Abstract Objective The gut microbiota (GM) plays a role in epilepsy development via the microbiota–gut–brain axis. However, its relationship with various epilepsy subtypes and its mediating role through immune cells remain unclear. Thus, identifying the GM linked to specific epilepsy subtypes and investigating immune mechanisms to predict epilepsy risk, tailor treatments, and monitor outcomes are crucial. Methods We performed a two‐sample Mendelian randomization (MR) study focused on the relationships between different epilepsy subtypes associated with the GM and the mediating role of immune cells between different epilepsy subtypes and the GM. Genome‐wide association analysis summary statistics of 412 GM species (GCST90027446–GCST90027857) and 731 immune cell phenotypes (GCST90001391–GCST90002121), along with summary statistics of different subtypes of epilepsy, were used in a publicly available genome‐wide association analysis. Significantly associated single‐nucleotide polymorphism (SNP) loci were extracted as instrumental variables according to preset thresholds, with an inverse variance weighted (IVW) model being the main model. Additionally, MR‐Egger regression, weighted median, weighted, and simple models were also used for analysis. Results MR analyses revealed the relationships of the GM and immune cells with diverse epilepsy subtypes, with no statistically significant effect of different epilepsy subtypes on the GM after correction for multiple testing via the false discovery rate (FDR) approach. Notably, one bacterial species, Gordonibacter pamelaeae, with an uncorrected low p‐value (OR: 1.0136, 95% CI: 1.0048–1.0225, p = 0.0025), was positively related to childhood absence epilepsy (CAE). Among immune cells, CD4+ ACs (OR: 1.0152, 95% CI: 1.0067–1.0238, p = 0.0005) were strongly related to CAE. Additionally, mediated effect analysis revealed that seven types of GM mediate the effects of eight immune cells on epilepsy, with Bacteroides caccae mediating CD33br HLA DR+ CD14dim AC cells producing the greatest effect on generalized epilepsy. Significance The above results demonstrate the close association between specific GM and specific immune cells in epilepsy and can be used to inform the treatment of different epilepsy subtypes by modulating the GM and immune cells. Plain Language Summary This study investigated the relationships between the gut microbiota and different epilepsy subtypes and the mediating role of immune cells. These findings emphasize that there is a close association between specific gut microbiota and specific immune cells in epilepsy and that they can be used to inform the treatment of different epilepsy subtypes by modulating the gut microbiota and immune cells.
Abstract Introduction Acute ischemic stroke (AIS) significantly contributes to severe disability and mortality among the elderly. This study aims to explore the association between longitudinal fluid balance (FB) trajectories and clinical outcomes in elderly patients with AIS. Our hypothesis posits the existence of multiple latent trajectories of FB in patients with AIS during the initial 7 days following ICU admission. Methods Patients (age ≥ 65 years) with AIS and continuous FB records were identified from two large databases. Group-based trajectory modeling identified latent groups with similar 7-day FB trajectories. Subsequently, multivariable logistic and quasi-Poisson regression were employed to evaluate the relationship between trajectory groups and outcomes. Additionally, nonlinear associations between maximum fluid overload (FO) and outcomes were analyzed using restricted cubic spline models. To further validate our findings, subgroup and sensitivity analysis were conducted. Results A total of 1146 eligible patients were included in this study, revealing three trajectory patterns were identified: low FB (84.8%), decreasing FB (7.2%), and high FB (7.9%). High FB emerged as an independent risk factor for in-hospital mortality. Compared with those without FO, patients with FO had a 1.57-fold increased risk of hospital mortality (adjusted odd ratio (OR) 1.57, 95% confidence interval (CI) 1.08–2.27), 2.37-fold increased risk of adverse kidney event (adjusted OR 2.37, 95% CI 1.56–3.59), and 1.33-fold increased risk of prolonged ICU stay (adjusted incidence rate ratio (IRR) 1.33, 95% CI 1.19–1.48). The risk of hospital mortality and adverse kidney event increased linearly with rising maximum FO (P for non-linearity = 0.263 and 0.563, respectively). Conclusion Daily FB trajectories were associated with adverse outcomes in elderly patients with AIS. Regular assessment of daily fluid status and restriction of FO are crucial for the recovery of critically ill patients.
Vanessa Loss Volpatto, Jaqueline Bohrer Schuch, Francisco Diego Rabelo-da-Ponte
et al.
