Association of Biomarkers of Neuronal Injury and Inflammation With Insomnia Trajectories After Traumatic Brain Injury: A TRACK-TBI Study.

BACKGROUND AND OBJECTIVES: Insomnia affects about one-third of patients with traumatic brain injury and is associated with worsened outcomes after injury. We hypothesized that higher levels of plasma neuroinflammation biomarkers at the time of TBI would be associated with worse 12-month insomnia trajectories. METHODS: Participants were prospectively enrolled from 18 level-1 trauma centers participating in the Transforming Research and Clinical Knowledge in Traumatic Brain Injury study from February 26, 2014, to August 8, 2018. Plasma glial fibrillary acidic protein (GFAP), high-sensitivity C-reactive protein (hsCRP), S100b, neuron-specific enolase (NSE), and ubiquitin carboxyl-terminal hydrolase-L1 (UCH-L1) were collected on days 1 (D1) and 14 (D14) after TBI. The insomnia severity index was collected at 2 weeks, 3, 6, and 12 months postinjury. Participants were classified into insomnia trajectory classes based on a latent class model. We assessed the association of biomarkers with insomnia trajectories, controlling for medical and psychological comorbidities and demographics. RESULTS: Two thousand twenty-two individuals with TBI were studied. Elevations in D1 hsCRP were associated with persistent insomnia (severe, odds ratio [OR] = 1.33 [1.11, 1.59], p = 0.002; mild, OR = 1.10 [1.02, 1.19], p = 0.011). Similarly, D14 hsCRP elevations were associated with persistent insomnia (severe, OR = 1.27 [1.02, 1.59], p = 0.03). Of interest, D1 GFAP was lower in persistent severe insomnia (median [Q1, Q3]: 154 [19, 445] pg/mL) compared with resolving mild (491 [154, 1,423], p < 0.001) and persistent mild (344 [79, 1,287], p < 0.001). D14 GFAP was similarly lower in persistent (11.8 [6.4, 19.4], p = 0.001) and resolving (13.9 [10.3, 20.7], p = 0.011) severe insomnia compared with resolving mild (20.6 [12.4, 39.6]. Accordingly, increases in D1 GFAP were associated with reduced likelihood of having persistent severe (OR = 0.76 [95% CI 0.63-0.92], p = 0.004) and persistent mild (OR = 0.88 [0.81, 0.96], p = 0.003) compared with mild resolving insomnia. No differences were found with other biomarkers. DISCUSSION: Elevated plasma hsCRP and, surprisingly, lower GFAP were associated with adverse insomnia trajectories after TBI. Results support future prospective studies to examine their utility in guiding insomnia care after TBI. Further work is needed to explore potential mechanistic connections between GFAP levels and the adverse insomnia trajectories.

Performance of the IMPACT and CRASH prognostic models for traumatic brain injury in a contemporary multicenter cohort: a TRACK-TBI study.

