Rey-Osterrieth complex figure normative data for the psychiatric population

What are the predictors of TOMM failure in clinical TBI populations? A retrospective analysis

OBJECTIVES

To determine base rates of invalid performance on the Test of Memory Malingering (TOMM) in patients with traumatic brain injury (TBI) undertaking rehabilitation who were referred for clinical assessment, and the factors contributing to TOMM failure.

METHODS

Retrospective file review of consecutive TBI referrals for neuropsychological assessment over seven years. TOMM failure was conventionally defined as performance <45/50 on Trial 2 or Retention Trial. Demographic, injury, financial compensation, occupational, and medical variables were collected.

RESULTS

Four hundred and ninety one TBI cases (Median age = 40 years [IQR = 26-52], 79% male, 82% severe TBI) were identified. Overall, 48 cases (9.78%) failed the TOMM. Logistic regression analyses revealed that use of an interpreter during the assessment (adjusted odds ratio [aOR] = 8.25, 95%CI = 3.96-17.18), outpatient setting (aOR = 4.80, 95%CI = 1.87-12.31) and post-injury psychological distress (aOR = 2.77, 95%CI = 1.35-5.70) were significant multivariate predictors of TOMM failure. The TOMM failure rate for interpreter cases was 49% (21/43) in the outpatient setting vs. 7% (2/30) in the inpatient setting. By comparison, 9% (21/230) of non-interpreter outpatient cases failed the TOMM vs. 2% (4/188) of inpatient cases.

CONCLUSIONS

TOMM failure very rarely occurs in clinical assessment of TBI patients in the inpatient rehabilitation setting. It is more common in the outpatient setting, particularly in non-English-speaking people requiring an interpreter. The findings reinforce the importance of routinely administering stand-alone performance validity tests in assessments of clinical TBI populations, particularly in outpatient settings, to ensure that neuropsychological test results can be interpreted with a high degree of confidence.

A Graph Theory Approach to Clarifying Aging and Disease Related Changes in Cognitive Networks

In accordance with the physiological networks that underlie it, human cognition is characterized by both the segregation and interdependence of a number of cognitive domains. Cognition itself, therefore, can be conceptualized as a network of functions. A network approach to cognition has previously revealed topological differences in cognitive profiles between healthy and disease populations. The present study, therefore, used graph theory to determine variation in cognitive profiles across healthy aging and cognitive impairment. A comprehensive neuropsychological test battery was administered to 415 participants. This included three groups of healthy adults aged 18-39 (n = 75), 40-64 (n = 75), and 65 and over (n = 70) and three patient groups with either amnestic (n = 75) or non-amnestic (n = 60) mild cognitive impairment or Alzheimer's type dementia (n = 60). For each group, cognitive networks were created reflective of test-to-test covariance, in which nodes represented cognitive tests and edges reflected statistical inter-nodal significance (p < 0.05). Network metrics were derived using the Brain Connectivity Toolbox. Network-wide clustering, local efficiency and global efficiency of nodes showed linear differences across the stages of aging, being significantly higher among older adults when compared with younger groups. Among patients, these metrics were significantly higher again when compared with healthy older controls. Conversely, average betweenness centralities were highest in middle-aged participants and lower among older adults and patients. In particular, compared with controls, patients demonstrated a distinct lack of centrality in the domains of semantic processing and abstract reasoning. Network composition in the amnestic mild cognitive impairment group was similar to the network of Alzheimer's dementia patients. Using graph theoretical methods, this study demonstrates that the composition of cognitive networks may be measurably altered by the aging process and differentially impacted by pathological cognitive impairment. Network alterations characteristic of Alzheimer's disease in particular may occur early and be distinct from alterations associated with differing types of cognitive impairment. A shift in centrality between domains may be particularly relevant in identifying cognitive profiles indicative of underlying disease. Such techniques may contribute to the future development of more sophisticated diagnostic tools for neurodegenerative disease.