Objective: This study investigated the relationship between impulsivity and early trauma through a network analysis in individuals diagnosed with different substance use disorders. Methods: In a cross-sectional design, the sample included 556 men with substance use disorders (195 with alcohol use, 157 with cocaine/crack use, and 214 with polysubstance use). Early trauma and impulsive behavior were assessed using the Childhood Trauma Questionnaire and the Barratt Impulsiveness Scale, respectively. The connection between trauma and impulsivity was assessed using network analysis through a fused graphical lasso algorithm. Results: No connection was observed between impulsivity and trauma networks in individuals with alcohol use disorder. In those with cocaine use disorder, networks were linked through the motor domain and sexual abuse nodes. Inverse connections were observed between the emotional neglect node and perseverance, but not the non-planning node. In polysubstance use, the connection between impulsivity and trauma networks was weak, with the cognitive complexity node connecting to the trauma network through physical abuse. There connections were inversely proportional between the motor domain and emotional neglect nodes, as well as between cognitive instability and physical neglect. Conclusion: Our results suggest that the relationship between the type of early (childhood) trauma and the expression of impulsivity could lead to different substance use profiles.
Astrid Gieselmann, Astrid Gieselmann, Jakov Gather
et al.
BackgroundAdvance research directives (ARDs) provide a promising way to involve individuals with mild cognitive impairment (MCI) in research decisions before they lose the capacity to consent. At the same time, the views of people with MCI on ARDs are underexplored. This study assesses the perceptions of people with MCI and family members on the benefits and challenges associated with ARDs.AimsThe aim of this study was to investigate the perspectives of individuals with MCI and family members of individuals with MCI on ARDs. We focus specifically on willingness to participate in nontherapeutic research, understanding of ARDs and the ethical considerations involved.MethodsThirteen open-ended, face-to-face interviews were conducted using a semi-structured format. Seven interviews were conducted with individuals with MCI, and six with family members of individuals with MCI. The narratives were transcribed verbatim and qualitative content analysis was carried out.ResultsResearch participation and ARDs were viewed positively, largely based on altruistic motives and the desire to contribute to society. The participants recognized the potential advantages of ARDs in reducing the decision-making burden on family members and maintaining personal autonomy. They also highlighted challenges in comprehending ARDs and navigating the complexities surrounding potential conflicts between current preferences versus preferences described in an ARD.ConclusionsARDs were predominantly seen as valuable instruments that enable individuals with MCI to participate in research. This study provides insights into the reasons why affected individuals are interested in drafting ARDs. These insights can guide the development of supportive interventions that are tailored to assist individuals with MCI and their families in navigating ARD processes.
Neuroproteomics, an emerging field at the intersection of neuroscience and proteomics, has garnered significant attention in the context of neurotrauma research. Neuroproteomics involves the quantitative and qualitative analysis of nervous system components, essential for understanding the dynamic events involved in the vast areas of neuroscience, including, but not limited to, neuropsychiatric disorders, neurodegenerative disorders, mental illness, traumatic brain injury, chronic traumatic encephalopathy, and other neurodegenerative diseases. With advancements in mass spectrometry coupled with bioinformatics and systems biology, neuroproteomics has led to the development of innovative techniques such as microproteomics, single-cell proteomics, and imaging mass spectrometry, which have significantly impacted neuronal biomarker research. By analyzing the complex protein interactions and alterations that occur in the injured brain, neuroproteomics provides valuable insights into the pathophysiological mechanisms underlying neurotrauma. This review explores how such insights can be harnessed to advance personalized medicine (PM) approaches, tailoring treatments based on individual patient profiles. Additionally, we highlight the potential future prospects of neuroproteomics, such as identifying novel biomarkers and developing targeted therapies by employing artificial intelligence (AI) and machine learning (ML). By shedding light on neurotrauma’s current state and future directions, this review aims to stimulate further research and collaboration in this promising and transformative field.
