCs at all levels; (2) eliminate body checking in Bantam youth hockey games; (3) expand a behavior modification program (Fair Play) to all youth hockey levels; (4) enforce game ejection penalties for fighting in Junior A and professional hockey leagues; (5) establish objective tests to diagnose concussion at point of care; and (6) mandate baseline testing to improve concussion diagnosis for all age groups.

CONCLUSIONS

Expedient implementation of the Summit III prioritized action items is necessary to reduce the risk, severity, and consequences of concussion in the sport of ice hockey.

Autonomic Dysregulation in Adolescent Concussion Is Sex- and Posture-Dependent

OBJECTIVE

To study autonomic responses to postural changes in concussed adolescents. The influence of sex was also studied.

DESIGN

Longitudinal cohort observational study.

PARTICIPANTS

Concussed adolescents (CONC; n = 65; 26 male adolescents; age 15 ± 1 years, range = 12-18 years) and a control (CTRL) group of nonconcussed adolescents of similar age and sport (CTRL; n = 54; 29 male adolescents; age 14 ± 1 years, range = 12-18 years).

INTERVENTIONS

Concussed participants were monitored through 6 weekly visits throughout usual physician care. Control participants underwent 2 visits separated by at least 1 week to account for intrapersonal variation in testing measures.

MAIN OUTCOME MEASURES

Heart rate variability as the root mean square of successive differences in R-R intervals (RMSSD), heart rate (HR), and blood pressure [mean arterial pressure (MAP) and diastolic blood pressure (DBP)] were measured in supine, sitting, and standing postures.

RESULTS

A mixed analysis of variance revealed a group × sex × posture interaction (P = 0.04) where seated values of RMSSD were less in concussed female participants versus control female participants (42 ± 4 vs 61 ± 7 ms; P = 0.01; Mann-Whitney rank test). Compared with CTRL, CONC exhibited increased pretesting seated DBP (69 ± 1 vs 74 ± 1 mm Hg; P < 0.01), MAP (83 ± 1 vs 86 ± 1 mm Hg; P = 0.02), and baseline seated HR (72 ± 1 vs 77 ± 2 bpm; P = 0.03). Values of DBP (P = 0.03) and MAP (P < 0.01) improved at clinical discharge, whereas the RMSSD in female participants did not (P > 0.5). Data are mean ± SEM.

CONCLUSIONS

A modest reduction in female cardiac autonomic regulation was observed during seated postures. Alterations in seated concussed DBP and MAP, but not RMSSD, resolved at clinical discharge (median = 37 days). The results indicate that, in adolescents, concussion may impair cardiovagal function in a sex- and posture-dependent manner. The findings also suggest that BP metrics, but not RMSSD, are associated with clinical concussion recovery.

Plasma Protein Profiling by Proximity Extension Assay Technology Reveals Novel Biomarkers of Traumatic Brain Injury-A Pilot Study

BACKGROUND

Traumatic brain injury (TBI) is a significant public health issue affecting nearly 69 million patients worldwide per year. Reliable diagnostic biomarkers are urgently needed to aid in disease diagnosis and prognosis and to guide patient aftercare. Blood biomarkers represent an attractive modality to quickly, cheaply, and objectively evaluate clinical status. We hypothesize that deep and quantitative plasma proteomic profiling with a novel technology, proximity extension assay, may lead to the discovery of diagnostic and/or prognostic biomarkers of TBI.

METHODS

We used high-throughput proximity extension assays (PEA) to quantify the relative abundance of over 1000 unique proteins in plasma. PEA is a highly sensitive multiplex immunoassay capable of detecting very low-abundance proteins (down to fg/mL) in complex biological matrices. Our patient cohort consisted of severe TBI (sTBI) patients, matched healthy controls, and another non-TBI group that was included in the analysis to validate the specificity of the candidates during the selection process. The obtained protein quantification data was then filtered to identify candidate biomarkers through statistical analysis, literature searches, and comparison to our reference control groups.

