Interaction of obesity and proteins associated with the NLRP3 inflammasome following mild traumatic brain injury.

The NOD-like receptor pyrin domain-containing protein 3 (NLRP3) inflammasome has been associated with worse outcomes from severe traumatic brain injury (TBI). The NLRP3 inflammasome is also strongly associated with other pro-inflammatory conditions, such as obesity. Little is known about the potential effect of mild TBI (mTBI) on the NLRP3 inflammasome and the extent to which modifying factors, such as obesity, may augment the inflammatory response to mTBI. The purpose of this study was to evaluate the association of NLRP3 inflammasome proteins with obese body mass index (BMI ≥ 30) within 24 h of mTBI after presenting to a level 1 trauma center emergency department. This is a secondary analysis of prospectively enrolled patients with mTBI who presented to the emergency department of one U.S. Level 1 trauma center from 2013 to 2018 (n = 243). A series of regression models were built to evaluate the association of NLRP3 proteins obtained from blood plasma within 24 h of injury and BMI as well as the potential interaction effect of higher BMI with NLRP3 proteins (n = 243). A logistic regression model revealed a significant association between IL-18 (p < 0.001) in mTBI patients with obese BMI compared to mTBI patients with non-obese BMI (< 30). Moderation analyses revealed statistically significant interaction effects between apoptotic speck-like protein (ASC), caspase-1, IL-18, IL-1ß and obese BMI which worsened symptom burden, quality of life, and physical function at 2 weeks and 6 months post-injury. Higher acute concentrations of IL-1ß in the overall cohort predicted higher symptoms at 6-months and worse physical function at 2-weeks and 6-months. Higher acute concentrations of IL-18 in the overall cohort predicted worse physical function at 6-months. In this single center mTBI cohort, obese BMI interacted with higher acute concentrations of NLRP3 inflammasome proteins and worsened short- and long-term clinical outcomes.

Medical Conditions in Former Professional American-Style Football Players Are Associated With Self-Reported Clinical Features of Traumatic Encephalopathy Syndrome.

Consensus criteria for traumatic encephalopathy syndrome (TES) specify that at least one core clinical feature of cognitive impairment (CI; e.g., difficulties with memory, executive function) or neurobehavioral dysregulation (ND; e.g., explosiveness, rage, and mood lability) be present and not fully accounted for by other health disorders. Associations between self-reported symptoms that mirror the core clinical features of TES-and how they may be related to concomitant medical conditions-remain unclear. The purpose of this study was to evaluate the association of medical conditions and football exposures with TES clinical features (CI+/-, ND+/-) in 1741 former professional American-style football (ASF) players (age, 57.7 ± 13.9 years; professional seasons, 6.6 ± 3.9 years). Demographics (age, race/ethnicity, current body mass index, age of first football exposure, use of performance-enhancing drugs, position played, and past concussion symptoms), self-reported medical conditions (anxiety, depression, attention-deficit hyperactivity disorder [ADHD], sleep apnea, headache, stroke, hypertension, heart disease, high cholesterol, erectile dysfunction, and low testosterone) were collected. Of 1741 participants, 7.4% were CI+ and/or ND+ (n = 129). Participants who were CI+ or ND+ were more likely to report one or more coexisting medical conditions than participants who did not report CI or ND (odds ratio [OR] = 2.04; 95% confidence interval: 1.25-3.47; p = 0.003). Separate general linear models for each medical condition that adjusted for demographics and football-related factors identified significant associations between ADHD, diabetes, erectile dysfunction, headaches, sleep apnea, anxiety, and low testosterone and CI+ and/or ND+ (ORs = 1.8-6.0). Chi-square automatic interaction detection (CHAID) multi-variable decision tree models that incorporated medical conditions and football exposures accurately differentiated former players meeting either CI or ND clinical criteria from those meeting none (accuracy = 91.2-96.6%). CHAID identified combinations of depression, headache, sleep apnea, ADHD, and upper quartiles of concussion symptom history as most predictive of CI+ and/or ND+ status. CI+ and/or ND+ players were more likely to report medical conditions known to cause cognitive symptoms. Concussion exposure and medical conditions significantly increased the likelihood that a former ASF player would demonstrate cognitive or neurobehavioral dysfunction. Clinicians engaged with this population should consider whether treatable coexisting condition(s) could account for some portion of the clinical picture associated with TES presentation.

The Interval Between Concussions Does Not Influence Time to Asymptomatic or Return to Play: A CARE Consortium Study.