BackgroundDeep-vein thrombosis (DVT) is a common complication of acute stroke (AS). Only limited studies have discussed DVT in patients with AS at admission to a rehabilitation unit. The purpose of this study is to identify the predictors of DVT in AS patients admitted to a rehabilitation unit in China.MethodsWe retrospectively reviewed the medical records of all patients with AS admitted within 14 days of stroke onset between July 2019 and June 2022 at the Department of Rehabilitation Medicine, Xuanwu Hospital, Capital Medical University, China. Ultrasonography was used to diagnose DVT in all patients within 3 days after rehabilitation admission. Univariate and binary logistic regression analyses were performed to determine the risk factors for DVT.ResultsOverall, 234 cases were identified and the incidence rate of DVT among AS patients was 13.2% (31/234). The univariate analysis showed that age, drinking, lower limb muscle strength, Brunnstrom Assessment (BRS), Fugl-Meyer Assessment (FMA), Berg Balance Scale (BBS), Barthel Index (BI) scale, serum albumin (Alb), and D-dimer were statistically significant factors. Age (OR = 1.037, 95% CI = 1.000–1.075, p < 0.05), BBS (OR = 0.952, 95% CI = 0.913–0.993, p < 0.05), and D-dimer (OR = 1.446, 95% CI = 1.130–1.849, p < 0.05) were demonstrated as independent risk factors for DVT.ConclusionOlder age, lower BBS, and higher D-dimer levels at rehabilitation admission were independent risk factors for DVT. Therefore, ultrasonography should be performed for those patients with these three significant factors before implementing rehabilitation therapy.
Kongyuan Wu, Zhengzhou Yuan, Zhengzhou Yuan
et al.
IntroductionEarly neurological deterioration (END) is common in acute ischemic stroke and is directly associated with poor outcome after stroke. Our aim is to develop and validate a nomogram to predict the risk of END after mechanical thrombectomy (MT) in acute ischemic stroke patients with anterior circulation large-vessel occlusion.MethodsWe conducted a real-world, multi-center study in patients with stroke treated with mechanical thrombectomy. END was defined as a worsening by 2 or more NIHSS points within 72-hour after stroke onset compared to admission. Multivariable logistic regression was used to determine the independent predictors of END, and the discrimination of the scale was assessed using the C-index. Calibration curves were constructed to evaluate the calibration of the nomogram, and decision curves were used to describe the benefits of using the nomogram.ResultsA total of 1007 patients were included in our study. Multivariate logistic regression analysis found age, admission systolic blood pressure, initial NIHSS scores, history of hyperlipemia, and location of occlusion were independent predictors of END. We developed a nomogram that included these 6 factors, and it revealed a prognostic accuracy with a C-index of 0.678 in the derivation group and 0.650 in the validation group. The calibration curves showed that the nomogram provided a good fit to the data, and the decision curves demonstrated a large net benefit.DiscussionOur study established and validated a nomogram to stratify the risk of END before mechanical embolectomy and identify high-risk patients, who should be more cautious when making clinical decisions.
Shalini Bassi, Shalini Bassi, Gaurang P. Nazar
et al.
BackgroundThe world witnessed a highly contagious and deadly disease, COVID-19, toward the end of 2019. India is one of the worst affected countries. We aimed to assess anxiety and depression levels among adult tobacco users and people who recently quit tobacco during COVID-19 lockdown in India.Materials and methodsThe study was conducted across two Indian cities, Delhi and Chennai (July-August, 2020) among adult tobacco users (n = 801). Telephonic interviews were conducted using validated mental health tools (Patient Health Questionnaire-PHQ-9 and Generalized Anxiety Disorder-GAD-7) to assess the anxiety and depression levels of the participants. Descriptive analysis and multiple logistic regression were used to study the prevalence and correlates of depression and anxiety.ResultsWe found that 20.6% of tobacco users had depression symptoms (3.9% moderate to severe); 20.7% had anxiety symptoms (3.8% moderate to severe). Risk factors associated with depression and anxiety included food, housing, and financial insecurity.ConclusionDuring COVID-19 lockdown, mental health of tobacco users (primarily women) was associated with food, housing and financial insecurity. The Indian Government rightly initiated several health, social and economic measures to shield the most vulnerable from COVID-19, including a ban on the sale of tobacco products. It is also necessary to prioritize universal health coverage, expanded social security net, tobacco cessation and mental health services to such vulnerable populations during pandemic situations.
Elisa Kaltenbach, Michelle Chisholm, Ting Xiong
et al.
