Longitudinal Trajectories of Post-Concussive Symptoms Following Mild Traumatic Brain Injury.

BACKGROUND: Individuals recovering from mild traumatic brain injury (TBI) represent a heterogenous population that requires distinct treatment approaches. Identification of recovery trajectories improves our ability to understand the natural history of mild TBI recovery and develop targeted interventions. OBJECTIVE: To utilize group-based trajectory modeling (GBTM) to identify distinct patterns of symptom recovery following mild TBI in the first 6 months after mild TBI. METHODS: This study is comprised of 253 adults who presented to the emergency department with mild TBI and completed assessments for six-months post-injury. Patients were recruited for the prospective observational cohort study, HeadSMART. The primary outcome measure was the Rivermead Postconcussion Symptom Questionnaire. GBTM was used to identify longitudinal trajectories of recovery following mild TBI using Rivermead scores at baseline, one, three, and six months following diagnosis. RESULTS: Findings identified four distinct trajectories of symptom recovery follwing mild TBI including 9% of participants who were categorized with minimal acute symptoms that decreased over time, 45% with mild acute symptoms that decreased over time, 33% with relatively higher acute symptoms that decreased over time, and 13% with relatively higher acute symptoms that increased over time. CONCLUSIONS: GBTM identified four distinct trajectories of recovery following mild TBI and GBTM may be useful for research interventions that can alter recovery trajectories.

Prevalence and Correlates of Depressive Symptoms Within 6 Months After First-Time Mild Traumatic Brain Injury.

OBJECTIVE: Depressive symptoms are among the most common neuropsychiatric sequelae of mild traumatic brain injury (mTBI). Very few studies have compared correlates of depressive symptoms within the first 6 months of injury in cohorts experiencing their first TBI. The authors investigated whether the correlates of depressive symptoms (being female, older, lower education, having brain lesions, experiencing worse postconcussive symptoms, and incomplete functional recovery) that have been established in populations with moderate to severe TBI were the same for individuals with first-time mTBI within the first 6 months of recovery. METHODS: Two hundred seventeen individuals with first-time mTBI were divided into subgroups-new-onset depressive symptoms, recurrent depressive symptoms, prior depression history only, and never depressed-and compared on clinical and demographic variables and the presence of postconcussive symptoms and functional recovery at 3 and 6 months. RESULTS: New-onset depressive symptoms developed in 12% of the cohort, whereas 11% of the cohort had recurrent depressive symptoms. Both depressive symptoms groups were more likely to comprise women and persons of color and were at higher risk for clinically significant postconcussive symptoms and incomplete functional recovery for the first 6 months postinjury. CONCLUSIONS: Presence of depressive symptoms after first-time mTBI was associated with persistent postconcussive symptoms and incomplete functional recovery in the first 6 months. Adding to the existing literature, these findings identified correlates of depressive symptom development and poor outcomes after mTBI, thus providing further evidence that mTBI may produce persistent symptoms and functional limitations that warrant clinical attention.

Loss of Consciousness and Altered Mental State as Predictors of Functional Recovery Within 6 Months Following Mild Traumatic Brain Injury.

OBJECTIVE: The authors tested the hypothesis that a combination of loss of consciousness (LOC) and altered mental state (AMS) predicts the highest risk of incomplete functional recovery within 6 months after mild traumatic brain injury (mTBI), compared with either condition alone, and that LOC alone is more strongly associated with incomplete recovery, compared with AMS alone. METHODS: Data were analyzed from 407 patients with mTBI from Head injury Serum Markers for Assessing Response to Trauma (HeadSMART), a prospective cohort study of TBI patients presenting to two urban emergency departments. Four patient subgroups were constructed based on information documented at the time of injury: neither LOC nor AMS, LOC only, AMS only, and both. Logistic regression models assessed LOC and AMS as predictors of functional recovery at 1, 3, and 6 months. RESULTS: A gradient of risk of incomplete functional recovery at 1, 3, and 6 months postinjury was noted, moving from neither LOC nor AMS, to LOC or AMS alone, to both. LOC was associated with incomplete functional recovery at 1 and 3 months (odds ratio=2.17, SE=0.46, p<0.001; and odds ratio=1.80, SE=0.40, p=0.008, respectively). AMS was associated with incomplete functional recovery at 1 month only (odds ratio=1.77, SE=0.37 p=0.007). No association was found between AMS and functional recovery in patients with no LOC. Neither LOC nor AMS was predictive of functional recovery at later times. CONCLUSIONS: These findings highlight the need to include symptom-focused clinical variables that pertain to the injury itself when assessing who might be at highest risk of incomplete functional recovery post-mTBI.