INTRODUCTION: The purpose of this study was to determine if the time interval between two concussive events influences the number of days to asymptomatic status, days to return to play, or performance on common post-concussion assessments following the second concussion. METHODS: Data from 448 collegiate athletes and service academy cadets with two concussions (time between concussions: median 295.0 days [interquartile range: 125.0-438.2]), 40.0% female) were analyzed from Concussion Assessment Research and Education (CARE) Consortium institutions between 2014 and 2020. Days between concussions was the primary predictor variable. Primary outcome measures included time to asymptomatic and time to return to play following the second concussion. Secondary outcome measures included total number of symptoms, total symptom severity, Balance Error Scoring System total score, and Standardized Assessment of Concussion total score within 48 h of their second concussion. RESULTS: Time between concussions did not significantly contribute to the multivariate time to asymptomatic (p = 0.390), time to return to play (p = 0.859), or the secondary outcomes (p-range = 0.165-0.477) models. Time to asymptomatic (p = 0.619) or return to play (p = 0.524) did not differ between same-season and different-season concussions. Sex significantly contributed to the return to play (p = 0.005) multivariate model. Delayed symptom onset and immediate removal from play/competition significantly contributed to the total number of symptoms (p = 0.001, p = 0.014) and symptom severity (p = 0.011, p = 0.022) multivariate models. CONCLUSION: These results suggest that in a population with a large period between injuries, the time between concussions may not be relevant to clinical recovery.

Evaluating Recovery After Two and Three Repeated Concussions Using Growth Curves.

The results of prior research concerning the effects of repeated concussions have been mixed. The aim of this study was to evaluate how concussion outcomes and presentation changed within patients who were evaluated at a concussion specialty clinic multiple times with a concussion. Subjects included 202 patients (54% male) aged 10-21 years (M = 13.17) who presented to a specialty concussion clinic for two and three concussions (77% sport-related) and were followed through formal clearance. First, growth curve models were estimated to determine recovery time and initial symptom burden across the multiple injuries. Second, covariates were added to these models to evaluate which demographic, risk factor, or injury variables predicted any change that did occur in evaluation or outcome variables. Models indicated that each subsequent concussion linearly resulted in significantly fewer days to recovery (-4.62 days, p < 0.047) across three concussions, and significantly lower (and linear) symptom scores on the post-concussion symptom scale (PCSS) (-2.16, p = 0.05). More severe presentation (i.e., days to recovery; higher symptom score) was significantly associated (-.62, p = 0.005) with greater improvement in recovery time (-.62, p = 0.005) and symptom burden (-.56, p < 0.001) at subsequent injuries. No covariates were significantly associated with improvement (or lack thereof) at subsequent injuries. This study adds to evidence suggesting multiple injuries is not associated with protracted recovery at subsequent injuries, in the context of treatment and full clearance for each injury at a multi-disciplinary clinic.

Temporal Changes in Fixational Eye Movements After Concussion in Adolescents and Adults: Preliminary Findings.

Concussions often involve ocular impairment and symptoms such as convergence insufficiency, accommodative insufficiency, blurred vision, diplopia, eye strain, and pain. Current clinical assessments of ocular function and symptoms rely on subjective symptom reporting and/or involve lengthy administration time. More objective, brief assessments of ocular function following concussion are warranted. The purpose of this study was to evaluate changes in fixational eye movements (FEMs) and their association with clinical outcomes including recovery time, symptoms, cognitive and vestibular/ocular motor impairment. Thirty-three athletes (13-27 years of age; 54.5% female) within 21 days of a diagnosed concussion participated in the study. A tracking scanning laser ophthalmoscope (TSLO) evaluated FEMs metrics during fixation on a center and corner target. Participants completed symptom (Post-Concussion Symptom Scale [PCSS]), cognitive (Immediate Post-concussion Assessment and Cognitive Testing [ImPACT], and Vestibular/Ocular Motor Screening (VOMS) evaluations. All measures were administered at the initial visit and following medical clearance, which was defined as clinical recovery. Changes in FEMs were calculated using paired-samples t tests. Linear regression (LR) models were used to evaluate the association of FEMs with clinical recovery. Pearson product-moment correlations were used to evaluate the associations among FEMs and clinical outcomes. On the center task, changes across time were supported for average microsaccade amplitude (p = 0.005; Cohen's d = 0.53), peak velocity of microsaccades (p = 0.01; d = 0.48), peak acceleration of microsaccades (p = 0.02; d = 0.48), duration of microsaccade (p < 0.001; d = 0.72), and drift vertical (p = 0.017; d = -0.154). The LR model for clinical recovery was significant (R2 = 0.37; p = 0.023) and retained average instantaneous drift amplitude (ß = 0.547) and peak acceleration of microsaccade (ß = 0.414). On the corner task, changes across time were supported for drift proportion (p = 0.03; d = 0.43). The LR model to predict clinical recovery was significant (R2 = 0.85; p = 0.004) and retained average amplitude of microsaccades (ß = 2.66), peak velocity of microsaccades (ß = -15.11), peak acceleration of microsaccades (ß = 12.56), drift horizontal (ß = 7.95), drift vertical (ß = 1.29), drift amplitude (ß = -8.34), drift proportion (ß = 0.584), instantaneous drift direction (ß = -0.26), and instantaneous drift amplitude (ß = 0.819). FEMs metrics were also associated with reports of nausea and performance within the domain of visual memory. The FEMs metric were also associated with PCSS, ImPACT, and VOMS clinical concussion outcomes, with the highest magnitude correlations between average saccade amplitude and VOMS symptoms of nausea and average instantaneous drift speed and ImPACT visual memory, respectively. FEMs metrics changed across time following concussion, were useful in predicting clinical recovery, and were correlated with clinical outcomes. FEMs measurements may provide objective data to augment clinical assessments and inform prognosis following this injury.