OBJECTIVE: The International Mission on Prognosis and Analysis of Clinical Trials in Traumatic Brain Injury (IMPACT) and Corticosteroid Randomization After Significant Head Injury (CRASH) prognostic models for mortality and outcome after traumatic brain injury (TBI) were developed using data from 1984 to 2004. This study examined IMPACT and CRASH model performances in a contemporary cohort of US patients. METHODS: The prospective 18-center Transforming Research and Clinical Knowledge in Traumatic Brain Injury (TRACK-TBI) study (enrollment years 2014-2018) enrolled subjects aged ≥ 17 years who presented to level I trauma centers and received head CT within 24 hours of TBI. Data were extracted from the subjects who met the model criteria (for IMPACT, Glasgow Coma Scale [GCS] score 3-12 with 6-month Glasgow Outcome Scale-Extended [GOSE] data [n = 441]; for CRASH, GCS score 3-14 with 2-week mortality data and 6-month GOSE data [n = 831]). Analyses were conducted in the overall cohort and stratified on the basis of TBI severity (severe/moderate/mild TBI defined as GCS score 3-8/9-12/13-14), age (17-64 years or ≥ 65 years), and the 5 top enrolling sites. Unfavorable outcome was defined as GOSE score 1-4. Original IMPACT and CRASH model coefficients were applied, and model performances were assessed by calibration (intercept [< 0 indicated overprediction; > 0 indicated underprediction] and slope) and discrimination (c-statistic). RESULTS: Overall, the IMPACT models overpredicted mortality (intercept -0.79 [95% CI -1.05 to -0.53], slope 1.37 [1.05-1.69]) and acceptably predicted unfavorable outcome (intercept 0.07 [-0.14 to 0.29], slope 1.19 [0.96-1.42]), with good discrimination (c-statistics 0.84 and 0.83, respectively). The CRASH models overpredicted mortality (intercept -1.06 [-1.36 to -0.75], slope 0.96 [0.79-1.14]) and unfavorable outcome (intercept -0.60 [-0.78 to -0.41], slope 1.20 [1.03-1.37]), with good discrimination (c-statistics 0.92 and 0.88, respectively). IMPACT overpredicted mortality and acceptably predicted unfavorable outcome in the severe and moderate TBI subgroups, with good discrimination (c-statistic ≥ 0.81). CRASH overpredicted mortality in the severe and moderate TBI subgroups and acceptably predicted mortality in the mild TBI subgroup, with good discrimination (c-statistic ≥ 0.86); unfavorable outcome was overpredicted in the severe and mild TBI subgroups with adequate discrimination (c-statistic ≥ 0.78), whereas calibration was nonlinear in the moderate TBI subgroup. In subjects ≥ 65 years of age, the models performed variably (IMPACT-mortality, intercept 0.28, slope 0.68, and c-statistic 0.68; CRASH-unfavorable outcome, intercept -0.97, slope 1.32, and c-statistic 0.88; nonlinear calibration for IMPACT-unfavorable outcome and CRASH-mortality). Model performance differences were observed across the top enrolling sites for mortality and unfavorable outcome. CONCLUSIONS: The IMPACT and CRASH models adequately discriminated mortality and unfavorable outcome. Observed overestimations of mortality and unfavorable outcome underscore the need to update prognostic models to incorporate contemporary changes in TBI management and case-mix. Investigations to elucidate the relationships between increased survival, outcome, treatment intensity, and site-specific practices will be relevant to improve models in specific TBI subpopulations (e.g., older adults), which may benefit from the inclusion of blood-based biomarkers, neuroimaging features, and treatment data.

Isolated Traumatic Subarachnoid Hemorrhage on Head Computed Tomography Scan May Not Be Isolated: A TRACK-TBI Study.

Isolated traumatic subarachnoid hemorrhage (tSAH) after traumatic brain injury (TBI) on head computed tomography (CT) scan is often regarded as a "mild" injury, with reduced need for additional workup. However, tSAH is also a predictor of incomplete recovery and unfavorable outcome. This study aimed to evaluate the characteristics of CT-occult intracranial injuries on brain magnetic resonance imaging (MRI) scan in TBI patients with emergency department (ED) arrival Glasgow Coma Scale (GCS) score 13-15 and isolated tSAH on CT. The prospective, 18-center Transforming Research and Clinical Knowledge in Traumatic Brain Injury Study (TRACK-TBI; enrollment years 2014-2019) enrolled participants who presented to the ED and received a clinically-indicated head CT within 24 hours (h) of TBI. A subset of TRACK-TBI participants underwent venipuncture within 24h for plasma glial fibrillary acidic protein (GFAP) analysis, and research MRI at 2-weeks post-injury. In the current study, TRACK-TBI participants aged ≥17 years with ED arrival GCS 13-15, isolated tSAH on initial head CT, plasma GFAP level, and 2-week MRI data were analyzed. In 57 participants, median age was 46.0 years [quartile 1 to 3 (Q1-Q3): 34-57] and 52.6% were male. At ED disposition, 12.3% were discharged home, 61.4% were admitted to hospital ward, and 26.3% to intensive care unit. MRI identified CT-occult traumatic intracranial lesions in 45.6% (26 of 57 participants; 1 additional lesion type: 31.6%; 2 additional lesion types: 14.0%); of these 26 participants with CT-occult intracranial lesions, 65.4% had axonal injury, 42.3% had subdural hematoma, and 23.1% had intracerebral contusion. GFAP levels were higher in participants with CT-occult MRI lesions compared to without (median: 630.6 pg/ml, Q1-Q3: [172.4-941.2] vs. 226.4 [105.8-436.1], p=0.049), and were associated with axonal injury (no: median 226.7 pg/ml [109.6-435.1], yes: 828.6 pg/ml [204.0-1194.3], p=0.009). Our results indicate that isolated tSAH on head CT is often not the sole intracranial traumatic injury in GCS 13-15 TBI. Forty-six percent of patients in our cohort (26 of 57 participants) had additional CT-occult traumatic lesions on MRI. Plasma GFAP may be an important biomarker for the identification of additional CT-occult injuries, including axonal injury. These findings should be interpreted cautiously given our modest sample size and await validation from larger studies.

Polygenic risk for suicide attempt is associated with lifetime suicide attempt in US soldiers independent of parental risk.

