POST-TRAUMATIC STRESS DISORDER IN POLY-TRAUMA CASES.
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ABSTRACT:
SUBMITTER: Saldanha D
PROVIDER: S-EPMC5530272 | biostudies-other | 1996 Jan
REPOSITORIES: biostudies-other
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Project description:Post-traumatic stress disorder (PTSD) and mild traumatic brain injury (mTBI) are highly prevalent and closely related disorders. Affected individuals often exhibit substantially overlapping symptomatology - a major challenge for differential diagnosis in both military and civilian contexts. According to our symptom assessment, the PTSD group exhibited comparable levels of concussion symptoms and severity to the mTBI group. An objective and reliable system to uncover the key neural signatures differentiating these disorders would be an important step towards translational and applied clinical use. Here we explore use of MEG (magnetoencephalography)-multivariate statistical learning analysis in identifying the neural features for differential PTSD/mTBI characterisation. Resting state MEG-derived regional neural activity and coherence (or functional connectivity) across seven canonical neural oscillation frequencies (delta to high gamma) were used. The selected features were consistent and largely confirmatory with previously established neurophysiological markers for the two disorders. For regional power from theta, alpha and high gamma bands, the amygdala, hippocampus and temporal areas were identified. In line with regional activity, additional connections within the occipital, parietal and temporal regions were selected across a number of frequency bands. This study is the first to employ MEG-derived neural features to reliably and differentially stratify the two disorders in a multi-group context. The features from alpha and beta bands exhibited the best classification performance, even in cases where distinction by concussion symptom profiles alone were extremely difficult. We demonstrate the potential of using 'invisible' neural indices of brain functioning to understand and differentiate these debilitating conditions.
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Project description:A greater understanding of why some people are more at risk of developing PTSD is required. We examine the relationship between temperament traits in early childhood and subsequent trauma exposure and risk of PTSD. We used data on 2017 participants from the Avon Longitudinal Study of Parents and Children (ALSPAC). Temperament was measured using the Carey Infant Temperament Scale (average score from ages 6 and 24 months). This provided data on 9 individuals traits, and Easy, Medium, and Difficult temperament clusters. Trauma exposure was measured from 0 to 17 years, and PTSD at age 23 years using the PTSD Checklist for DSM-V (PCL-5). Regression models were used to estimate associations between temperament and both trauma and PTSD, and to examine mediation (of temperament to PTSD pathway) and interaction (temperament X trauma on PTSD) effects. 1178 (58.4%) individuals were exposed to a trauma in childhood and 112 (5.5%) had PTSD. Higher levels of Intensity were associated with a small increase in trauma exposure (ORadjusted 1.23, 95% CI 1.12, 1.34; p < 0.001) and PTSD (ORadjusted 1.27, 95% CI 1.05, 1.54; p = 0.012). Higher levels of Activity, Adaptability, Mood and Threshold temperament traits were also associated with trauma exposure. Medium (ORadjusted 1.49, 95% CI 1.21, 1.84; p < 0.001) and Difficult (ORadjusted 1.47, 95% CI 1.18, 1.84; p = 0.001) temperament clusters were associated with increased trauma exposure compared to an Easy cluster, but were not associated with PTSD. The relationship between trait Intensity and adult PTSD was partially mediated by childhood/adolescent trauma (Indirect ORadjusted 1.08, 95% CI 1.01, 1.16, p = 0.024, proportion mediated 26.2%). There was some evidence that trait Intensity modified the relationship between trauma and PTSD (ORadjusted 1.66, 95% CI 1.07, 2.55, p = 0.023). PTSD in early adulthood is more common in those with intense stimuli responsiveness in childhood. Temperament traits might be useful predictors of trauma exposure and mental health outcomes and offer potential targets for supportive interventions.
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Project description:BackgroundPosttraumatic stress disorder (PTSD) is one of the most prevalent mental disorders in war-affected regions. Syria has endured 9 years of war and yet little is known about the impact of the conflict on the well-being of Syrians who remain. In this study, we investigated trauma and estimated PTSD prevalence among university students in Deir-ez-Zor, a Syrian governorate that was under the siege by ISIS for over 3 years.MethodsA descriptive cross-sectional study design was used on a sample of Al-Furat university students in Deir-ez-Zor. We collected data on socio-demographics, trauma exposure, and stress levels. PTSD Checklist for DSM-5 was used to provide prevalence rate estimates, and determine the symptom severity among Syrian university students. Binary logistic regression was used to identify factors associated with the development of PTSD symptoms.ResultsA total of 833 students were recruited into the study, 86.4% of the participants were exposed to at least one traumatic event. The estimated PTSD prevalence was 28.2%, and the highest PTSD rates were found among students who were forced into sexual act (46.3%). A significant association was found between PTSD and internal displacement (p = .032), academic year (p = .002), and social economic status (p = .000). Binary logistic regression indicated that PTSD symptoms were predicted by smoking and third-year university students.ConclusionsThe results presented in this research revealed a high prevalence of trauma exposure and PTSD symptoms among a sample of university students in Deir-ez-Zor. These findings call for immediate actions to help the affected population in restoring their mental health, so they can be prepared to face the challenges and demands of the post-conflict period.