Interaction of Medical Conditions and Football Exposures Associated with Premortem Chronic Traumatic Encephalopathy Diagnosis in Former Professional American Football Players.

BACKGROUND AND OBJECTIVE: Despite being a postmortem diagnosis, former professional American-style football players report receiving chronic traumatic encephalopathy (CTE) diagnoses from medical care providers. However, many players also report other health conditions that manifest with cognitive and psychological symptoms. The purpose of this study was to identify how medical conditions, psychological disorders, and football exposure combinations are associated with former athletes reporting a premortem CTE diagnosis. METHODS: This study was a cross-sectional cohort survey from 2015 to 2019 of 4033 former professional American-style football players. Demographics (age, race, domestic status, primary care recipient), football-related factors (position, years of professional play, burden of symptoms following head impacts, performance-enhancing drug use), and comorbidities (sleep apnea, psychological disorder status [depression and anxiety; either depression or anxiety; neither depression nor anxiety], diabetes mellitus, attention-deficit/hyperactivity disorder, hypertension, heart conditions, high cholesterol, stroke, cancer, low testosterone, chronic pain, current and maximum body mass index) were recorded. A Chi-square automatic interaction detection (CHAID) decision tree model identified interactive effects between demographics, health conditions, and football exposures on the CTE diagnosis. RESULTS: Depression showed the strongest univariate association with premortem CTE diagnoses (odds ratio [OR] = 9.5, 95% confidence interval [CI] 6.0-15.3). CHAID differentiated participants with premortem CTE diagnoses with 98.2% accuracy and area under the curve = 0.81. Participants reporting both depression and anxiety were more likely to have a CTE diagnosis compared with participants who reported no psychological disorders (OR = 12.2; 95% CI 7.3-21.1) or one psychological disorder (OR = 4.5; 95% CI 1.9-13.0). Sleep apnea was also associated with a CTE diagnosis amongst those with both depression and anxiety (OR = 2.7; 95% CI 1.4-5.2). CONCLUSIONS: Clinical phenotypes including psychological disorders and sleep apnea were strongly associated with an increased likelihood of having received a pre-mortem CTE diagnosis in former professional football players. Depression, anxiety, and sleep apnea produce cognitive symptoms, are treatable conditions, and should be distinguished from neurodegenerative disease.

Network analysis and relationship of symptom factors to functional outcomes and quality of life following mild traumatic brain injury: a TRACK-TBI study.

Introduction: Mild traumatic brain injury (mTBI) is a heterogenous injury which can be difficult to characterize and manage. Using cross-sectional network analysis (NA) to conceptualize mTBI symptoms offers an innovative solution to identify how mTBI symptoms relate to each other. The centrality hypothesis of network theory posits that certain symptoms in a network are more relevant (central) or have above average influence over the rest of the network. However, no studies have used NA to characterize the interrelationships between symptoms in a cohort of patients who presented with mTBI to a U.S. Level 1 trauma center emergency department and how subacute central symptoms relate to long-term outcomes. Methods: Patients with mTBI (Glasgow Coma Scale = 13-15) evaluated across 18 U.S. Level 1 trauma centers from 2013 to 2019 completed the Rivermead Post-Concussion Symptoms Questionnaire (RPQ) at 2 weeks (W2) post-injury (n = 1,593) and at 3 months (M3), 6 months (M6), and 12 months (M12) post-injury. Network maps were developed from RPQ subscale scores at each timepoint. RPQ scores at W2 were associated with M6 and M12 functional and quality of life outcomes. Results: Network structure did not differ across timepoints, indicating no difference in symptoms/factors influence on the overall symptom network across time. The cognitive factor had the highest expected influence at W2 (1.761), M3 (1.245), and M6 (1.349). Fatigue had the highest expected influence at M12 (1.275). The emotional factor was the only other node with expected influence >1 at any timepoint, indicating disproportionate influence of emotional symptoms on overall symptom burden (M3 = 1.011; M6 = 1.076). Discussion: Several symptom factors at 2-weeks post-injury were more strongly associated with incomplete recovery and/or poorer injury-related quality of life at 6 and 12 months post-injury than previously validated demographic and clinical covariates. The network analysis suggests that emotional, cognitive, and fatigue symptoms may be useful treatment targets in this population due to high centrality and activating potential of the overall symptom network.