Age differences in outcome after mild traumatic brain injury: results from the HeadSMART study.

This study longitudinally examined age differences across multiple outcome domains in individuals diagnosed with acute mild traumatic brain injury (mTBI). A sample of 447 adults meeting VA/DoD criteria for mTBI was dichotomized by age into older (≥65 years; n = 88) and younger (<65 years; n = 359) sub-groups. All participants presented to the emergency department within 24 hours of sustaining a head injury, and outcomes were assessed at 1-, 3-, and 6-month intervals. Depressive symptoms were assessed using the Patient Health Questionnaire-9 (PHQ-9), post-concussive symptoms (PCS) were ascertained with the Rivermead Post-Concussion Questionnaire (RPQ), and functional recovery from the Extended Glasgow Outcome Scale (GOSE). Mixed effects logistic regression models showed that the rate of change over time in odds of functional improvement and symptom alleviation did not significantly differ between age groups (p = 0.200-0.088). Contrary to expectation, older adults showed equivalent outcome trajectories to younger persons across time. This is a compelling finding when viewed in light of the majority opinion that older adults are at risk for significantly worse outcomes. Future work is needed to identify the protective factors inherent to sub-groups of older individuals such as this.

Serum NfL (Neurofilament Light Chain) Levels and Incident Stroke in Adults With Diabetes Mellitus.

Background and Purpose- Effective stroke prevention depends on accurate stroke risk prediction. We determined the discriminative ability of NfL (neurofilament light chain) levels for distinguishing between adults with diabetes mellitus who develop incident stroke and those who remain stroke free during a 7-year follow-up period. Methods- We performed a case-control study of participants selected from the previously completed ACCORD trial (Action to Control Cardiovascular Risk in Diabetes). Cases were all ACCORD subjects who were stroke free at enrollment and developed incident stroke during follow-up (n=113). Control subjects (n=250) were randomly selected ACCORD subjects who had no stroke events either before or after randomization. NfL was measured in baseline samples using Single Molecule Array technology (Quanterix). Results- Baseline NfL levels were higher in stroke subjects, compared to controls, after adjusting for age, race, blood pressure, weight, and the Framingham Stroke Risk Score. Relative to the subjects in the lowest quintile of NfL levels, the hazard ratios of incident stroke for subjects in the second to fifth quintiles were 3.91 (1.45-10.53), 4.05 (1.52-10.79), 5.63 (2.16-14.66), and 9.75 (3.84-27.71), respectively, after adjusting for race and Framingham Stroke Risk Score. Incorporating NfL levels into a predictive score that already included race and Framingham Stroke Risk Score increased the score's C statistic from 0.71 (95% CI, 0.66-0.77) to 0.78 (95% CI, 0.73-0.83), P<0.001. Older age, nonwhite race, higher systolic blood pressure, glomerular filtration rate <60, and higher hemoglobin A1C were independent predictors of serum NfL in this cohort but diastolic blood pressure, durations of hypertension or diabetes mellitus, and lipid levels were not. In total, cardiovascular disease risk factors explained 19.2% of the variability in baseline NfL levels. Conclusions- Serum NfL levels predict incident stroke and add considerably to the discriminatory power of the Framingham Stroke Risk Score in a cohort of middle-aged and older adults with diabetes mellitus.

Loss of consciousness and altered mental state predicting depressive and post-concussive symptoms after mild traumatic brain injury.

Objective: Limited studies exist on the association between loss of consciousness (LOC) and altered mental state (AMS) and development of depressive and post-concussive symptoms within six months after mild traumatic brain injury (mTBI). We tested the hypothesis that presence of both LOC and AMS predict the highest risk of symptoms within the first six months post-mTBI compared to either variable alone, and that LOC alone is more strongly associated with these symptoms. Research design: We analyzed data from 407 subjects with mTBI from the Head injury Serum Markers for Assessing Response to Trauma (HeadSMART) cohort, a prospective cohort of patients post-TBI presenting to two urban emergency departments. Results: There were higher rates of depressive (44%) and post-concussive symptoms (54%) at 1 month post-injury, among participants with both LOC and AMS compared to other groups. AMS was associated with depressive symptoms at one and six months (OR = 1.59, p = .038; OR = 1.60; p = .060) and post-concussive symptoms at one month (OR = 1.56, p = .053). LOC was associated only with post-concussive symptoms at one month (OR = 1.55;p = .048). Among those without LOC, AMS was associated with depressive symptoms at one month (OR = 2.24; p = .028). Conclusions: AMS predicts post-mTBI depressive symptoms both in the acute and chronic mTBI phases whereas LOC is a more sensitive predictor of post-concussive symptoms in the acute mTBI period.