Background: Parents of children with intellectual and neurodevelopmental disorders (IDD) often experience traumatic events in the care of their children. This leads to comparatively high numbers of mental health problems such as posttraumatic stress disorder (PTSD) in those parents. Intervention approaches for parents of children with IDD are scarce and many parents remain without support. Objective: This study aims to test the feasibility and efficacy of online Narrative Exposure Therapy (eNET) with parents of children with IDD. Methods: The study follows a randomized waitlist-control design. eNET is an exposure-based PTSD intervention and includes 8–12 90-minute sessions. All sessions will be conducted via video calls with trained paraprofessionals. We aim to include 50 parents, approximately 25 in the immediate intervention group and 25 in the waitlist group. Waitlist participants will receive the same intervention after a three-month wait period. All participants need to either fulfill full or subclinical PTSD symptoms according to DSM-5. Feasibility and efficacy of the intervention will be measured with pre, post, and 2 and 6 months follow-up surveys focusing on PTSD symptoms. Secondary outcomes include other health-related outcomes such as physical symptoms, depression symptoms, anxiety symptoms and functionality. Conclusions: The proposed study allows us to test the feasibility and efficacy of eNET in a sample of parents of children with IDD. There are so far no published studies on the evidence of eNET; this study is one of the first randomized controlled trials investigating the feasibility and efficacy of eNET and therefore will have implications on further research and practice. Clinical trial registration: NCT04385927 Date and version identifier: 22 July 2021
Rosina Giordano-Santini, Eva Kaulich, Kate M Galbraith
et al.
Significance Ramón y Cajal’s neuron doctrine, which states that neurons are individual cells that do not share any membrane or cytoplasmic continuity between them, has underpinned our view of modern neuroscience. However, there is considerable evidence that fusogens, specialized proteins essential and sufficient for the fusion of cells in other tissues, are expressed in the nervous system of several species in response to viral infection, stress conditions, and neurological disease. By manipulating the expression of fusogens in the chemosensory neurons of Caenorhabditis elegans, our results provide conclusive evidence that deregulation of fusogen expression causes neuronal fusion and can have deleterious effects on neural circuitry and behavioral outputs, revealing a possible novel underlying cause of neurological disorders. The 100-y-old neuron doctrine from Ramón y Cajal states that neurons are individual cells, rejecting the process of cell−cell fusion in the normal development and function of the nervous system. However, fusogens—specialized molecules essential and sufficient for the fusion of cells—are expressed in the nervous system of different species under conditions of viral infection, stress, or disease. Despite these findings, whether the expression of fusogens in neurons leads to cell−cell fusion, and, if so, whether this affects neuronal fate, function, and animal behavior, has not been explored. Here, using Caenorhabditis elegans chemosensory neurons as a model system, we provide proof-of-principle that aberrant expression of fusogens in neurons results in neuron−neuron fusion and behavioral impairments. We demonstrate that fusion between chemoattractive neurons does not affect the response to odorants, whereas fusion between chemoattractive and chemorepulsive neurons compromises chemosensation. Moreover, we provide evidence that fused neurons are viable and retain their original specific neuronal fate markers. Finally, analysis of calcium transients reveals that fused neurons become electrically coupled, thereby compromising neural circuit connectivity. Thus, we propose that aberrant expression of fusogens in the nervous system disrupts neuronal individuality, which, in turn, leads to a change in neural circuit connectivity and disruption of normal behavior. Our results expose a previously uncharacterized basis of circuit malfunction, and a possible underlying cause of neurological diseases.
Smoking is a complex behavior with a heritability as high as 50%. Given such a large genetic contribution, it provides an opportunity to prevent those individuals who are susceptible to smoking dependence from ever starting to smoke by predicting their inherited predisposition with their genomic profiles. Although previous studies have identified many susceptibility variants for smoking, they have limited power to predict smoking behavior. We applied the support vector machine (SVM) and random forest (RF) methods to build prediction models for smoking behavior. We first used 1,431 smokers and 1,503 non-smokers of African origin for model building with a 10-fold cross-validation and then tested the prediction models on an independent dataset consisting of 213 smokers and 224 non-smokers. The SVM model with 500 top single nucleotide polymorphisms (SNPs) selected using logistic regression (p<0.01) as the feature selection method achieved an area under the curve (AUC) of 0.691, 0.721, and 0.720 for the training, test, and independent test samples, respectively. The RF model with 500 top SNPs selected using logistic regression (p<0.01) achieved AUCs of 0.671, 0.665, and 0.667 for the training, test, and independent test samples, respectively. Finally, we used the combined logistic (p<0.01) and LASSO (λ=10−3) regression to select features and the SVM algorithm for model building. The SVM model with 500 top SNPs achieved AUCs of 0.756, 0.776, and 0.897 for the training, test, and independent test samples, respectively. We conclude that machine learning methods are promising means to build predictive models for smoking.