Comparison of physiological outcomes after dynamic exertion between athletes at return to sport from concussion and controls: Preliminary findings.

OBJECTIVES: Compare physiological (heart rate, heart rate variability, and blood pressure), performance (change-of-direction task completion time and errors), and clinical (symptoms and rating of perceived exertion) outcomes during dynamic exertion between athletes at return to sport after concussion to healthy athlete controls. DESIGN: Case control. METHODS: A sample of 23 (Female = 10; 43.5 %) athletes at medical clearance to play/activity from concussion (CONCUSS) and 23 sex-, age-, and sport-matched healthy athletes (CONTROLS) completed a 5-min seated rest before and after the dynamic exertion test. Independent sample t-tests were used to compare CONCUSS and CONTROLS for completion time, heart rate, and blood pressure; and Mann-Whitney U tests for symptoms, perceived exertion, and errors. A series of ANOVAs were conducted to compare heart rate variability between groups across pre- and post-exercise rest periods. RESULTS: There were no differences in heart rate, blood pressure, symptoms, perceived exertion, and errors. CONCUSS were faster on Zig Zag (p = .048) and Pro Agility (p = .018) tasks, reported lower symptom severity (p = .019), and had lower post-EXiT HRV (p < .049) than CONTROLS. CONCLUSIONS: Performance, symptoms, perceived exertion, and blood pressure outcomes from dynamic exertion were equivocal between athletes at medical clearance from concussion and healthy controls, which provide empirical support for dynamic exercise to inform medical clearance clinical decision making for sport-related concussion. However, differences in autonomic nervous system functioning indicate that additional research is needed to examine temporal changes in heart rate variability and other physiological outcomes following dynamic exertion.

Interaction of admission platelet count with current medications and the risk for chronic subdural recurrence.

OBJECTIVE: Chronic subdural hematoma (cSDH) has a reported 10%-24% rate of recurrence after surgery, and prognostic models for recurrence have produced equivocal results. The objective of this study was to leverage a data mining algorithm, chi-square automatic interaction detection (CHAID), which can incorporate continuous, nominal, and binary data into a decision tree, to identify the most robust predictors of repeat surgery for cSDH patients. METHODS: This was a retrospective cohort study of all patients with SDH from two level 1 trauma centers at a single institution. All patients underwent cSDH evacuation performed by 15 neurosurgeons between 2011 and 2020. The primary outcome was the rate of repeat surgery for recurrent cSDH following the initial evacuation. The authors used CHAID to identify relevant predictors of repeat surgery, including age, sex, comorbidities, postsurgical complications, platelet count prior to the first procedure, midline shift prior to the first procedure, hematoma volume, and preoperative use of anticoagulants, antiplatelets, or statins. RESULTS: Sixty (13.8%) of 435 study-eligible patients (average age 74.0 years) had a cSDH recurrence. These patients had 2.0 times greater odds of having used anticoagulants. The final CHAID model had an overall accuracy of 87.4% and an area under the curve of 0.76. According to the model, the predictor with the strongest association with cSDH recurrence was admission platelet count. Approximately 26% of patients (n = 23/87) with an admission platelet count < 157 × 109/L had a cSDH recurrence, whereas none of the 44 patients with admission platelets > 313 × 109/L had a recurrence. Approximately 17% of patients in the 157-313 × 109/L platelet group who had used preoperative statins required a second procedure, which was associated with a 2.3 times increased risk for repeat surgery compared to those who had not used statins preoperatively. Among those who had not used preoperative statins, a platelet count ≤ 179 × 109/L on admission for the first procedure was the strongest differentiator for a second surgery (n = 5/22 [23%]), which increased the risk of recurrence by 4.5 times. Among the patients using preoperative statins, the use of anticoagulants was the strongest differentiator for requiring repeat surgery (n = 11/33 [33%]). CONCLUSIONS: The described model identified platelet count on admission as the most important predictor of repeat cSDH surgery, followed by preoperative statin use and anticoagulant use. Critical cutoffs for platelet count were identified, which future studies should evaluate to determine if they are modifiable or reflective of underlying disease states.

Comparison of machine learning models to predict long-term outcomes after severe traumatic brain injury.