Influence of study population definition on the effect of age on outcomes after blunt head trauma.

OBJECTIVES: The purpose of this study was to assess whether study population definition influences the effect of age on outcomes after blunt head trauma. We hypothesized that examining 'all comers' receiving head computerized tomography after blunt head trauma, fewer older individuals would meet Veterans Administration and Department of Defense (VA/DoD) criteria for traumatic brain injury (TBI), and would, therefore, display better outcomes than younger cohorts. However, restricting to participants meeting VA/DoD criteria for TBI, we hypothesized that older individuals would have worse outcomes. METHODS: Data from a recently completed prospective cohort study were analysed with age dichotomized at 65 years. Logistic regression modelling, controlled for potential confounders including head trauma severity, was estimated to measure the effect of age on functional recovery, post-concussion symptoms (PCS), and depressive symptoms at 1-month post-TBI. RESULTS: Fewer older than younger individuals met VA/DoD criteria for TBI. Older individuals had better functional, PCS, and depressive outcomes at 1 month. Restricting to those meeting VA/DoD criteria for TBI, older individuals continued to have better functional and PCS outcomes but had outcomes comparable to younger on depressive symptoms. CONCLUSIONS: Contrary to our hypothesis, there was a tendency for older adults to have better outcomes than younger, independent of the diagnostic criteria applied.

Head injury serum markers for assessing response to trauma: Design of the HeadSMART study.

BACKGROUND: Accurate diagnosis and risk stratification of traumatic brain injury (TBI) at time of presentation remains a clinical challenge. The Head Injury Serum Markers for Assessing Response to Trauma study (HeadSMART) aims to examine blood-based biomarkers for diagnosing and determining prognosis in TBI. METHODS: HeadSMART is a 6-month prospective cohort study comparing emergency department patients evaluated for TBI (exposure group) to (1) emergency department patients evaluated for traumatic injury without head trauma and (2) healthy persons. Study methods and characteristics of the first 300 exposure participants are discussed. RESULTS: Of the first 300 participants in the exposure arm, 70% met the American Congress of Rehabilitation Medicine criteria for TBI, with the majority (80.1%) classified as mild TBI. The majority of subjects in the exposure arm had Glasgow Coma Scale scores of 13-15 (98.0%), normal head computed tomography (81.3%) and no prior history of concussion (71.7%). CONCLUSION: With systematic phenotyping, HeadSMART will facilitate diagnosis and risk-stratification of the heterogeneous group of individuals currently diagnosed with TBI.

Responses to glial cell line-derived neurotrophic factor change in mice as spermatogonial stem cells form progenitor spermatogonia which replicate and give rise to more differentiated progeny.

Spermatogonial stem cells (SSCs) are the foundation of spermatogenesis. These cells are classically defined as a subset of morphologically defined A single (As) spermatogonia, which can produce more SSCs or they can give rise to nonstem As cells that, upon replication, generate A paired (Apr) and then A aligned (Aal) spermatogonia. These latter two cell types, along with the nonstem As cells, function as transit-amplifying progenitor cells. It is known that glial cell line-derived neurotrophic factor (GDNF) is essential for maintaining all of these cells, but it is unknown if or how the responses of these cells change as they progress down the pathway to differentiated type A1 spermatogonia. We address this issue by using a chemical-genetic approach to inhibit GDNF signaling in vivo and an in vitro approach to increase GDNF stimulation. We show that inhibition for 2 days suppresses replication of As, Apr, and Aal spermatogonia to an equal extent, whereas stimulation by GDNF preferentially increases replication of As and Apr spermatogonia. We also test if inhibiting GDNF signaling causes As, Apr, and Aal spermatogonia to express Kit, an essential step in their differentiation into type A1 spermatogonia. Inhibition for 3 or 7 days produces a progressive increase in the percentages of As, Apr, and Aal undergoing differentiation, with the largest increase observed in Aal spermatogonia. Finally, we demonstrate that numbers of SSCs decrease more slowly than numbers of progenitor spermatogonia when GDNF signaling is inhibited. Taken together, these data suggest that there are significant changes in the responses to GDNF as SSCs give rise to progenitor spermatogonia, which replicate and gradually differentiate into type A1 spermatogonia.