RESULTS

Overall, we identified 6 novel candidate TBI biomarkers. Candidates exhibit a significant increase in plasma protein abundance in sTBI when comparing between healthy controls and sTBI patients. Candidates generally had low expression in our reference groups compared with the sTBI group.

CONCLUSIONS

Our preliminary findings represent a starting point for future validation. These biomarkers, either alone or in combination, may have significant clinical utility in aiding in TBI diagnosis, prognosis, and/or management.

Detection and Profiling of Human Coronavirus Immunoglobulins in Critically Ill Coronavirus Disease 2019 Patients

OBJECTIVES

Coronavirus disease 2019 continues to spread worldwide with high levels of morbidity and mortality. We performed anticoronavirus immunoglobulin G profiling of critically ill coronavirus disease 2019 patients to better define their underlying humoral response.

DESIGN

Blood was collected at predetermined ICU days to measure immunoglobulin G with a research multiplex assay against four severe acute respiratory syndrome coronavirus 2 proteins/subunits and against all six additionally known human coronaviruses.

SETTING

Tertiary care ICU and academic laboratory.

SUBJECTS

ICU patients suspected of being infected with severe acute respiratory syndrome coronavirus 2 had blood collected until either polymerase chain reaction testing was confirmed negative on ICU day 3 (coronavirus disease 2019 negative) or until death or discharge if the patient tested polymerase chain reaction positive (coronavirus disease 2019 positive).

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Age- and sex-matched healthy controls and ICU patients who were either coronavirus disease 2019 positive or coronavirus disease 2019 negative were enrolled. Cohorts were well-balanced with the exception that coronavirus disease 2019 positive patients had greater body mass indexes, presented with bilateral pneumonias more frequently, and suffered lower Pao2:Fio2 ratios, when compared with coronavirus disease 2019 negative patients (p < 0.05). Mortality rate for coronavirus disease 2019 positive patients was 50%. On ICU days 1-3, anti-severe acute respiratory syndrome coronavirus 2 immunoglobulin G was significantly elevated in coronavirus disease 2019 positive patients, as compared to both healthy control subjects and coronavirus disease 2019 negative patients (p < 0.001). Weak severe acute respiratory syndrome coronavirus immunoglobulin G serologic responses were also detected, but not other coronavirus subtypes. The four anti-severe acute respiratory syndrome coronavirus 2 immunoglobulin G were maximal by ICU day 3, with all four anti-severe acute respiratory syndrome coronavirus 2 immunoglobulin G providing excellent diagnostic potential (severe acute respiratory syndrome coronavirus 2 Spike 1 protein immunoglobulin G, area under the curve 1.0, p < 0.0005; severe acute respiratory syndrome coronavirus receptor binding domain immunoglobulin G, area under the curve, 0.93-1.0; p ≤ 0.0001; severe acute respiratory syndrome coronavirus 2 Spike proteins immunoglobulin G, area under the curve, 1.0; p < 0.0001; severe acute respiratory syndrome coronavirus 2 Nucleocapsid protein immunoglobulin G area under the curve, 0.90-0.95; p ≤ 0.0003). Anti-severe acute respiratory syndrome coronavirus 2 immunoglobulin G increased and/or plateaued over 10 ICU days.

CONCLUSIONS

Critically ill coronavirus disease 2019 patients exhibited anti-severe acute respiratory syndrome coronavirus 2 immunoglobulin G, whereas serologic responses to non-severe acute respiratory syndrome coronavirus 2 antigens were weak or absent. Detection of human coronavirus immunoglobulin G against the different immunogenic structural proteins/subunits with multiplex assays may be useful for pathogen identification, patient cohorting, and guiding convalescent plasma therapy.

Evaluation of a population health strategy to reduce distracted driving: Examining all "Es" of injury prevention

BACKGROUND

Cell phone use while driving (CPWD) increases the risk of crashing and is a major contributor to injuries and deaths. The objective of this study was to describe the evaluation of a multifaceted, evidence-based population health strategy for the reduction of distracted driving.