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Project description:Post-traumatic stress disorder (PTSD) is a debilitating psychiatric disorder. It can be difficult to discern the symptoms of PTSD and obtain an accurate diagnosis. Different magnetic resonance imaging (MRI) modalities focus on different aspects, which may provide complementary information for PTSD discrimination. However, none of the published studies assessed the diagnostic potential of multimodal MRI in identifying individuals with and without PTSD. In the current study, we investigated whether the complementary information conveyed by multimodal MRI scans could be combined to improve PTSD classification performance. Structural and resting-state functional MRI (rs-fMRI) scans were conducted on 17 PTSD patients, 20 trauma-exposed controls without PTSD (TEC) and 20 non-traumatized healthy controls (HC). Gray matter volume (GMV), amplitude of low-frequency fluctuations (ALFF), and regional homogeneity were extracted as classification features, and in order to integrate the information of structural and functional MRI data, the extracted features were combined by a multi-kernel combination strategy. Then a support vector machine (SVM) classifier was trained to distinguish the subjects at individual level. The performance of the classifier was evaluated using the leave-one-out cross-validation (LOOCV) method. In the pairwise comparison of PTSD, TEC, and HC groups, classification accuracies obtained by the proposed approach were 2.70, 2.50, and 2.71% higher than the best single feature way, with the accuracies of 89.19, 90.00, and 67.57% for PTSD vs. HC, TEC vs. HC, and PTSD vs. TEC respectively. The proposed approach could improve PTSD identification at individual level. Additionally, it provides preliminary support to develop the multimodal MRI method as a clinical diagnostic aid.
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Project description:The present study investigated the psychopathological processes of post-traumatic stress disorder (PTSD) following the network approach to psychopathology. The directed acyclic graph model was employed to analyse a large longitudinal data-set of Chinese children and adolescents exposed to a destructive earthquake. It was found that intrusion symptoms were first activated by trauma exposure, and subsequently activated other PTSD symptoms. The data are consistent with the idea that symptoms may form a self-sustaining dynamic network by interacting with each other to promote or maintain the chronicity of PTSD. The findings advance the current understanding about the psychopathological processes of PTSD, and inform further research and clinical practices on post-traumatic psychopathology.
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Project description:Women have a higher prevalence of post-traumatic stress disorder (PTSD) than men, with a peak during the reproductive years. PTSD during pregnancy adversely impacts maternal and infant health outcomes. The objectives of this study were to estimate the prevalence of antepartum PTSD symptoms in a population of pregnant Peruvian women and to examine the impact of number of traumatic events and type of trauma experienced. The Traumatic Events Questionnaire was used to collect data about traumatic exposures. The Post-traumatic Stress Disorder Checklist-Civilian Version (PCL-C) was used to assess PTSD. Multivariable logistic regression procedures were used to estimate adjusted odds ratios (aOR) and 95% confidence intervals (95% CI). Three thousand three hundred seventy-two pregnant women were interviewed. Of the 2920 who reported experiencing one or more traumatic events, 41.8% met criteria for PTSD (PCL-C score ≥ 26). A quarter of participants had experienced four or more traumas, and 60.5% of those women had PTSD. Interpersonal trauma was most strongly associated with PTSD (aOR, 3.20; 95% CI, 2.74-3.74), followed by unspeakable trauma (aOR, 2.87; 95% CI, 2.35-3.50), and structural trauma (aOR, 1.39; 95% CI, 1.15-1.67). These findings indicate the high prevalence of PTSD during pregnancy in the Peruvian population, which is relevant to other countries suffering from terrorism, war, or high rates of violence. This underscores the importance of screening for PTSD in pregnancy.