Abstract Background The lack of universally accepted diagnostic criteria and the high rate of psychiatric comorbidity make it difficult to diagnose Fetal Alcohol Spectrum Disorder (FASD). In an effort to improve the diagnosis of FASD, the current study aimed to identify a neurodevelopmental profile that is both sensitive and specific to FASD. Methods A secondary analysis was conducted on data obtained from the Canadian component of the World Health Organization International Study on the Prevalence of FASD. Data on neurodevelopmental status and behavior were derived from a battery of standardized tests and the Child Behavior Checklist for 21 children with FASD, 28 children with other neurodevelopmental disorders, and 37 typically developing control children, aged 7 to 11 years. Two latent profile analyses were performed to derive discriminative profiles: i) children with FASD compared with typically developing control children, and ii) children with FASD compared with typically developing control children and children with other neurodevelopmental disorders. The classification function of the resulting profiles was evaluated using the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). Confidence intervals (CIs) were approximated using 10,000 bootstrapped samples. Results The neurodevelopmental profile of FASD tested consisted of impairments in perceptual reasoning, verbal comprehension, visual-motor speed and motor coordination, processing speed (nonverbal information), attention and executive function, visuospatial processing, and language, in combination with rule-breaking behavior and attention problems. When children with FASD were compared with typically developing control children, a 2-class model fit the data best and resulted in a sensitivity of 95.2% (95% CI: 84.2–100.0%), specificity of 89.2% (95% CI: 78.4–97.5%), PPV of 83.3% (95% CI: 66.7–96.2%), and NPV of 97.1% (95% CI: 90.3–100.0%). When children with FASD were compared with typically developing control children and children with other neurodevelopmental disorders, the neurodevelopmental profile correctly identified only 56.9% (95% CI: 45.1–69.2%) of typically developing children and children with other neurodevelopmental disorders as not having FASD, and thus the profile was found not to be specific to children with FASD. Conclusion The findings question the uniqueness of children with FASD with respect to their neurodevelopmental impairments and behavioral manifestations.
Krista D. DiSano, Michael R. Linzey, Darlene B. Royce
et al.
Abstract Background The mechanisms driving multiple sclerosis (MS), the most common cause of non-traumatic disability in young adults, remain unknown despite extensive research. Especially puzzling are the underlying molecular processes behind the two major disease patterns of MS: relapsing-remitting and progressive. The relapsing-remitting course is exemplified by acute inflammatory attacks, whereas progressive MS is characterized by neurodegeneration on a background of mild-moderate inflammation. The molecular and cellular features differentiating the two patterns are still unclear, and the role of inflammation during progressive disease is a subject of active debate. Methods We performed a comprehensive analysis of the intrathecal inflammation in two clinically distinct mouse models of MS: the PLP139-151-induced relapsing experimental autoimmune encephalomyelitis (R-EAE) and the chronic progressive, Theiler’s murine encephalomyelitis virus-induced demyelinating disease (TMEV-IDD). Microarray technology was first used to examine global gene expression changes in the spinal cord. Inflammation in the spinal cord was further assessed by immunohistochemical image analysis and flow cytometry. Levels of serum and cerebrospinal fluid (CSF) immunoglobulin (Ig) isotypes and chemokines were quantitated using Luminex Multiplex technology, whereas a capture ELISA was used to measure serum and CSF albumin levels. Finally, an intrathecal Ig synthesis index was established with the ratio of CSF and serum test results corrected as a ratio of their albumin concentrations. Results Microarray analysis identified an enrichment of B cell- and Ig-related genes upregulated in TMEV-IDD mice. We also demonstrated an increased level of intrathecal Ig synthesis as well as a marked infiltration of late differentiated B cells, including antibody secreting cells (ASC), in the spinal cord of TMEV-IDD, but not R-EAE mice. An intact blood-brain barrier in TMEV-IDD mice along with higher CSF levels of CXCL13, CXCL12, and CCL19 provides evidence for an intrathecal synthesis of chemokines mediating B cell localization to the central nervous system (CNS). Conclusions Overall, these findings, showing increased concentrations of intrathecally produced Igs, substantial infiltration of ASC, and the presence of B cell supporting chemokines in the CNS of TMEV-IDD mice, but not R-EAE mice, suggest a potentially important role for Igs and ASC in the chronic progressive phase of demyelinating diseases.