METHODS

A multipronged campaign was undertaken from 2014 to 2016 for 16- to 44-year-olds, based on epidemiology, focused on personal stories and consequences, using the "Es" of injury prevention (epidemiology, education, environment, enforcement, and evaluation). Education consisted of distracted driving videos, informational cards, a social media AdTube campaign, and a movie theater trailer, which were evaluated with a questionnaire regarding CPWD attitudes, opinions, and behaviors. Spatial analysis of data within a geographic information system was used to target advertisements. A random sample telephone survey evaluated public awareness of the campaign. Increased CPWD enforcement was undertaken by police services and evaluated by ARIMA time series modeling.

RESULTS

The AdTube campaign had a view rate of >10% (41,101 views), slightly higher for females. The top performing age group was 18- to 24-year-olds (49%). Our survey found 61% of respondents used handheld CPWD (14% all of the time) with 80% reporting our movie trailer made them think twice about future CPWD. A stakeholder survey and spatial analysis targeted our advertisements in areas of close proximity to high schools, universities, near intersections with previous motor vehicle collisions, high traffic volumes, and population density. A telephone survey revealed that 41% of the respondents were aware of our campaign, 17% from our print and movie theater ads and 3% from social media. Police enforcement campaign blitzes resulted in 160 tickets for CPWD. Following campaign implementation, there was a statistically significant mean decrease of 462 distracted driving citations annually (p = 0.001).

CONCLUSION

A multifaceted, evidence-based population health strategy using the Es of injury prevention with interdisciplinary collaboration is a comprehensive method to be used for the reduction of distracted driving.

LEVEL OF EVIDENCE

Therapeutic, level IV.

Development of a Mortality Prediction Tool in Pediatric Severe Traumatic Brain Injury

Severe traumatic brain injury (sTBI) is a leading cause of pediatric death, yet outcomes remain difficult to predict. The goal of this study was to develop a predictive mortality tool in pediatric sTBI. We retrospectively analyzed 196 patients with sTBI (pre-sedation Glasgow Coma Scale [GCS] score <8 and head Maximum Abbreviated Injury Scale (MAIS) score >4) admitted to a pediatric intensive care unit (PICU). Overall, 56 patients with sTBI (29%) died during PICU stay. Of the survivors, 88 (63%) were discharged home, and 52 (37%) went to an acute care or rehabilitation facility. Receiver operating characteristic (ROC) curve analyses of admission variables showed that pre-sedation GCS score, Rotterdam computed tomography (CT) score, and partial thromboplastin time (PTT) were fair predictors of PICU mortality (area under the curve [AUC] = 0.79, 0.76, and 0.75, respectively; p < 0.001). Cutoff values best associated with PICU mortality were pre-sedation GCS score <5 (sensitivity = 0.91, specificity = 0.54), Rotterdam CT score >3 (sensitivity = 0.84, specificity = 0.53), and PTT >34.5 sec (sensitivity = 0.69 specificity = 0.67). Combining pre-sedation GCS score, Rotterdam CT score, and PTT in ROC curve analysis yielded an excellent predictor of PICU mortality (AUC = 0.91). In summary, pre-sedation GCS score (<5), Rotterdam CT score (>3), and PTT (>34.5 sec) obtained on hospital admission were fair predictors of PICU mortality, ranked highest to lowest. Combining these three admission variables resulted in an excellent pediatric sTBI mortality prediction tool for further prospective validation.

Concussion Acutely Decreases Plasma Glycerophospholipids in Adolescent Male Athletes