BACKGROUND: Suicide is a leading cause of death worldwide. Whereas some studies have suggested that a direct measure of common genetic liability for suicide attempts (SA), captured by a polygenic risk score for SA (SA-PRS), explains risk independent of parental history, further confirmation would be useful. Even more unsettled is the extent to which SA-PRS is associated with lifetime non-suicidal self-injury (NSSI). METHODS: We used summary statistics from the largest available GWAS study of SA to generate SA-PRS for two non-overlapping cohorts of soldiers of European ancestry. These were tested in multivariable models that included parental major depressive disorder (MDD) and parental SA. RESULTS: In the first cohort, 417 (6.3 %) of 6573 soldiers reported lifetime SA and 1195 (18.2 %) reported lifetime NSSI. In a multivariable model that included parental history of MDD and parental history of SA, SA-PRS remained significantly associated with lifetime SA [aOR = 1.26, 95%CI:1.13-1.39, p < 0.001] per standardized unit SA-PRS]. In the second cohort, 204 (4.2 %) of 4900 soldiers reported lifetime SA, and 299 (6.1 %) reported lifetime NSSI. In a multivariable model that included parental history of MDD and parental history of SA, SA-PRS remained significantly associated with lifetime SA [aOR = 1.20, 95%CI:1.04-1.38, p = 0.014]. A combined analysis of both cohorts yielded similar results. In neither cohort or in the combined analysis was SA-PRS significantly associated with NSSI. CONCLUSIONS: PRS for SA conveys information about likelihood of lifetime SA (but not NSSI, demonstrating specificity), independent of self-reported parental history of MDD and parental history of SA. LIMITATIONS: At present, the magnitude of effects is small and would not be immediately useful for clinical decision-making or risk-stratified prevention initiatives, but this may be expected to improve with further iterations. Also critical will be the extension of these findings to more diverse populations.

Diagnostic Utility of Glial Fibrillary Acidic Protein Beyond 12 Hours After Traumatic Brain Injury: A TRACK-TBI Study.

Blood levels of glial fibrillary acidic protein (GFAP) and ubiquitin carboxyl-terminal hydrolase-L1 (UCH-L1) within 12h of suspected traumatic brain injury (TBI) have been approved by the Food and Drug administration to aid in determining the need for a brain computed tomography (CT) scan. The current study aimed to determine whether this context of use can be expanded beyond 12h post-TBI in patients presenting with Glasgow Coma Scale (GCS) 13-15. The prospective, 18-center Transforming Research and Clinical Knowledge in Traumatic Brain Injury (TRACK-TBI) study enrolled TBI participants aged ≥17 years who presented to a United States Level 1 trauma center and received a clinically indicated brain CT scan within 24h post-injury, a blood draw within 24h and at 14 days for biomarker analysis. Data from participants with emergency department arrival GCS 13-15 and biomarker values at days 1 and 14 were extracted for the primary analysis. A subgroup of hospitalized participants with serial biomarkers at days 1, 3, 5, and 14 were analyzed, including plasma GFAP and UCH-L1, and serum neuron-specific enolase (NSE) and S100 calcium-binding protein B (S100B). The primary analysis compared biomarker values dichotomized by head CT results (CT+/CT-). Area under receiver-operating characteristic curve (AUC) was used to determine diagnostic accuracy. The overall cohort included 1142 participants with initial GCS 13-15, with mean age 39.8 years, 65% male, and 73% Caucasian. The GFAP provided good discrimination in the overall cohort at days 1 (AUC = 0.82) and 14 (AUC = 0.72), and in the hospitalized subgroup at days 1 (AUC = 0.84), 3 (AUC = 0.88), 5 (AUC = 0.82), and 14 (AUC = 0.74). The UCH-L1, NSE, and S100B did not perform well (AUC = 0.51-0.57 across time points). This study demonstrates the utility of GFAP to aid in decision-making for diagnostic brain CT imaging beyond the 12h time frame in patients with TBI who have a GCS 13-15.

Effects of a hospital discharge clinic among people with HIV: Lack of early follow-up is associated with 30-day hospital readmission and decreased retention in care.