OBJECTIVE: An estimated 1.5 million people die every year worldwide from traumatic brain injury (TBI). Physicians are relatively poor at predicting long-term outcomes early in patients with severe TBI. Machine learning (ML) has shown promise at improving prediction models across a variety of neurological diseases. The authors sought to explore the following: 1) how various ML models performed compared to standard logistic regression techniques, and 2) if properly calibrated ML models could accurately predict outcomes up to 2 years posttrauma. METHODS: A secondary analysis of a prospectively collected database of patients with severe TBI treated at a single level 1 trauma center between November 2002 and December 2018 was performed. Neurological outcomes were assessed at 3, 6, 12, and 24 months postinjury with the Glasgow Outcome Scale. The authors used ML models including support vector machine, neural network, decision tree, and naïve Bayes models to predict outcome across all 4 time points by using clinical information available on admission, and they compared performance to a logistic regression model. The authors attempted to predict unfavorable versus favorable outcomes (Glasgow Outcome Scale scores of 1-3 vs 4-5), as well as mortality. Models' performance was evaluated using the area under the receiver operating characteristic (ROC) curve (AUC) with 95% confidence interval and balanced accuracy. RESULTS: Of the 599 patients in the database, the authors included 501, 537, 469, and 395 at 3, 6, 12, and 24 months posttrauma. Across all time points, the AUCs ranged from 0.71 to 0.85 for mortality and from 0.62 to 0.82 for unfavorable outcomes with various modeling strategies. Decision tree models performed worse than all other modeling approaches for multiple time points regarding both unfavorable outcomes and mortality. There were no statistically significant differences between any other models. After proper calibration, the models had little variation (0.02-0.05) across various time points. CONCLUSIONS: The ML models tested herein performed with equivalent success compared with logistic regression techniques for prognostication in TBI. The TBI prognostication models could predict outcomes beyond 6 months, out to 2 years postinjury.

Applying the Sliding Scale Approach to Quantifying Functional Outcomes Up to Two Years After Severe Traumatic Brain Injury.

Outcomes after severe traumatic brain injury (TBI) can be represented by a sliding score that compares actual functional recovery to that predicted by illness severity models. This approach has been applied in clinical trials because of its statistical efficiency and interpretability but has not been used to describe change in functional recovery over time. The objective of this study was to use a sliding scoring system to describe the magnitude of change in Glasgow Outcome Scale Extended (GOSE) score at 6, 12, and 24 months after severe TBI and to compare patients who improved after 6 months to those who did not. This study included consecutive severe TBI patients (Glasgow Coma Scale ≤8; n = 482) from a single center. We grouped patients into four strata based on probability of unfavorable outcome (GOSE = 1-4) using the International Mission on Prognosis and Analysis of Clinical Trials (IMPACT) model, selected a dichotomous GOSE threshold within each stratum, and compared each patient's GOSE to this threshold to calculate a score (GOSE-Sliding Scale [SS]) from -5 to +4 at 6, 12, and 24 months. We compared GOSE-SS at 6 months with GOSE-SS at 12 and 24 months and also compared characteristics of participants who improved after 6 months with characteristics of those who did not using χ2 and t tests. Compared with at 6 months, 40% of patients (n = 74) had improved GOSE-SS at 12 months, and 53% had improved GOSE-SS by 24 months (n = 72). Among those who improved at 12 months, the average magnitude of improvement was 1.7 ± 0.9 and among those who improved at 24 months, the average magnitude of improvement was 1.9 ± 1.0. Those who improved their GOSE-SS score from 6 to 24 months had longer hospital stays (mean-difference = 8.6 days; p = 0.03), longer intensive care unit (ICU) stays (mean-difference = 5.5 days; p = 0.02), and longer ventilator time (mean-difference = 5 days; p = 0.02) than those who worsened. These results support an optimistic long-term outlook for severe TBI patients and emphasize the importance of long-term follow-up in severe TBI survivors.

Incidence of concussion and associated risk factors in collegiate soccer: findings from the NCAA-DoD CARE consortium.

This retrospective cohort study aims to examine concussion incidence rates (IR) in collegiate soccer players and compare IRs based on risk factors including sex, competition level, games/practices, history of concussion, and playing position. Collegiate soccer players were recruited (n = 2,471) from 23 institutions from the NCAA-DoD Concussion Assessment, Research, and Education (CARE) Consortium. Incidence rates for concussion per 1000 athlete exposures (AEs) were calculated across the 2015-16/2016-17 seasons. Incidence rates (IR) comparing risk factor groups were also calculated. A total of 162 concussions occurred during the study, for an IR of 0.08/1000 AEs. Females were more likely to have a concussion than males overall (IR = 1.47) and were more likely to have a concussion in games (IR = 1.42) and practices (IR = 2.91). Concussions were more likely during competition compared to practice (IR = 2.53), and less likely in Division III, compared to Divisions I and II, χ2 = 6.5, p > .05. In the concussed group, male sex was associated with 2.47 times higher odds of playing defender and 2.29 times higher odds of a collision mechanism. Results confirm previous findings that females and game exposures have higher concussion IR than males and practice exposures. Findings also supported sex differences in IRs based on exposure type, position, and mechanism.