Concussions are frequent in sports and can contribute to significant and long-lasting neurological disability. Adolescents are particularly susceptible to concussions, with accurate determination of the injury challenging. Our previous study demonstrated that concussion diagnoses could be aided by metabolomics profiling and machine learning, with particular weighting on changes in plasma glycerophospholipids (PCs). Here, our aim was to report directional change of PCs after concussion and develop a diagnostic concussion panel utilizing a minimum number of plasma PCs. To this end, we enrolled 12 concussed male athletes at our academic Sport Medicine Concussion Clinic, as well as 17 sex-, age-, and activity-matched healthy controls. Blood was drawn and 71 plasma PCs were measured for statistically significant changes within 72 h of injury, and individual PCs were further analyzed with receiver operating characteristic (ROC) curves. Our data demonstrated that 26 of 71 PCs measured were significantly decreased after sports-related concussion (p < 0.01). None of the PCs increased in plasma after concussion. ROC curve analyses identified the top four PCs with areas under the curve (AUCs) ≥0.86 for concussion diagnosis: PCaeC36:0 (0.92; p < 0.001); PCaaC42:6 (0.90; p < 0.001); PCaeC36:2 (0.86; p = 0.001), and PCaaC32:0 (0.86; p = 0.001). Cut-off values in μM were ≤0.31, 0.22, 5.07, and 4.63, respectively. Importantly, combining these four PCs produced an AUC of 0.96 for concussion diagnoses (p < 0.001; 95% confidence interval, 0.89, 1.00). Our data suggest that as few as four circulating PCs may provide excellent diagnostic potential for adolescent concussion. External validation is required in larger cohorts.

Case Report: Inflammation and Endothelial Injury Profiling of COVID-19 Pediatric Multisystem Inflammatory Syndrome (MIS-C)

Introduction: COVID-19 is associated with a novel multi-system inflammatory syndrome that shares some characteristics with Kawasaki's Disease. The syndrome manifestation is delayed relative to COVID-19 onset, with a spectrum of clinical severity. Clinical signs may include persistent fever, gastrointestinal symptoms, cardiac inflammation and/or shock. Case Presentation: We measured 59 inflammatory and endothelial injury plasma analytes in an adolescent girl that presented with malaise, fever, cough, strawberry tongue and jaundice. Her COVID-19 status was positive with detection of 2 SARS-CoV-2 viral genes using polymerase chain reaction. She was treated with intravenous immunoglobulin prior to blood draw, but our plasma measurements suggested a unique analyte expression pattern associated with inflammation, endothelial injury and microvascular glycocalyx degradation. Conclusions: COVID-19 is associated with a multi-system inflammatory syndrome and a unique inflammatory and endothelial injury signature. Summary: Analyte markers of inflammation and endothelial cell injury might serve as putative biomarkers and/or be investigated further as potential therapeutic targets.

Clinical and Physiologic Factors Associated With Mode of Death in Pediatric Severe TBI

Aims and Objectives: Severe traumatic brain injury (sTBI) is the leading cause of death in children. Our aim was to determine the mode of death for children who died with sTBI in a Pediatric Critical Care Unit (PCCU) and evaluate factors associated with mortality. Methods: We performed a retrospective cohort study of all severely injured trauma patients (Injury Severity Score ≥ 12) with sTBI (Glasgow Coma Scale [GCS] ≤ 8 and Maximum Abbreviated Injury Scale ≥ 4) admitted to a Canadian PCCU (2000-2016). We analyzed mode of death, clinical factors, interventions, lab values within 24 h of admission (early) and pre-death (48 h prior to death), and reviewed meeting notes in patients who died in the PCCU. Results: Of 195 included patients with sTBI, 55 (28%) died in the PCCU. Of these, 31 (56%) had a physiologic death (neurologic determination of death or cardiac arrest), while 24 (44%) had withdrawal of life-sustaining therapies (WLST). Median (IQR) times to death were 35.2 (11.8, 86.4) hours in the physiologic group and 79.5 (17.6, 231.3) hours in the WLST group (p = 0.08). The physiologic group had higher partial thromboplastin time (PTT) within 24 h of admission (p = 0.04) and lower albumin prior to death (p = 0.04). Conclusions: Almost half of sTBI deaths in the PCCU were by WLST. There was a trend toward a longer time to death in these patients. We found few early and late (pre-death) factors associated with mode of death, namely higher PTT and lower albumin.