BACKGROUND: The transition between inpatient and outpatient care for hospitalized people with HIV represents an opportunity for linkage and re-engagement in care. We evaluated whether attendance at a post-hospitalization visit ('discharge clinic') within 1-2 weeks of discharge would reduce readmissions and improve retention in care (RIC) among people with HIV in San Diego, California, USA. METHODS: This was a retrospective cohort study of people with HIV hospitalized between June 2020 and November 2021. Our primary outcome was 30-day readmissions among people with HIV who did or did not attend a discharge clinic visit. Secondary outcomes included the effect of discharge clinic attendance on RIC, along with the impact of attendance at any HIV clinic visit within 30 days of discharge on readmissions and RIC. RESULTS: We evaluated 114 people with HIV, of whom 77 (67.5%) and 90 (78.9%) attended a discharge clinic visit or any HIV clinic visit within 30 days of discharge, respectively. Active substance use disorder (SUD) was associated with failing to attend a discharge clinic visit (odds ratio 0.31; 95% confidence interval 0.13-0.77). We observed no significant differences in readmissions between people with HIV who did or did not attend a discharge clinic visit; however, the former had significantly higher 6-month RIC (79.2% vs. 35.1%, p < 0.001). People with HIV attending any HIV clinic visit within 30 days of discharge had significantly fewer 30-day readmissions (8.9% vs. 29.2%, p = 0.02) and better 6-month RIC (75.6% vs. 25%, p < 0.001) than those who did not attend. CONCLUSION: Early hospital follow-up care was associated with a reduction in readmissions among people with HIV. Active SUD was a significant barrier to linkage to outpatient follow-up and RIC.

Amplification of Positivity Treatment for Anxiety and Depression: A Randomized Experimental Therapeutics Trial Targeting Social Reward Sensitivity to Enhance Social Connectedness.

BACKGROUND: Social disconnection is common and causes significant impairment in anxiety and depressive disorders, and it does not respond sufficiently to available treatments. The positive valence system supports social bond formation and maintenance but is often hyporesponsive in people with anxiety or depression. We conducted an experimental therapeutics trial to test the hypothesis that targeting positive valence processes through cognitive and behavioral strategies would enhance responsivity to social rewards, a core mechanism underlying social connectedness. METHODS: Sixty-eight adults who endorsed clinically elevated anxiety and/or depression with social impairment were randomized 1:1:1 to 5 (n = 23) or 10 (n = 22) sessions of amplification of positivity (AMP) treatment or waitlist (n = 23). Pre- to posttreatment change in striatal activity (primary outcome) during social reward anticipation was measured using functional magnetic resonance imaging, and reactivity to a social affiliation task (secondary) and self-reported social connectedness (exploratory) were examined. Primary analyses compared AMP (doses combined) versus waitlist. A second aim was to compare the effects of different doses. RESULTS: AMP engaged the hypothesized treatment target, leading to greater striatal activation during anticipation of social rewards versus waitlist (d = 1.01 [95% CI = 0.42-1.61]; largest striatal volume). AMP yielded larger improvements in positive affect and approach behavior during the affiliation task (but not other outcomes) and social connectedness. Larger striatal and social connectedness increases were observed for 5-session versus 10-session AMP (d range = 0.08-1.03). CONCLUSIONS: Teaching people with anxiety or depression strategies to increase positive thoughts, behaviors, and emotions enhances activity in brain regions that govern social reward processing and promotes social connectedness. Social reward sensitivity may be a transdiagnostic target for remediating social disconnection.

Addressing sequential and concurrent treatment regimens in a small n sequential, multiple assignment, randomized trial (snSMART) in the MISTIC study.

Multisystem Inflammatory Syndrome in children (MIS-C) is a rare and novel pediatric complication linked to COVID-19 exposure, which was first identified in April 2020. A small n, Sequential, Multiple Assignment, Randomized Trial (snSMART) was applied to the Multisystem Inflammatory Syndrome Therapies in Children Comparative Effectiveness Study (MISTIC) to efficiently evaluate multiple competing treatments. In the MISTIC snSMART study, participants are randomized to one of three interventions (steroids, infliximab or anakinra), and potentially re-randomized to the remaining two treatments depending on their response to the first randomized treatment. However, given the novelty and urgency of the MIS-C disease, in addition to patient welfare concerns, treatments were not always administered sequentially, but allowed to be administered concurrently if deemed medically necessary. We propose a pragmatic modification to the original snSMART design to address the analysis of concurrent versus sequential treatments in the MISTIC study. A modified Bayesian joint stage model is developed that can distinguish a concurrent treatment effect from a sequential treatment effect. A simulation study is conducted to demonstrate the improved accuracy and efficiency of the primary aim to estimate the first stage treatments' response rates and the secondary aim to estimate the combined first and second stage treatments' responses in the proposed model compared to the standard snSMART Bayesian joint stage model. We observed that the modified model has improved efficiency in terms of bias and rMSE under large sample size settings.

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.

Association Between Insomnia and Mental Health and Neurocognitive Outcomes Following Traumatic Brain Injury.

