Structured interview for mild traumatic brain injury after military blast: inter-rater agreement and development of diagnostic algorithm.

The existing gold standard for diagnosing a suspected previous mild traumatic brain injury (mTBI) is clinical interview. But it is prone to bias, especially for parsing the physical versus psychological effects of traumatic combat events, and its inter-rater reliability is unknown. Several standardized TBI interview instruments have been developed for research use but have similar limitations. Therefore, we developed the Virginia Commonwealth University (VCU) retrospective concussion diagnostic interview, blast version (VCU rCDI-B), and undertook this cross-sectional study aiming to 1) measure agreement among clinicians' mTBI diagnosis ratings, 2) using clinician consensus develop a fully structured diagnostic algorithm, and 3) assess accuracy of this algorithm in a separate sample. Two samples (n = 66; n = 37) of individuals within 2 years of experiencing blast effects during military deployment underwent semistructured interview regarding their worst blast experience. Five highly trained TBI physicians independently reviewed and interpreted the interview content and gave blinded ratings of whether or not the experience was probably an mTBI. Paired inter-rater reliability was extremely variable, with kappa ranging from 0.194 to 0.825. In sample 1, the physician consensus prevalence of probable mTBI was 84%. Using these diagnosis ratings, an algorithm was developed and refined from the fully structured portion of the VCU rCDI-B. The final algorithm considered certain symptom patterns more specific for mTBI than others. For example, an isolated symptom of "saw stars" was deemed sufficient to indicate mTBI, whereas an isolated symptom of "dazed" was not. The accuracy of this algorithm, when applied against the actual physician consensus in sample 2, was almost perfect (correctly classified = 97%; Cohen's kappa = 0.91). In conclusion, we found that highly trained clinicians often disagree on historical blast-related mTBI determinations. A fully structured interview algorithm was developed from their consensus diagnosis that may serve to enhance diagnostic standardization for clinical research in this population.

Post-acute brain injury urinary signature: a new resource for molecular diagnostics.

Heterogeneity within brain injury presents a challenge to the development of informative molecular diagnostics. Recent studies show progress, particularly in cerebrospinal fluid, with biomarker assays targeting one or a few structural proteins. Protein-based assays in peripheral fluids, however, have been more challenging to develop, in part because of restricted and intermittent barrier access. Further, a greater number of molecular variables may be required to inform on patient status given the multi-factorial nature of brain injury. Presented is an alternative approach profiling peripheral fluid for a class of small metabolic by-products rendered by ongoing brain pathobiology. Urine specimens were collected for head trauma subjects upon admission to acute brain injury rehabilitation and non-traumatized matched controls. An innovative data-independent mass spectrometry approach was employed for reproducible molecular quantification across osmolarity-normalized samples. The postacute human traumatic brain injury urinary signature encompassed 2476 discriminant variables reproducibly measured in specimens for subject classification. Multiple subprofiles were then discerned in correlation with injury severity per the Glasgow Comma Scale and behavioral and neurocognitive function per the Patient Competency Rating Scale and Frontal Systems Behavioral Scale. Identified peptide constituents were enriched for outgrowth and guidance, extracellular matrix, and post-synaptic density proteins, which were reflective of ongoing post-acute neuroplastic processes demonstrating pathobiological relevance. Taken together, these findings support further development of diagnostics based on brain injury urinary signatures using either combinatorial quantitative models or pattern-recognition methods. Particularly, these findings espouse assay development to address unmet diagnostic and theragnostic needs in brain injury rehabilitative medicine.

Political violence and mental health in Nepal: prospective study.

BACKGROUND: Post-conflict mental health studies in low-income countries have lacked pre-conflict data to evaluate changes in psychiatric morbidity resulting from political violence. AIMS: This prospective study compares mental health before and after exposure to direct political violence during the People's War in Nepal. METHOD: An adult cohort completed the Beck Depression Inventory and Beck Anxiety Inventory in 2000 prior to conflict violence in their community and in 2007 after the war. RESULTS: Of the original 316 participants, 298 (94%) participated in the post-conflict assessment. Depression increased from 30.9 to 40.6%. Anxiety increased from 26.2 to 47.7%. Post-conflict post-traumatic stress disorder (PTSD) was 14.1%. Controlling for ageing, the depression increase was not significant. The anxiety increase showed a dose-response association with conflict exposure when controlling for ageing and daily stressors. No demographic group displayed unique vulnerability or resilience to the effects of conflict exposure. CONCLUSIONS: Conflict exposure should be considered in the context of other types of psychiatric risk factors. Conflict exposure predicted increases in anxiety whereas socioeconomic factors and non-conflict stressful life events were the major predictors of depression. Research and interventions in post-conflict settings therefore should consider differential trajectories for depression v. anxiety and the importance of addressing chronic social problems ranging from poverty to gender and ethnic/caste discrimination.

Culture in psychiatric epidemiology: using ethnography and multiple mediator models to assess the relationship of caste with depression and anxiety in Nepal.

BACKGROUND: The causes of ethnic and caste-based disparities in mental health are poorly understood. AIM: The study aimed to identify mediators underlying caste-based disparities in mental health in Nepal. SUBJECTS AND METHODS: A mixed methods ethnographic and epidemiological study of 307 adults (Dalit/Nepali, n=75; high caste Brahman and Chhetri, n=232) was assessed with Nepali versions of Beck Depression (BDI) and Anxiety (BAI) Inventories. RESULTS: One-third (33.7%) of participants were classified as depressed: Dalit/Nepali 50.0%, high caste 28.4%. One quarter (27.7%) of participants were classified as anxious: Dalit/Nepali 50.7%, high caste 20.3%. Ethnographic research identified four potential mediators: Stressful life events, owning few livestock, no household income, and lack of social support. The direct effect of caste was 1.08 (95% CI -1.10-3.27) on depression score and 4.76 (95% CI 2.33-7.19) on anxiety score. All four variables had significant indirect (mediation) effects on anxiety, and all but social support had significant indirect effects on depression. CONCLUSION: Caste-based disparities in mental health in rural Nepal are statistically mediated by poverty, lack of social support, and stressful life events. Interventions should target these areas to alleviate the excess mental health burden born by Dalit/Nepali women and men.