Blast in Context: The Neuropsychological and Neurocognitive Effects of Long-Term Occupational Exposure to Repeated Low-Level Explosives on Canadian Armed Forces' Breaching Instructors and Range Staff

Currently, there is strong interest within the military to better understand the effects of long-term occupational exposure to repeated low-level blast on health and performance. To gain traction on the chronic sequelae of blast, we focused on breaching—a tactical technique for gaining entry into closed/blocked spaces by placing explosives and maintaining a calculated safe distance from the detonation. Using a cross-sectional design, we compared the neuropsychological and neurocognitive profiles of breaching instructors and range staff to sex- and age-matched Canadian Armed Forces (CAF) controls. Univariate tests demonstrated that breaching was associated with greater post-concussive symptoms (Rivermead Post Concussion Symptoms Questionnaire) and lower levels of energy (RAND SF-36). In addition, breaching instructors and range staff were slower on a test that requires moving and thinking simultaneously (i.e., cognitive-motor integration). Next, using a multivariate approach, we explored the impact of other possible sources of injury, including concussion and prior war-zone deployment on the same outcomes. Concussion history was associated with higher post-concussive scores and musculoskeletal problems, whereas deployment was associated with higher post-concussive scores, but lower energy and greater PTSD symptomatology (using PCL-5). Our results indicate that although breaching, concussion, and deployment were similarly correlated with greater post-concussive symptoms, concussion history appears to be uniquely associated with altered musculoskeletal function, whereas deployment history appears to be uniquely associated with lower energy and risk of PTSD. We argue that the broader injury context must, therefore, be considered when studying the impact of repetitive low-level explosives on health and performance in military members.

Transcriptional profiling of leukocytes in critically ill COVID19 patients: implications for interferon response and coagulation

BACKGROUND

COVID19 is caused by the SARS-CoV-2 virus and has been associated with severe inflammation leading to organ dysfunction and mortality. Our aim was to profile the transcriptome in leukocytes from critically ill patients positive for COVID19 compared to those negative for COVID19 to better understand the COVID19-associated host response. For these studies, all patients admitted to our tertiary care intensive care unit (ICU) suspected of being infected with SARS-CoV-2, using standardized hospital screening methodologies, had blood samples collected at the time of admission to the ICU. Transcriptome profiling of leukocytes via ribonucleic acid sequencing (RNAseq) was then performed and differentially expressed genes as well as significantly enriched gene sets were identified.

RESULTS

We enrolled seven COVID19 + (PCR positive, 2 SARS-CoV-2 genes) and seven age- and sex-matched COVID19- (PCR negative) control ICU patients. Cohorts were well-balanced with the exception that COVID19- patients had significantly higher total white blood cell counts and circulating neutrophils and COVID19 + patients were more likely to suffer bilateral pneumonia. The mortality rate for this cohort of COVID19 + ICU patients was 29%. As indicated by both single-gene based and gene set (GSEA) approaches, the major disease-specific transcriptional responses of leukocytes in critically ill COVID19 + ICU patients were: (i) a robust overrepresentation of interferon-related gene expression; (ii) a marked decrease in the transcriptional level of genes contributing to general protein synthesis and bioenergy metabolism; and (iii) the dysregulated expression of genes associated with coagulation, platelet function, complement activation, and tumour necrosis factor/interleukin 6 signalling.

CONCLUSIONS

Our findings demonstrate that critically ill COVID19 + patients on day 1 of admission to the ICU display a unique leukocyte transcriptional profile that distinguishes them from COVID19- patients, providing guidance for future targeted studies exploring novel prognostic and therapeutic aspects of COVID19.

Brain Metabolite Levels in Sedentary Women and Non-contact Athletes Differ From Contact Athletes