We previously described five trajectories of insomnia (each defined by a distinct pattern of insomnia severity over 12 months following traumatic brain injury [TBI]). Our objective in the present study was to estimate the association between insomnia trajectory status and trajectories of mental health and neurocognitive outcomes during the 12 months after TBI. In this study, participants included N = 2022 adults from the Federal Inter-agency Traumatic Brain Injury Repository database and Transforming Research and Clinical Knowledge in TBI (TRACK-TBI) study. The following outcome measures were assessed serially at 2 weeks, and 3, 6, and 12 months post-injury: Insomnia Severity Index, Patient Health Questionnaire, Post-Traumatic Stress Disorder (PTSD) Checklist for Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5), Patient Reported Outcomes Measurement Information System-Pain, and Quality of Life After Brain Injury-Overall Scale. Neurocognitive performance was assessed at 2 weeks, and 6 and 12 months using the Wechsler Adult Intelligence Scales Processing Speed Index and the Trails Making Test Parts A and B. Results indicated that greater insomnia severity was associated with greater abnormality in mental health, quality of life, and neuropsychological testing outcomes. The pattern of insomnia over time tracked the temporal pattern of all these outcomes for all but a very small number of participants. Notably, severe insomnia at 3 or 6 months post-TBI was a risk factor for poor recovery at 12 months post-injury. In conclusion, in this well-characterized sample of individuals with TBI, insomnia severity generally tracked severity of depression, pain, PTSD, quality of life, and neurocognitive outcomes over 12 months post-injury. More intensive sleep assessment is needed to elucidate the nature of these relationships and to help inform best strategies for intervention.

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.

Development and Validation of a Machine Learning Prediction Model of Posttraumatic Stress Disorder After Military Deployment.

Importance: Military deployment involves significant risk for life-threatening experiences that can lead to posttraumatic stress disorder (PTSD). Accurate predeployment prediction of PTSD risk may facilitate the development of targeted intervention strategies to enhance resilience. Objective: To develop and validate a machine learning (ML) model to predict postdeployment PTSD. Design, Setting, and Participants: This diagnostic/prognostic study included 4771 soldiers from 3 US Army brigade combat teams who completed assessments between January 9, 2012, and May 1, 2014. Predeployment assessments occurred 1 to 2 months before deployment to Afghanistan, and follow-up assessments occurred approximately 3 and 9 months post deployment. Machine learning models to predict postdeployment PTSD were developed in the first 2 recruited cohorts using as many as 801 predeployment predictors from comprehensive self-report assessments. In the development phase, cross-validated performance metrics and predictor parsimony were considered to select an optimal model. Next, the selected model's performance was evaluated with area under the receiver operating characteristics curve and expected calibration error in a temporally and geographically distinct cohort. Data analyses were performed from August 1 to November 30, 2022. Main Outcomes and Measures: Posttraumatic stress disorder diagnosis was assessed by clinically calibrated self-report measures. Participants were weighted in all analyses to address potential biases related to cohort selection and follow-up nonresponse. Results: This study included 4771 participants (mean [SD] age, 26.9 [6.2] years), 4440 (94.7%) of whom were men. In terms of race and ethnicity, 144 participants (2.8%) identified as American Indian or Alaska Native, 242 (4.8%) as Asian, 556 (13.3%) as Black or African American, 885 (18.3%) as Hispanic, 106 (2.1%) as Native Hawaiian or other Pacific Islander, 3474 (72.2%) as White, and 430 (8.9%) as other or unknown race or ethnicity; participants could identify as of more than 1 race or ethnicity. A total of 746 participants (15.4%) met PTSD criteria post deployment. In the development phase, models had comparable performance (log loss range, 0.372-0.375; area under the curve range, 0.75-0.76). A gradient-boosting machine with 58 core predictors was selected over an elastic net with 196 predictors and a stacked ensemble of ML models with 801 predictors. In the independent test cohort, the gradient-boosting machine had an area under the curve of 0.74 (95% CI, 0.71-0.77) and low expected calibration error of 0.032 (95% CI, 0.020-0.046). Approximately one-third of participants with the highest risk accounted for 62.4% (95% CI, 56.5%-67.9%) of the PTSD cases. Core predictors cut across 17 distinct domains: stressful experiences, social network, substance use, childhood or adolescence, unit experiences, health, injuries, irritability or anger, personality, emotional problems, resilience, treatment, anxiety, attention or concentration, family history, mood, and religion. Conclusions and Relevance: In this diagnostic/prognostic study of US Army soldiers, an ML model was developed to predict postdeployment PTSD risk with self-reported information collected before deployment. The optimal model showed good performance in a temporally and geographically distinct validation sample. These results indicate that predeployment stratification of PTSD risk is feasible and may facilitate the development of targeted prevention and early intervention strategies.

Latent polydrug use patterns and the provision of injection initiation assistance among people who inject drugs in three North American settings.