Association of obesity with mild traumatic brain injury symptoms, inflammatory profile, quality of life and functional outcomes: a TRACK-TBI Study.

OBJECTIVES: Obesity is associated with chronic inflammation, which may impact recovery from mild traumatic brain injury (mTBI). The objective was to assess the role of obesity in recovery of symptoms, functional outcome and inflammatory blood biomarkers after mTBI. METHODS: TRACK-TBI is a prospective study of patients with acute mTBI (Glasgow Coma Scale=13-15) who were enrolled ≤24 hours of injury at an emergency department of level 1 trauma centres and followed for 12 months. A total of 770 hospitalised patients who were either obese (body mass index (BMI) >30.0) or healthy mass (BMI=18.5-24.9) were enrolled. Blood concentrations of high-sensitivity C reactive protein (hsCRP), interleukin (IL) 6, IL-10, tumour necrosis factor alpha; Rivermead Post-Concussion Symptoms Questionnaire (RPQ), Quality of Life After Brain Injury and Glasgow Outcome Score-Extended reflecting injury-related functional limitations at 6 and 12 months were collected. RESULTS: After adjusting for age and gender, obese participants had higher concentrations of hsCRP 1 day after injury (mean difference (MD)=0.65; 95% CI: 0.44 to 0.87, p<0.001), at 2 weeks (MD=0.99; 95% CI: 0.74 to 1.25, p<0.001) and at 6 months (MD=1.08; 95% CI: 0.79 to 1.37, p<0.001) compared with healthy mass participants. Obese participants had higher concentrations of IL-6 at 2 weeks (MD=0.37; 95% CI: 0.11 to 0.64, p=0.006) and 6 months (MD=0.42; 95% CI: 0.12 to 0.72, p=0.006). Obese participants had higher RPQ total score at 6 months (MD=2.79; p=0.02) and 12 months (MD=2.37; p=0.049). CONCLUSIONS: Obesity is associated with higher symptomatology at 6 and 12 months and higher concentrations of blood inflammatory markers throughout recovery following mTBI.

Evaluating Targeted Therapeutic Response With Predictive Blood-Based Biomarkers in Patients With Chronic Mild Traumatic Brain Injury.

Chronic consequences of mild traumatic brain injury (mTBI) are heterogeneous, but may be treatable with targeted medical and rehabilitation interventions. A biological signature for the likelihood of response to therapy (i.e., "predictive" biomarkers) would empower personalized medicine post-mTBI. The purpose of this study was to correlate pre-intervention blood biomarker levels and the likelihood of response to targeted interventions for patients with chronic issues attributable to mTBI. Patients with chronic symptoms and/or disorders secondary to mTBI >3 months previous (104 days to 15 years; n = 74) were enrolled. Participants completed pre-intervention assessments of symptom burden, comprehensive clinical evaluation, and blood-based biomarker measurements. Multi-domain targeted interventions for specific symptoms and impairments across a 6-month treatment period were prescribed. Participants completed a follow-up testing after the treatment period. An all-possible model's backward logistic regression was built to identify predictors of improvement in relation to blood biomarker levels before intervention. The minimum clinically important difference (MCID) of the change score (post-intervention subtracted from pre-intervention) for the Post-Concussion Symptom Scale (PCSS) to identify treatment responders from non-responders was the primary outcome. The MCID for total PCSS score was 10. The model to predict change in PCSS score over the 6-month intervention was significant (R2 = 0.09; p = 0.01) and identified ubiquitin C-terminal hydrolase L1 (odds ratio [OR] = 2.53; 95% confidence interval [CI], 1.18-5.46; p = 0.02) and hyperphosphorylated tau (p-tau; OR = 0.70; 95% CI, 0.51-0.96; p = 0.03) as significant predictors of symptom improvement beyond the PCSS MCID. In this cohort of chronic TBI subjects, blood biomarkers before rehabilitation intervention predicted the likelihood of response to targeted therapy for chronic disorders post-TBI.

Association of Plasma Biomarkers with Sleep Outcomes and Treatment Response After Mild Traumatic Brain Injury.