White matter tracts are known to be susceptible to injury following concussion. The objective of this study was to determine whether contact play in sport could alter white matter metabolite levels in female varsity athletes independent of changes induced by long-term exercise. Metabolite levels were measured by single voxel proton magnetic resonance spectroscopy (MRS) in the prefrontal white matter at the beginning (In-Season) and end (Off-Season) of season in contact (N = 54, rugby players) and non-contact (N = 23, swimmers and rowers) varsity athletes. Sedentary women (N = 23) were scanned once, at a time equivalent to the Off-Season time point. Metabolite levels in non-contact athletes did not change over a season of play, or differ from age matched sedentary women except that non-contact athletes had a slightly lower myo-inositol level. The contact athletes had lower levels of myo-inositol and glutamate, and higher levels of glutamine compared to both sedentary women and non-contact athletes. Lower levels of myo-inositol in non-contact athletes compared to sedentary women indicates long-term exercise may alter glial cell profiles in these athletes. The metabolite differences observed between contact and non-contact athletes suggest that non-contact athletes should not be used as controls in studies of concussion in high-impact sports because repetitive impacts from physical contact can alter white matter metabolite level profiles. It is imperative to use athletes engaged in the same contact sport as controls to ensure a matched metabolite profile at baseline.

Metabolomics Profiling of Critically Ill Coronavirus Disease 2019 Patients: Identification of Diagnostic and Prognostic Biomarkers

OBJECTIVES

Coronavirus disease 2019 continues to spread rapidly with high mortality. We performed metabolomics profiling of critically ill coronavirus disease 2019 patients to understand better the underlying pathologic processes and pathways, and to identify potential diagnostic/prognostic biomarkers.

DESIGN

Blood was collected at predetermined ICU days to measure the plasma concentrations of 162 metabolites using both direct injection-liquid chromatography-tandem mass spectrometry and proton nuclear magnetic resonance.

SETTING

Tertiary-care ICU and academic laboratory.

SUBJECTS

Patients admitted to the ICU suspected of being infected with severe acute respiratory syndrome coronavirus 2, using standardized hospital screening methodologies, had blood samples collected until either testing was confirmed negative on ICU day 3 (coronavirus disease 2019 negative) or until ICU day 10 if the patient tested positive (coronavirus disease 2019 positive).

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Age- and sex-matched healthy controls and ICU patients that were either coronavirus disease 2019 positive or coronavirus disease 2019 negative were enrolled. Cohorts were well balanced with the exception that coronavirus disease 2019 positive patients suffered bilateral pneumonia more frequently than coronavirus disease 2019 negative patients. Mortality rate for coronavirus disease 2019 positive ICU patients was 40%. Feature selection identified the top-performing metabolites for identifying coronavirus disease 2019 positive patients from healthy control subjects and was dominated by increased kynurenine and decreased arginine, sarcosine, and lysophosphatidylcholines. Arginine/kynurenine ratio alone provided 100% classification accuracy between coronavirus disease 2019 positive patients and healthy control subjects (p = 0.0002). When comparing the metabolomes between coronavirus disease 2019 positive and coronavirus disease 2019 negative patients, kynurenine was the dominant metabolite and the arginine/kynurenine ratio provided 98% classification accuracy (p = 0.005). Feature selection identified creatinine as the top metabolite for predicting coronavirus disease 2019-associated mortality on both ICU days 1 and 3, and both creatinine and creatinine/arginine ratio accurately predicted coronavirus disease 2019-associated death with 100% accuracy (p = 0.01).

CONCLUSIONS

Metabolomics profiling with feature classification easily distinguished both healthy control subjects and coronavirus disease 2019 negative patients from coronavirus disease 2019 positive patients. Arginine/kynurenine ratio accurately identified coronavirus disease 2019 status, whereas creatinine/arginine ratio accurately predicted coronavirus disease 2019-associated death. Administration of tryptophan (kynurenine precursor), arginine, sarcosine, and/or lysophosphatidylcholines may be considered as potential adjunctive therapies.

Identification of adverse events in pediatric severe traumatic brain injury patients to target evidence-based prevention for increased performance improvement and patient safety

INTRODUCTION

Trauma centres are required to continuously measure, evaluate and improve care. Severe traumatic brain injury (sTBI) patients are highly susceptible to adverse events (AE; unintended, potentially harmful events resulting from health care) due to their unstable condition requiring high risk interventions, multiple medications and invasive monitoring. Objectives were to describe: (1) a process for identifying AE in pediatric sTBI patients to identify safety risks, target and implement evidence-based prevention strategies; and (2) a tertiary care PICU's sTBI AE experience.