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Project description:Background: Developmental trauma disorder (DTD) has been proposed to describe the biopsychosocial sequelae of exposure to interpersonal victimization in childhood that extend beyond the symptoms of post-traumatic stress disorder (PTSD). Objective: To characterize the psychopathology comorbid with DTD and to determine whether this comorbidity is distinct from, and extends beyond, comorbidities of PTSD. Method: DTD was assessed by structured interview, and probable Diagnostic and Statistical Manual of Mental Disorders, 4th Edition (DSM-IV) psychiatric disorders were identified with screening modules on the Kiddie Schedule for Affective Disorders and Schizophrenia, Present/Lifetime version (K-SADS-PL), in a multi-site sample of 236 children (7-18 years old; 50% female) referred by paediatric or mental health providers. Results: DTD (N = 80, 34%) and PTSD (N = 69, 29%) were highly comorbid and shared several DSM-IV internalizing disorder and DSM, 5th Edition (DSM-5) dysregulation disorder comorbidities. However, DTD, but not PTSD, was associated with comorbid panic disorder and disruptive behaviour disorders. On a multivariate basis including all probable DSM-IV disorders and DSM-5 dysregulation disorders, DTD was associated with separation anxiety disorder and attention deficit hyperactivity disorder after controlling for PTSD, while PTSD was associated with major depression and generalized anxiety disorder after controlling for DTD. Conclusions: DTD's comorbidities overlap with but extend beyond those of PTSD to include panic, separation anxiety, and disruptive behaviour disorders. DTD warrants further investigation as a potential diagnosis or a complex variant of PTSD in children, similar to the adult symptoms of disturbances of self-organization in the proposed International Classification of Diseases, 11th revision (ICD-11) complex post-traumatic stress disorder subtype.
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Project description:Contemporary symptom-based diagnosis of post-traumatic stress disorder (PTSD) largely overlooks related neurobehavioral mechanisms and relies entirely on subjective interpersonal reporting. Previous studies associating biomarkers with PTSD have mostly used symptom-based diagnosis as the main outcome measure, disregarding the wide variability and richness of PTSD phenotypical features. Here, we aimed to computationally derive potential biomarkers that could efficiently differentiate PTSD subtypes among recent trauma survivors. A three-staged semi-unsupervised method ("3C") was used to firstly categorize individuals by current PTSD symptom severity, then derive clusters based on clinical features related to PTSD (e.g. anxiety and depression), and finally to classify participants' cluster membership using objective multi-domain features. A total of 256 features were extracted from psychometrics, cognitive functioning, and both structural and functional MRI data, obtained from 101 adult civilians (age = 34.80 ± 11.95; 51 females) evaluated within 1 month of trauma exposure. The features that best differentiated cluster membership were assessed by importance analysis, classification tree, and ANOVA. Results revealed that entorhinal and rostral anterior cingulate cortices volumes (structural MRI domain), in-task amygdala's functional connectivity with the insula and thalamus (functional MRI domain), executive function and cognitive flexibility (cognitive testing domain) best differentiated between two clusters associated with PTSD severity. Cross-validation established the results' robustness and consistency within this sample. The neural and cognitive potential biomarkers revealed by the 3C analytics offer objective classifiers of post-traumatic morbidity shortly following trauma. They also map onto previously documented neurobehavioral mechanisms associated with PTSD and demonstrate the usefulness of standardized and objective measurements as differentiating clinical sub-classes shortly after trauma.
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Project description:Background: The purpose of this study was to identify gene expression differences associated with post-traumatic stress disorder (PTSD) and trauma exposure (TE) in a three-group study design comprised of those with and without trauma exposure and PTSD. Methods: We conducted gene expression and gene network analyses in a sample (n = 45) composed of female subjects of European Ancestry (EA) with PTSD, TE without PTSD, and controls. Results: We identified 283 genes differentially expressed between PTSD-TE groups. In an independent sample of Veterans (n = 78) a small minority of these genes were also differentially expressed. We identified 7 gene network modules significantly associated with PTSD and TE (Bonferroni corrected p ≤ 0.05), which at a false discovery rate (FDR) of q ≤ 0.2, were significantly enriched for biological pathways involved in focal adhesion, neuroactive ligand receptor interaction, and immune related processes among others. Conclusions: This study uses gene network analyses to identify significant gene modules associated with PTSD, TE, and controls. On an individual gene level, we identified a large number of differentially expressed genes between PTSD-TE groups, a minority of which were also differentially expressed in the independent sample. We also demonstrate a lack of network module preservation between PTSD and TE, suggesting that the molecular signature of PTSD and trauma are likely independent of each other. Our results provide a basis for the identification of likely disease pathways and biomarkers involved in the etiology of PTSD.
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