A Prognostic Model for Predicting One-Month Outcomes among Emergency Department Patients with Mild Traumatic Brain Injury and a Presenting Glasgow Coma Scale of Fifteen.

The lack of well-performing prognostic models for early prognostication of outcomes remains a major barrier to improving the clinical care of patients with mild traumatic brain injury (mTBI). We aimed to derive a prognostic model for predicting incomplete recovery at 1-month in emergency department (ED) patients with mTBI and a presenting Glasgow Coma Scale (GCS) score of 15 who were enrolled in the HeadSMART (Head Injury Serum Markers for Assessing Response to Trauma) study. The derivation cohort included 355 participants with complete baseline (day-of-injury) and follow-up data. The primary outcome measure was the Glasgow Outcome Scale Extended (GOSE) at 1-month and incomplete recovery was defined as a GOSE <8. At 1-month post-injury, incomplete recovery was present in 58% (n = 205) of participants. The final multi-variable logistic regression model included six variables: age in years (odds ratio [OR] = 0.98; 95% confidence interval [CI]: 0.97-1.00), positive head CT (OR = 4.42; 95% CI: 2.21-9.33), history of depression (OR = 2.59; 95% CI: 1.47-4.69), and self-report of moderate or severe headache (OR = 2.49; 95% CI: 1.49-4.18), difficulty concentrating (OR = 3.17; 95% CI: 1.53-7.04), and photophobia (OR = 4.17; 95% CI: 2.08-8.92) on the day-of-injury. The model was validated internally using bootstrap resampling (1000 resamples), which revealed a mean over-optimism value of 0.01 and an optimism-corrected area under the curve (AUC) of 0.79 (95% CI: 0.75-0.85). A prognostic model for predicting incomplete recovery among ED patients with mTBI and a presenting GCS of 15 using easily obtainable clinical and demographic variables has acceptable discriminative accuracy. External validation of this model is warranted.

Teaching Python for Data Science: Collaborative development of a modular & interactive curriculum.

We are bioinformatics trainees at the University of Michigan who started a local chapter of Girls Who Code to provide a fun and supportive environment for high school women to learn the power of coding. Our goal was to cover basic coding topics and data science concepts through live coding and hands-on practice. However, we could not find a resource that exactly met our needs. Therefore, over the past three years, we have developed a curriculum and instructional format using Jupyter notebooks to effectively teach introductory Python for data science. This method, inspired by The Carpentries organization, uses bite-sized lessons followed by independent practice time to reinforce coding concepts, and culminates in a data science capstone project using real-world data. We believe our open curriculum is a valuable resource to the wider education community and hope that educators will use and improve our lessons, practice problems, and teaching best practices. Anyone can contribute to our Open Educational Resources on GitHub.

Poor sleep is linked to impeded recovery from traumatic brain injury.

Study Objectives: While disruptions in sleep are common after mild traumatic brain injury (TBI), the longitudinal relationships between sleep problems and global functioning after injury are poorly understood. Here, we prospectively investigate risk for functional impairment during the first 6 months of TBI recovery based on sleep onset insomnia symptoms and short sleep. Methods: Patients presenting to the Emergency Department (ED) at Johns Hopkins Hospital within 24 hours of head injury and evaluated for TBI were eligible for our study. Demographic and injury-related information were collected in the ED. Patients then completed in-person surveys and phone interviews to provide follow-up data on global functioning, sleep, and depressive symptoms at 1, 3, and 6 months post-injury. A total of 238 patients provided sufficient data for analysis, and hypotheses were tested using mixed effects modeling. Results: Sleep quality and global functioning improved over the 6 months of TBI recovery, but patients were at increased risk for functional impairment when sleeping poorly (odds ratio [OR] = 7.69, p < .001). Sleep onset insomnia symptoms and short sleep both independently corresponded to poor global functioning. Functional impairment was highest among those with both insomnia and short sleep (43%-79%) compared to good sleepers (15%-25%) and those with short sleep (29%-33%) or insomnia alone (33%-64%). A bidirectional relationship between sleep quality and functioning was observed. Conclusions: Functionally impaired patients diagnosed predominantly with mild TBI exhibit high rates of insomnia and short sleep, which may impede TBI recovery. Monitoring sleep after head injury may identify patients with poor prognoses and allow for early intervention to improve functional outcomes.

Prevalence of Incomplete Functional and Symptomatic Recovery among Patients with Head Injury but Brain Injury Debatable.