INTRODUCTION: We sought to identify latent profiles of polysubstance use patterns among people who inject drugs in three distinct North American settings, and then determine whether profile membership was associated with providing injection initiation assistance to injection-naïve persons. METHODS: Cross-sectional data from three linked cohorts in Vancouver, Canada; Tijuana, Mexico; and San Diego, USA were used to conduct separate latent profile analyses based on recent (i.e., past 6 months) injection and non-injection drug use frequency. We then assessed the association between polysubstance use patterns and recent injection initiation assistance provision using logistic regression analyses. RESULTS: A 6-class model for Vancouver participants, a 4-class model for Tijuana participants and a 4-class model for San Diego participants were selected based on statistical indices of fit and interpretability. In all settings, at least one profile included high-frequency polysubstance use of crystal methamphetamine and heroin. In Vancouver, several profiles were associated with a greater likelihood of providing recent injection initiation assistance compared to the referent profile (low-frequency use of all drugs) in unadjusted and adjusted analyses, however, the inclusion of latent profile membership in the multivariable model did not significantly improve model fit. DISCUSSION AND CONCLUSIONS: We identified commonalities and differences in polysubstance use patterns among people who inject drugs in three settings disproportionately impacted by injection drug use. Our results also suggest that other factors may be of greater priority when tailoring interventions to reduce the incidence of injection initiation. These findings can aid in efforts to identify and support specific higher-risk subpopulations of people who inject drugs.

Association of body anthropometry and obstructive sleep apnea in children: Variations observed in Hispanic children.

Objectives: Obesity is a risk factor for obstructive sleep apnea (OSA) in children. Childhood obesity rates vary amongst different ethnic groups. Here the interaction of Hispanic ethnicity and obesity on OSA risk was evaluated. Methods: Retrospective cross-sectional analysis of consecutive children undergoing polysomnography and anthropometry using bioelectrical impedance from 2017 to 2020. Demographics obtained from the medical chart. Children who had also undergone cardiometabolic testing were identified and the relationship of cardiometabolic markers with OSA and anthropometry was assessed. Results: Data from 1217 children revealed Hispanic children were more likely to have moderate-severe OSA (36.0%) compared to Non-Hispanic children (26.5%), p < 0.001. Hispanic children had greater Body mass index (BMI), BMI percentile and percent body fat, p < 0.0001. In children that underwent cardiometabolic testing, Hispanic children had significantly greater serum alanine aminotransferase levels (ALT) levels. Following adjustment of age and sex, Hispanic ethnicity was not found to moderate the association of anthropometry with OSA, anthropometry with cardiometabolic markers, and OSA with cardiometabolic markers. Conclusions: OSA was more likely in Hispanic children; this relationship was likely driven by obesity status rather than ethnicity. Among children undergoing cardiometabolic testing, Hispanic children were observed to have greater ALT concentrations however ethnicity did not impact the association of anthropometry and ALT or other cardiometabolic markers.

In the era of universal test and treat in Uganda, recent intimate partner violence is not associated with subsequent ART use or viral suppression.

Intimate partner violence (IPV) has been associated with delays throughout the HIV care continuum. This study explored prospective associations between experiences of past-year IPV and two HIV care outcomes in the context of current universal test and treat guidelines using two consecutive rounds of an ongoing HIV surveillance study conducted in the Rakai region of Uganda. Longitudinal logistic regression models examined associations between IPV, use of antiretroviral therapy (ART) and viral load suppression (VS), adjusting for outcome variables at baseline. To address differences in ART retention by IPV, propensity scores were used to create inverse-probability-of-treatment-and-censoring-weighted (IPTCW) models. At baseline, of 1923 women with HIV (WWH), 34.6%, 26.5%, 13.5% reported past-year verbal, physical and sexual IPV; a lower proportion of persons who experienced physical IPV (79.4%) were VS than those who did not (84.3%; p = 0.01). The proportion VS at baseline also significantly differed by exposure to verbal IPV (p = 0.03). However, in adjusted longitudinal models, IPV was not associated with lower odds of ART use or VS at follow-up. Among WWH in the Rakai region, IPV does not appear to be a barrier to subsequent ART use or VS. However, given the prevalence of IPV in this population, interventions are needed.

Genetic, environmental, and behavioral correlates of lifetime suicide attempt: Analysis of additive and interactive effects in two cohorts of US Army soldiers.