Sleep disturbances occur in up to 70% of patients with mild traumatic brain injury (mTBI). Modern mTBI management recommends targeted treatment for the patient's unique clinical manifestations (i.e., obstructive sleep apnea, insomnia). The purpose of this study was to evaluate the association of plasma biomarkers with symptom reports, overnight sleep evaluations, and response to treatment for sleep disturbances secondary to mTBI. This study is a secondary analysis of a prospective multiple interventional trial of patients with chronic issues related to mTBI. Pre- and post-intervention assessments were conducted, including overnight sleep apnea evaluation, the Pittsburgh Sleep Quality Index (PSQI), and blinded analysis of blood biomarkers. Bivariate Spearman correlations were conducted for pre-intervention plasma biomarker concentrations and 1) PSQI change scores and 2) pre-intervention sleep apnea outcomes (i.e., oxygen saturation measures). A backward logistic regression model was built to evaluate the association of pre-intervention plasma biomarkers with improvement in PSQI over the treatment period (p < 0.05). Participants were 36.3 ± 8.6 years old and 6.1 ± 3.8 years from their index mTBI. Participants reported subjective improvements (PSQI = -3.7 ± 3.8), whereas 39.3% (n = 11) had improved PSQI scores beyond the minimum clinically important difference (MCID). PSQI change scores correlated with von Willebrand factor (vWF; ρ = -0.50; p = 0.02) and tau (ρ = -0.53; p = 0.01). Hyperphosphorylated tau correlated with average saturation (ρ = -0.29; p = 0.03), lowest desaturation (ρ = -0.27; p = 0.048), and baseline saturation (ρ = -0.31; p = 0.02). The multi-variate model (R 2 = 0.33; p = 0.001) retained only pre-intervention vWF as a predictor (odds ratio = 3.41; 95% confidence interval, 1.44-8.08; p = 0.005) of improving PSQI scores beyond the MCID. vWF had good discrimination (area under the curve = 0.83; p = 0.01), with an overall accuracy of 77%, sensitivity of 46.2%, and specificity of 90.0%. Validation of vWF as a potential predictive biomarker of sleep improvement post-mTBI could optimize personalized management and healthcare utilization.

Performance of CRASH and IMPACT Prognostic Models for Traumatic Brain Injury at 12 and 24 Months Post-Injury.

The Corticoid Randomization after Significant Head Injury (CRASH) and International Mission for Prognosis and Analysis of Clinical Trials (IMPACT) prognostic models are the most reported prognostic models for traumatic brain injury (TBI) in the scientific literature. However, these models were developed and validated to predict 6-month unfavorable outcome and mortality, and growing evidence supports continuous improvements in functional outcome after severe TBI up to 2 years post-injury. The purpose of this study was to evaluate CRASH and IMPACT model performance beyond 6 months post-injury to include 12 and 24 months post-injury. Discriminative validity remained consistent over time and comparable to earlier recovery time points (area under the curve = 0.77-0.83). Both models had poor fit for unfavorable outcomes, explaining less than one quarter of the variation in outcomes for severe TBI patients. The CRASH model had significant values for the Hosmer-Lemeshow test at 12 and 24 months, indicating poor model fit past the previous validation point. There is concern in the scientific literature that TBI prognostic models are being used by neurotrauma clinicians to support clinical decision making despite the goal of the models' development being to support research study design. The results of this study indicate that the CRASH and IMPACT models should not be used in routine clinical practice because of poor model fit that worsens over time and the large, unexplained variance in outcomes.

Pilot Biomarker Analysis and Decision Tree Algorithm Modeling of Patients with Chronic Subdural Hematomas.

The elderly population are at high risk for developing chronic subdural hematoma (cSDH). Surgical evacuation of cSDH is one of the most common procedures performed in neurosurgery. The present study aims to identify potential inflammatory biomarkers associated with its development and recurrence. Patients (>65 years of age) who presented with symptomatic cSDH (≥1 cm thickness or ≥5 mm midline shift [MLS]), requiring surgical intervention, were prospectively enrolled. The collected cSDH fluid was analyzed for inflammatory markers. Computed tomography (CT) scan data included pre-operative cSDH thickness and MLS. Outcome data included Glasgow Outcome Scale-Extended (GOS-E) score at 3, 6, and 12 months post-surgery, as well as cSDH recurrence. A decision tree model was used to determine the predictive power of extracted analytes for MLS, cSDH thickness, and recurrence. This pilot study includes 20 enrolled patients (mean age 77.9 ± 7.4 years and 85% falls). Rate of cSDH recurrence was 42%, with 21% requiring reoperation. Chemokine (C-X-C motif) ligand 9 (CXCL9) concentrations correlated with cSDH thickness (r = 0.975, p = 0.040). Interleukin (IL)-6 and vascular endothelial growth factor (VEGF)-A concentrations correlated with MLS (r = 0.974, p = 0.005; r = 0.472, p = 0.036, respectively). IL-5 concentrations correlated with more favorable GOS-E scores at 3, 6, and 12 months (r = 0.639, p = 0.006; r = 0.727, p = 0.003; r = 0.693, p = 0.026, respectively). Regulated on activation, normal T-cell expressed and secreted (RANTES) concentrations correlated with complete cSDH resolution (r = 0.514, p = 0.021). The decision tree model identified that higher concentrations of CXCL9 were predictive of MLS (risk ratio [RR] = 12.0), higher concentrations of IL-5 were predictive of cSDH thickness (RR = 4.5), and lower concentrations of RANTES were predictive of cSDH recurrence (RR = 2.2). CXCL9, IL-6, VEGF, IL-5, and RANTES are associated with recurrence after surgery and may be potential biomarkers for predicting cSDH recurrence and neurological outcomes.

