Potential Biomarkers of impulsivity in mild traumatic brain injury: A pilot study.

Very few studies have investigated cognition and impulsivity following mild traumatic brain injury (mTBI) in the general population. Furthermore, the neurobiological mechanisms underlying post-TBI neurobehavioral syndromes are complex and remain to be fully clarified. Herein, we took advantage of machine learning based-modeling to investigate potential biomarkers of mTBI-associated impulsivity. Twenty-one mTBI patients were assessed within one-month post-TBI and their data were compared to 19 healthy controls on measures of impulsivity (Barratt Impulsiveness Scale - BIS), executive functioning, episodic memory, self-report cognitive failures and blood biomarkers of inflammation, vascular and neuronal damage. mTBI patients were significantly more impulsive than controls in BIS total and subscales. Serum levels of sCD40L, Cathepsin D, IL-4, Neuropilin-1, IFN-α2, and Copeptin were associated with impulsivity in mTBI patients. Besides showing that mTBI are associated with impulsivity in non-military people, we unveiled different pathophysiological pathways potentially implicated in mTBI-related impulsivity.

Post-concussive mTBI in Student Athletes: MRI Features and Machine Learning.

Purpose: To determine and characterize the radiomics features from structural MRI (MPRAGE) and Diffusion Tensor Imaging (DTI) associated with the presence of mild traumatic brain injuries on student athletes with post-concussive syndrome (PCS). Material and Methods: 122 student athletes (65 M, 57 F), median (IQR) age 18.8 (15-20) years, with a mixed level of play and sports activities, with a known history of concussion and clinical PCS, and 27 (15 M, 12 F), median (IQR) age 20 (19, 21) years, concussion free athlete subjects were MRI imaged in a clinical MR machine. MPRAGE and DTI-FA and DTI-ADC images were used to extract radiomic features from white and gray matter regions within the entire brain (2 ROI) and the eight main lobes of the brain (16 ROI) for a total of 18 analyzed regions. Radiomic features were divided into five different data sets used to train and cross-validate five different filter-based Support Vector Machines. The top selected features of the top model were described. Furthermore, the test predictions of the top four models were ensembled into a single average prediction. The average prediction was evaluated for the association to the number of concussions and time from injury. Results: Ninety-one PCS subjects passed inclusion criteria (91 Cases, 27 controls). The average prediction of the top four models had a sensitivity of 0.80, 95% CI: [0.71, 0.88] and specificity of 0.74 95%CI [0.54, 0.89] for distinguishing subjects from controls. The white matter features were strongly associated with mTBI, while the whole-brain analysis of gray matter showed the worst association. The predictive index was significantly associated with the number of concussions (p < 0.0001) and associated with the time from injury (p < 0.01). Conclusion: MRI Radiomic features are associated with a history of mTBI and they were successfully used to build a predictive machine learning model for mTBI for subjects with PCS associated with a history of one or more concussions.

Specific Factors Influence Postconcussion Symptom Duration among Youth Referred to a Sports Concussion Clinic.

OBJECTIVE: To identify the clinical factors that influence the duration of postconcussion symptoms among youth referred to a sports concussion clinic. STUDY DESIGN: A retrospective cohort study was conducted to evaluate several potential predictors of symptom duration via a Cox proportional hazards analyses. The individual postconcussion symptom scores were highly correlated, so these symptoms were analyzed in the statistical model as coefficients derived from principal component analyses. RESULTS: Among 1953 youth with concussion, 1755 (89.9%) had dates of reported symptom resolution. The remainder (10.1%) were lost to follow-up and censored. The median time to recovery was 18 days (range 1-353 days). By 30 days, 72.6% had recovered; by 60 days, 91.4% had recovered; and by 90 days, 96.8% had recovered. Several variables in a multivariate Cox model predicted postconcussion symptom duration: female sex (P < .001, hazard ratio [HR] = 1.28), continued activity participation (P = .02, HR = 1.13), loss of consciousness (P = .03, HR = 1.18), anterograde amnesia (P = .04, HR = 1.15), premorbid headaches (P = .03, HR = 1.15), symptom components from the day of concussion (emotion, P = .03, HR = 1.08), and the day of clinic evaluation (cognitive-fatigue, P < .001, HR = 1.22; cephalalgic, P < .001, HR = 1.27; emotional, P = .05, HR = 1.08; arousal-stimulation, P = .003, HR = 1.1). In univariate analyses, greater symptom scores generally predicted longer symptom durations. Worsening of symptoms from the day of concussion to the day of clinic evaluation also predicted longer recovery (P < .001, HR = 1.59). CONCLUSIONS: Several factors help to predict protracted postconcussion symptom durations among youth referred to a sports concussion clinic.

Effects of Blast Exposure on Subjective and Objective Sleep Measures in Combat Veterans with and without PTSD.

STUDY OBJECTIVES: This study examined the extent to which self-reported exposure to blast during deployment to Iraq and Afghanistan affects subjective and objective sleep measures in service members and veterans with and without posttraumatic stress disorder (PTSD). METHODS: Seventy-one medication-free service members and veterans (mean age = 29.47 ± 5.76 years old; 85% men) completed self-report sleep measures and overnight polysomnographic studies. Four multivariate analyses of variance (MANOVAs) were conducted to examine the impact of blast exposure and PTSD on subjective sleep measures, measures of sleep continuity, non-rapid eye movement (NREM) sleep parameters, and rapid eye movement (REM) sleep parameters. RESULTS: There was no significant Blast × PTSD interaction on subjective sleep measures. Rather, PTSD had a main effect on insomnia severity, sleep quality, and disruptive nocturnal behaviors. There was no significant Blast × PTSD interaction, nor were there main effects of PTSD or Blast on measures of sleep continuity and NREM sleep. A significant PTSD × Blast interaction effect was found for REM fragmentation. CONCLUSIONS: The results suggest that, although persistent concussive symptoms following blast exposure are associated with sleep disturbances, self-reported blast exposure without concurrent symptoms does not appear to contribute to poor sleep quality, insomnia, and disruptive nocturnal disturbances beyond the effects of PTSD. Reduced REM sleep fragmentation may be a sensitive index of the synergetic effects of both psychological and physical insults.