Recently developed measures of genetic liability to suicide attempt may convey unique information regarding an individual's risk of suicidal behavior. We calculated a polygenic risk score for suicide attempt (SA-PRS) for soldiers of European ancestry who participated in the Army STARRS New Soldier Study (NSS; n = 6573) or Pre/Post Deployment Study (PPDS; n = 4900). Multivariable logistic regression models were fit within each sample to estimate the association of SA-PRS with lifetime suicide attempt (LSA), and to examine whether SA-PRS displayed additive or interactive effects with environmental and behavioral risk/protective factors (lifetime trauma burden, childhood maltreatment, negative urgency impulsivity, social network size, perceived mattering, and dispositional optimism). Age, sex, and within-ancestry variation were included as covariates. Observed prevalence of LSA was 6.3% and 4.2% in the NSS and PPDS samples, respectively. In the NSS model, SA-PRS and environmental/behavioral factors displayed strictly additive effects on odds of LSA. Results indicated an estimated 21% increase in odds of LSA per 1 SD increase in SA-PRS [adjusted odds ratio (AOR; 95% CI) = 1.21 (1.09-1.35)]. In PPDS, the effect of SA-PRS varied by reports of optimism [AOR = 0.85 (0.74-0.98) for SA-PRS x optimism effect]. Individuals reporting low and average optimism had 37% and 16% increased odds of LSA per 1 SD increase in SA-PRS, respectively, whereas SA-PRS was not associated with LSA in those reporting high optimism. Overall, results suggested the SA-PRS had predictive value over and above several environmental and behavioral risk factors for LSA. Moreover, elevated SA-PRS may be more concerning in the presence of environmental and behavioral risk factors (e.g., high trauma burden; low optimism). Given the relatively small effect magnitudes, the cost and incremental benefits of utilizing SA-PRS for risk targeting must also be considered in future work.

Infliximab for intensification of primary therapy for patients with Kawasaki disease and coronary artery aneurysms at diagnosis.

OBJECTIVE: Children with Kawasaki disease (KD) and an initial echocardiogram that demonstrates coronary artery aneurysms (CAAs, Z score ≥2.5) are at high risk for severe cardiovascular complications. We sought to determine if primary adjunctive infliximab treatment at a dose of either 5 or 10 mg/kg, compared with intravenous immunoglobulin (IVIG) alone, is associated with a greater likelihood of CAA regression in patients with KD with CAA at the time of diagnosis. DESIGN AND SETTING: Single-centre observational study. PATIENTS: Children with acute KD and Z score ≥2.5 at baseline. INTERVENTIONS: Primary adjunctive infliximab (5 or 10 mg/kg) within 48 hours of initiating IVIG 2 g/kg. MAIN OUTCOME MEASURES: Incidence of CAA regression to Zmax <2 within 2 months of disease onset. RESULTS: Of the 168 patients with KD, 111 received IVIG alone and 57 received primary adjunctive infliximab therapy: 39 received 5 mg/kg and 18 received 10 mg/kg. Incidence of CAA regression to Zmax <2 within 2 months was statistically significant at 52%, 62% and 83% in the IVIG alone, IVIG+infliximab 5 mg/kg and IVIG+infliximab 10 mg/kg, respectively. The multivariable logistic regression model adjusting for age, sex, baseline Zmax and bilateral CAA at baseline showed that IVIG plus 10 mg/kg infliximab was significantly associated with a greater likelihood of CAA regression (adjusted OR: 4.45, 95% CI 1.17 to 16.89, p=0.028) compared with IVIG alone. The difference between IVIG+infliximab 5 mg/kg and IVIG alone was not significant. CONCLUSIONS: Primary adjunctive high-dose 10 mg/kg infliximab treatment was associated with a greater likelihood of CAA regression in patients with CAA at the time of diagnosis.

Associations of Microvascular Injury-Related Biomarkers With Traumatic Brain Injury Severity and Outcomes: A Transforming Research and Clinical Knowledge in Traumatic Brain Injury (TRACK-TBI) Pilot Study.