Head injury patients not meeting the American Congress of Rehabilitation Medicine (ACRM)'s criteria for mild traumatic brain injury (mTBI), referred to hereafter as HIBRID (Head Injury BRain Injury Debatable), are often excluded from studies. The prognostic importance of HIBRID is unclear. We investigated the differences in functional and symptomatic recovery at 1 month post-injury among TBI patients classified as: HIBRID, ACRM+ cranial computed tomography (CT)-, and cranial CT+; and trauma and healthy controls. Subjects were enrolled in an ongoing prospective cohort (Head Injury Serum Markers for Assessing Response to Trauma; HeadSMART). Outcomes measured at 1 month post-injury include: incomplete functional recovery (Glasgow Outcome Scale Extended <8); moderate/severe post-concussive symptoms (PCS), defined according to the International Statistical Classification of Diseases and Related Health Problems, Tenth Revision definition; and moderate/severe depressive symptoms (Patient Health Questionnaire 9 ≥ 10). Between April 2014 and May 2016, 500 TBI and 100 control subjects were enrolled and 376 TBI and 78 control subjects completed outcome assessment. The HIBRID group, constituting 23.9% of study population, had a lower incidence of incomplete functional recovery (36.7% [33 of 90]) than ACRM+, CT- (60.7% [125 of 206]; p < 0.01) and CT+ (78.8% [63 of 80]; p < 0.01) groups. However, the incidence of delayed functional recovery within the HIBRID group was higher than in trauma (9.3% [5 of 54]; p < 0.01) and healthy controls (0% [0 of 24]; p < 0.01). Compared to trauma/healthy controls, the HIBRID group had a higher incidence of moderate/severe depressive symptoms and a similar incidence of moderate/severe PCS. Subjects in the HIBRID group are at high risk for adverse outcomes following head injury and warrant further investigation.

A machine learning based approach for identifying traumatic brain injury patients for whom a head CT scan can be avoided.

Head CT scan is more often used to evaluate patients with suspected traumatic brain injury (TBI). However, the use of head CT scans in evaluating TBI is costly with low value endeavor. In this paper, we propose a new algorithm and a set of features to help clinicians determine which patients evaluated for TBI need a head CT scan using cost sensitive random forest (CSRF) classifier. We show that random forest (RF) and CSRF are useful methods for identifying patients likely to have a positive head CT scan. The proposed algorithm has superior diagnostic accuracy in comparison to the Canadian head CT algorithm, which is currently the most accurate and widely used algorithm for determining which TBI patients need a head CT scan. In the highest sensitivity (i.e. 100%), our method outperforms the Canadian rule in terms of specificity, accuracy and area under ROC curve using cost sensitive classifier. Clinical implementation of this algorithm can help decrease financial costs associated with Emergency Department evaluations for traumatic brain injury, while decreasing patient exposure to avoidable ionizing radiation.

Low high-sensitivity troponin I and zero coronary artery calcium score identifies coronary CT angiography candidates in whom further testing could be avoided.

RATIONALE AND OBJECTIVES: Pilot study to determine whether among subjects receiving coronary computed tomography angiography (CTA), the combination of high-sensitivity troponin I (hsTnI) and coronary artery calcium score (CACS) identifies a low-risk population in whom CTA might be avoided. MATERIALS AND METHODS: A cross-sectional study of 314 symptomatic patients receiving CTA as part of their acute coronary syndrome evaluation was conducted. hsTnI was measured with Abbott Laboratories' hsTnI assay. CACSs were calculated via the Agatston method. Patients were followed for at least 30 days after discharge for the occurrence of major adverse cardiac events (MACEs; all-cause mortality, acute coronary syndrome, and revascularization). RESULTS: Of 314 subjects studied, 213 (67.8%) had no coronary artery stenosis, and 67 (21.3%), 28 (8.9%), and 6 (1.9%) had maximal coronary artery stenosis of 1%-49%, 50%-69%, and 70% or greater, respectively. All MACEs occurred during index hospitalization and include one myocardial infarction and four revascularizations. Sixty-two percent (189/307) of subjects had zero CACS, and 24% (76/314) of subjects had undetected hsTnI. No subjects with undetectable hsTnI or zero CACS had an MACE. A strategy of avoiding further testing in subjects with undetectable initial hsTnI, performing CACS on subjects with detectable initial hsTnI but nonincreased hsTnI (less than 99th percentile), and obtaining CTA in subjects with Agatston greater than 0 will have a negative predictive value of 100.0% (95% confidence interval, 98.2%-100.0%). This strategy will avoid CTA in 63% (198/314) of subjects. CONCLUSIONS: In this pilot study, the addition of CACS to hsTnI improves the identification of low-risk subjects in whom CTA might be avoided.