Military tactical adaptive decision making during simulated military operational stress is influenced by personality, resilience, aerobic fitness, and neurocognitive function.

Laboratory-based studies designed to mimic combat or military field training have consistently demonstrated deleterious effects on warfighter's physical, cognitive, and emotional performance during simulated military operational stress (SMOS). Purpose: The present investigation sought to determine the impact of a 48-h simulated military operational stress (SMOS) on military tactical adaptive decision making, and the influence of select psychological, physical performance, cognitive, and physiological outcome measures on decision making performance. Methods: Male (n = 48, 26.2 ± 5.5 years, 177.7 ± 6.6 cm, 84.7 ± 14.1 kg.) subjects currently serving in the U.S. military were eligible to participate in this study. Eligible subjects completed a 96-h protocol that occurred over five consecutive days and four nights. Day 2 (D2) and day 3 (D3) consisted of 48-h of SMOS wherein sleep opportunity and caloric needs were reduced to 50%. Differences in SPEAR total block score from baseline to peak stress (D3 minus D1) were calculated to assess change in military tactical adaptive decision making and groups were stratified based on increase (high adaptors) or decrease (low adaptors) of the SPEAR change score. Results: Overall, military tactical decision-making declined 1.7% from D1 to D3 (p < 0.001). High adaptors reported significantly higher scores of aerobic capacity (p < 0.001), self-report resilience (p = 0.020), extroversion (p < 0.001), and conscientiousness (p < 0.001). at baseline compared to low adaptors, while low adaptors reported greater scores in Neuroticism (p < 0.001). Conclusion: The present findings suggest that service members whose adaptive decision making abilities improved throughout SMOS (i.e., high adaptors) demonstrated better baseline psychological/self-reported resilience and aerobic capacity. Further, changes in adaptive decision-making were distinct from those of lower order cognitive functions throughout SMOS exposure. With the transition of future military conflicts placing higher priority on enhancing and sustaining cognitive readiness and resiliency, data presented here demonstrates the importance of measuring and categorizing baseline measures inherent to military personnel, in order to change and train one's ability to suffer less of a decline during high stress conditions.

The Effects of Rest on Concussion Symptom Resolution and Recovery Time: A Meta-analytic Review and Subgroup Analysis of 4329 Patients.

BACKGROUND: Numerous individual studies suggest that rest may have a negative effect on outcomes following concussion. PURPOSE: To perform a systematic meta-analysis of the effects of prescribed rest compared with active interventions after concussion. STUDY DESIGN: Meta-analysis; Level of evidence, 4. METHODS: A meta-analysis (using the Hedges g) of randomized controlled trials and cohort studies was conducted to evaluate the effects of prescribed rest on symptoms and recovery time after concussion. Subgroup analyses were performed for methodological, study, and sample characteristics. Data sources were obtained from systematic search of key terms using Ovid Medline, Embase, Cochrane Database of Systematic Reviews, APA PsycINFO, Web of Science, SPORTDiscus, and ProQuest dissertations and theses through May 28, 2021. Eligible studies were those that (1) assessed concussion or mild traumatic brain injury; (2) included symptoms or days to recovery for ≥2 time points; (3) included 2 groups with 1 group assigned to rest; and (4) were written in the English language. RESULTS: In total, 19 studies involving 4239 participants met criteria. Prescribed rest had a significant negative effect on symptoms (k = 15; g = -0.27; SE = 0.11; 95% CI, -0.48 to -0.05; P = .04) but not on recovery time (k = 8; g = -0.16; SE = 0.21; 95% CI, -0.57 to 0.26; P = .03). Subgroup analyses suggested that studies with shorter duration (<28 days) (g = -0.46; k = 5), studies involving youth (g = -0.33; k = 12), and studies focused on sport-related concussion (g = -0.38; k = 8) reported higher effect sizes. CONCLUSION: The findings support a small negative effect for prescribed rest on symptoms after concussion. Younger age and sport-related mechanisms of injury were associated with a greater negative effect size. However, the lack of support for an effect for recovery time and the relatively small overall numbers of eligible studies highlight ongoing concerns regarding the quantity and rigor of clinical trials in concussion. REGISTRATION: CRD42021253060 (PROSPERO).