Traumatic brain injury (TBI) is characterized by heterogeneity in terms of injury severity, mechanism, outcome, and pathophysiology. A single biomarker alone is unlikely to capture the heterogeneity of even one injury subtype, necessitating the use of panels of biomarkers. Herein, we focus on traumatic cerebrovascular injury and investigate associations of a panel of 16 vascular injury-related biomarkers with indices of TBI severity and outcomes using data from 159 participants in the Transforming Research and Clinical Knowledge in TBI (TRACK-TBI) Pilot Study. Associations of individual biomarkers and clusters of biomarkers identified using non-linear principal components analysis with TBI severity and outcomes were assessed using logistic regression models and Spearman's correlations. As individual biomarkers, higher levels of thrombomodulin, angiopoietin (Ang)-2, von Willebrand factor, and P-selectin were associated with more severe injury; higher levels of Ang-1, Tie2, vascular endothelial growth factor (VEGF)-C, and basic fibroblast growth factor (bFGF) were associated with less severe injury (all p < 0.05 in age-adjusted models). After false discovery rate correction for multiple comparisons, higher levels of Ang-2 remained associated with more severe injury and higher levels of Ang-1, Tie2, and bFGF remained associated with less severe injury at a p < 0.05 level. In principal components analysis, principal component (PC)1, comprised of Ang1, bFGF, P-selectin, VEGF-C, VEGF-A, and Tie2, was associated with less severe injury (age-adjusted odds ratio [OR]: 0.63, 95% confidence interval [CI]: 0.44-0.88 for head computer tomography [CT] positive vs. negative) and PC2 (Ang-2, E-selectin, Flt-1, placental growth factor, thrombomodulin, and vascular cell adhesion protein 1) was associated with greater injury severity (age-adjusted OR: 2.29, 95% CI: 1.49-3.69 for Glasgow Coma Scale [GCS] 3-12 vs. 13-15 and age-adjusted OR 1.59, 95% CI: 1.11-2.32 for head CT positive vs. negative). Neither individual biomarkers nor PCs were associated with outcomes in adjusted models (all p > 0.05). In conclusion, in this trauma-center based population of acute TBI patients, biomarkers of microvascular injury were associated with TBI severity.

Hepatitis C Virus Micro-elimination Among People With HIV in San Diego: Are We on Track?

Background: Rising incidence of hepatitis C virus (HCV) among people with HIV (PWH) in San Diego County (SDC) was reported. In 2018, the University of California San Diego (UCSD) launched a micro-elimination initiative among PWH, and in 2020 SDC launched an initiative to reduce HCV incidence by 80% across 2015-2030. We model the impact of observed treatment scale-up on HCV micro-elimination among PWH in SDC. Methods: A model of HCV transmission among people who inject drugs (PWID) and men who have sex with men (MSM) was calibrated to SDC. The model was additionally stratified by age, gender, and HIV status. The model was calibrated to HCV viremia prevalence among PWH in 2010, 2018, and 2021 (42.1%, 18.5%, and 8.5%, respectively), and HCV seroprevalence among PWID aged 18-39 years, MSM, and MSM with HIV in 2015. We simulate treatment among PWH, weighted by UCSD Owen Clinic (reaching 26% of HCV-infected PWH) and non-UCSD treatment, calibrated to achieve the observed HCV viremia prevalence. We simulated HCV incidence with observed and further treatment scale-up (+/- risk reductions) among PWH. Results: Observed treatment scale-up from 2018 to 2021 will reduce HCV incidence among PWH in SDC from a mean of 429 infections/year in 2015 to 159 infections/year in 2030. County-wide scale-up to the maximum treatment rate achieved at UCSD Owen Clinic (in 2021) will reduce incidence by 69%, missing the 80% incidence reduction target by 2030 unless accompanied by behavioral risk reductions. Conclusions: As SDC progresses toward HCV micro-elimination among PWH, a comprehensive treatment and risk reduction approach is necessary to reach 2030 targets.

Prospective Association of Unmet Mental Health Treatment Needs With Suicidal Behavior Among Combat-Deployed Soldiers.

OBJECTIVE: Military personnel frequently report discontinuing or not pursuing psychiatric treatment despite perceiving a need for services. This study aimed to examine how unmet need for treatment or support among U.S. Army soldiers relates to future suicidal ideation (SI) or suicide attempt (SA). METHODS: Mental health treatment need and help seeking in the past 12 months were evaluated for soldiers (N=4,645) who subsequently deployed to Afghanistan. Weighted logistic regression models were used to examine the prospective association of predeployment treatment needs with SI and SA during and after deployment, with adjustment for potential confounders. RESULTS: Compared with soldiers without predeployment treatment needs, those who reported not seeking help despite needing it had increased risk for SI during deployment (adjusted OR [AOR]=1.73), past-30-day SI at 2-3 months postdeployment (AOR=2.08), past-30-day SI at 8-9 months postdeployment (AOR=2.01), and SA through 8-9 months postdeployment (AOR=3.65). Soldiers who sought help and stopped treatment without improvement had elevated SI risk at 2-3 months postdeployment (AOR=2.35). Those who sought help and stopped after improving did not have increased SI risk during or 2-3 months after deployment but had elevated risks for SI (AOR=1.71) and SA (AOR=3.43) by 8-9 months postdeployment. Risks for all suicidality outcomes were also elevated among soldiers who reported receiving ongoing treatment before deployment. CONCLUSIONS: Unmet or ongoing needs for mental health treatment or support before deployment are associated with increased risk for suicidal behavior during and after deployment. Detecting and addressing treatment needs among soldiers before deployment may help prevent suicidality during deployment and reintegration periods.