Robert D. Shura

Chronic Traumatic Encephalopathy and Suicide: A Systematic Review

Traumatic brain injury (TBI) is a global health concern, and the recent literature reports that a single mild TBI can result in chronic traumatic encephalopathy (CTE). It has been suggested that CTE may lead to death by suicide, raising important prevention, treatment, and policy implications. Thus, we conducted a systematic review of the medical literature to answer the key question: What is the existing evidence in support of a relationship between CTE and suicide? Systematic searches of CTE and suicide yielded 85 unique abstracts. Seven articles were identified for full text review. Only two case series met inclusion criteria and included autopsies from 17 unique cases, 5 of whom died by suicide. Neither studies used blinding, control cases, or systematic data collection regarding TBI exposure and/or medical/neuropsychiatric history. The identified CTE literature revealed divergent opinions regarding neuropathological elements of CTE and heterogeneity regarding clinical manifestations. Overall quality of evidence regarding a relationship between CTE and suicide was rated as very low using Grading of Recommendations Assessment, Development and Evaluation Working Group (GRADE) criteria. Further studies of higher quality and methodological rigor are needed to determine the existence and nature of any relationship between CTE and suicide.

Embedded Performance Validity Measures with Postdeployment Veterans: Cross-Validation and Efficiency with Multiple Measures

Embedded validity measures support comprehensive assessment of performance validity. The purpose of this study was to evaluate the accuracy of individual embedded measures and to reduce them to the most efficient combination. The sample included 212 postdeployment veterans (average age = 35 years, average education = 14 years). Thirty embedded measures were initially identified as predictors of Green’s Word Memory Test (WMT) and were derived from the California Verbal Learning Test-Second Edition (CVLT-II), Conners’ Continuous Performance Test-Second Edition (CPT-II), Trail Making Test, Stroop, Wisconsin Card Sorting Test-64, the Wechsler Adult Intelligence Scale-Third Edition Letter-Number Sequencing, Rey Complex Figure Test (RCFT), Brief Visuospatial Memory Test-Revised, and the Finger Tapping Test. Eight nonoverlapping measures with the highest area-under-the-curve (AUC) values were retained for entry into a logistic regression analysis. Embedded measure accuracy was also compared to cutoffs found in the existing literature. Twenty-one percent of the sample failed the WMT. Previously developed cutoffs for individual measures showed poor sensitivity (SN) in the current sample except for the CPT-II (Total Errors, SN = .41). The CVLT-II (Trials 1–5 Total) showed the best overall accuracy (AUC = .80). After redundant measures were statistically eliminated, the model included the RCFT (Recognition True Positives), CPT-II (Total Errors), and CVLT-II (Trials 1–5 Total) and increased overall accuracy compared with the CVLT-II alone (AUC = .87). The combination of just 3 measures from the CPT-II, CVLT-II, and RCFT was the most accurate/efficient in predicting WMT performance.

Insular Cortex: Structural and Functional Neuroanatomy

Cover and FIGURE 1. (Cover) The approximate location and extent of the insula is illustrated on sagittal, coronal, and axial MRI scans. The insula is divided by the central sulcus into anterior (pink) and posterior (green) lobes. (Left) The insula’s location between the opercula and the claustrum is illustrated on an axial MRI. (Center) A simplified sagittal drawing of the insula depicts the major gyri. (Right) One way to identify possible functional subdivisions within an area is to createmaps of the cellular structure (cytoarchitecture). A recent study in humans reported a progression in cellular structure from the dorsal-posterior granular region (G and g) to the ventral-anterior agranular region (a2–a1) with a transition zone of dysgranular cortex (d3–d1). The locations and extents of the seven cytoarchitectonic subdivisions identified are approximated on a simplified sagittal drawing. The locations containing the majority of von Economo neurons (VENs) are indicated (region enclosed by white line).

Cost of malingering mild traumatic brain injury-related cognitive deficits during compensation and pension evaluations in the veterans benefits administration

ABSTRACT Given the high rates of exaggeration in those claiming long-term cognitive deficits as a result of mild traumatic brain injury (mTBI), the aim of this study was to evaluate the rates of malingering in those seeking disability through the Veterans Benefits Administration and estimate the financial burden of disability payments for those receiving compensation despite exaggerated mTBI-related cognitive deficits. Retrospective review included 74 veterans seen for Compensation and Pension evaluations for mTBI. Rates of malingering were based on failure of the Medical Symptom Validity Test (MSVT) and/or the Test of Memory Malingering (TOMM) trial 1 ≤ 40. Total estimated compensation was based on the level of disability awarded and the number of individuals found to be malingering cognitive deficits. Overall, 33–52% of the sample was found to be malingering mTBI-related cognitive deficits. The malingering groups were receiving approximately

Neuropsychological Test Administration by Videoconference: A Systematic Review and Meta-Analysis

71,000–

The Behavioral Dyscontrol Scale-II with Non-Elderly Veterans

121,000/year (

Auditory Consonant Trigrams: A Psychometric Update†.

6,390–

Factor structure and construct validity of the Behavioral Dyscontrol Scale-II

7,063 per year, per veteran on average). Estimated nationwide disability payments for those possibly malingering mTBI-related cognitive deficits would be

Personality Assessment Inventory profiles of veterans: Differential effects of mild traumatic brain injury and psychopathology

136–

Neurological Symptoms in US Government Personnel in Cuba

235 million/year (projected costs from 2015–2020 =