METHODS

Merging databases, Trauma Registry with Adverse Events Management System, identified AE in patients. Details on the event location, type and severity of harm were combined with patient demographics, injury data, costs and outcomes in a cohort of 193 PICU sTBI patients (2000-15). Descriptive statistics and multivariate logistic regression were undertaken to describe AE, and their association with risk factors and outcomes.

RESULTS

103/193 sTBI patients (53%) suffered at least one AE. 238 AE occurred (1.23 AE/patient), with 30% of patients having 2+ AE. Most resulted in no harm (54%) with decubitus ulcers (15%) the most common AE. AE patients were more likely to be monitored for elevated ICP (p<0.001), with fewer ventilator-free days (p=0.015), longer LOS for PICU (11 vs. 3.5 days; p<0.001) and in-hospital (31 vs. 11 days; p<0.001) with higher median costs ($121,234 vs. $53,341; p=0.031). AE patients required a higher level of care on discharge (p=0.035).

CONCLUSIONS

Merging databases is an effective practice to identify AE and safety risks in trauma populations. Utilizing this method, a PICU AE rate of 1.23 events per patient was found with TBI severity the most important factor to increase the odds of AE. AE represent performance improvement events, opportunities to optimize care, decrease costs, as well as improve outcomes, to ultimately improve patient safety in this vulnerable population.

Inflammation Profiling of Critically Ill Coronavirus Disease 2019 Patients

OBJECTIVES

Coronavirus disease 2019 is caused by severe acute respiratory syndrome-coronavirus-2 infection to which there is no community immunity. Patients admitted to ICUs have high mortality, with only supportive therapies available. Our aim was to profile plasma inflammatory analytes to help understand the host response to coronavirus disease 2019.

DESIGN

Daily blood inflammation profiling with immunoassays.

SETTING

Tertiary care ICU and academic laboratory.

SUBJECTS

All patients admitted to the ICU suspected of being infected with severe acute respiratory syndrome-coronavirus-2, using standardized hospital screening methodologies, had daily blood samples collected until either testing was confirmed negative on ICU day 3 (coronavirus disease 2019 negative), or until ICU day 7 if the patient was positive (coronavirus disease 2019 positive).

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Age- and sex-matched healthy controls and ICU patients that were either coronavirus disease 2019 positive or coronavirus disease 2019 negative were enrolled. Cohorts were well-balanced with the exception that coronavirus disease 2019 positive patients were more likely than coronavirus disease 2019 negative patients to suffer bilateral pneumonia. Mortality rate for coronavirus disease 2019 positive ICU patients was 40%. We measured 57 inflammatory analytes and then analyzed with both conventional statistics and machine learning. Twenty inflammatory analytes were different between coronavirus disease 2019 positive patients and healthy controls (p < 0.01). Compared with coronavirus disease 2019 negative patients, coronavirus disease 2019 positive patients had 17 elevated inflammatory analytes on one or more of their ICU days 1-3 (p < 0.01), with feature classification identifying the top six analytes between cohorts as tumor necrosis factor, granzyme B, heat shock protein 70, interleukin-18, interferon-gamma-inducible protein 10, and elastase 2. While tumor necrosis factor, granzyme B, heat shock protein 70, and interleukin-18 were elevated for all seven ICU days, interferon-gamma-inducible protein 10 transiently elevated on ICU days 2 and 3 and elastase 2 increased over ICU days 2-7. Inflammation profiling predicted coronavirus disease 2019 status with 98% accuracy, whereas elevated heat shock protein 70 was strongly associated with mortality.

CONCLUSIONS

While many inflammatory analytes were elevated in coronavirus disease 2019 positive ICU patients, relative to healthy controls, the top six analytes distinguishing coronavirus disease 2019 positive ICU patients from coronavirus disease 2019 negative ICU patients were tumor necrosis factor, granzyme B, heat shock protein 70, interleukin-18, interferon-gamma-inducible protein 10, and elastase 2.