Cecilia Higgs, James E. Hilbert, Libby Wood
et al.
Introduction: Recent evidence demonstrates that women with myotonic dystrophy type 1 are at increased risk of reproductive organ tumors. However, studies of reproductive cancer risk factors in those patients are lacking.Methods: Using questionnaires, we collected and analyzed personal history information related to cancer risk factors from women enrolled in a UK and US registry for myotonic dystrophy (dystrophia myotonica; DM) patients.Results: The survey was completed by 242 DM type 1 (DM1) and 44 DM type 2 (DM2) women enrolled in the UK Registry (N = 124) and the US National Registry (N = 162). The mean age at DM1 diagnosis was 33.8 years (standard deviation, SD = 13.2) and for DM2 was 49.2 (SD = 13.0). Mean age at survey was 48.7 (SD = 12.8) and 59.1 years (SD = 12.8) for DM1 and DM2, respectively. There were no statistically significant differences between DM1 and DM2 regarding menstrual history or fertility-related factors. Yet, women with DM2 were more likely to have used menopausal hormone therapy (HT) than women with DM1 (52.3 vs. 22.1%, p < 0.0001), and more women with DM2 had a hysterectomy (53.5 vs. 29.5%, p < 0.01). These differences were not statistically significant after age adjustment (OR = 2.00, p = 0.08, and OR = 1.40, p = 0.38, respectively). The frequency of self-reported reproductive organ tumors was not significantly different comparing DM1 to DM2 (p = 0.28). However, the data suggested that women with DM2 appear to have a lower risk of malignant tumors compared to those with DM1 (OR = 0.72, p = 0.69).Discussion: Our study is the first to characterize a wide range of reproductive risk factors in women with DM. We observed no significant differences between DM1 and DM2 in the factors that were evaluated, which suggests that the known excesses of ovarian and endometrial cancer previously reported in women with DM1 cannot be attributed to greater prevalence of standard cancer-related reproductive risk factors. Larger studies evaluating the possible link between reproductive cancer risk factors and risk of tumors in women with DM are needed.
Hannah M. Lindsey, Hannah M. Lindsey, Elisabeth A. Wilde
et al.
Traumatic brain injury (TBI) is a leading cause of death and disability for children and adolescents in the U.S. and other developed and developing countries. Injury to the immature brain varies greatly from that of the mature, adult brain due to numerous developmental, pre-injury, and injury-related factors that work together to influence the trajectory of recovery during the course of typical brain development. Substantial damage to brain structure often underlies subsequent functional limitations that persist for years following pediatric TBI. Advances in neuroimaging have established an important role in the acute management of pediatric TBI, and magnetic resonance imaging (MRI) techniques have a particular relevance for the sequential assessment of long-term consequences from injuries sustained to the developing brain. The present paper will discuss the various factors that influence recovery and review the findings from the present neuroimaging literature to assess altered development and long-term outcome following pediatric TBI. Four MR-based neuroimaging modalities have been used to examine recovery from pediatric TBI longitudinally: (1) T1-weighted structural MRI is sensitive to morphological changes in gray matter volume and cortical thickness, (2) diffusion-weighted MRI is sensitive to changes in the microstructural integrity of white matter, (3) MR spectroscopy provides a sensitive assessment of metabolic and neurochemical alterations in the brain, and (4) functional MRI provides insight into the functional changes that occur as a result of structural damage and typical developmental processes. As reviewed in this paper, 13 cohorts have contributed to only 20 studies published to date using neuroimaging to examine longitudinal changes after TBI in pediatric patients. The results of these studies demonstrate considerable heterogeneity in post-injury outcome; however, the existing literature consistently shows that alterations in brain structure, function, and metabolism can persist for an extended period of time post-injury. With larger sample sizes and multi-site cooperation, future studies will be able to further examine potential moderators of outcome, such as the developmental, pre-injury, and injury-related factors discussed in the present review.