Efficacy of the ANAM General Neuropsychological Screening battery (ANAM GNS) for Detecting Neurocognitive Impairment in a Mixed Clinical Sample

Abstract

The Automated Neuropsychological Assessment Metrics (ANAM) is a computerized neuropsychological assessment battery that has demonstrated utility in a variety of clinical populations including multiple sclerosis, systemic lupus erythematosus, Parkinson’s disease, acquired brain injury, migraine headaches, and Alzheimer’s disease. This study utilized selected tests from the ANAM General Neuropsychological Screening Battery (ANAM GNS), a newly defined subset of tests from the broader ANAM library designed for general clinical assessment of cognition. ANAM GNS is an expansion of the ANAM Core battery which has been utilized in a military setting. The efficacy of the ANAM GNS was explored in a mixed clinical sample relative to well-established, traditional neuropsychological measure, the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS). It was hypothesized that scores from the ANAM GNS would accurately predict participants as either impaired (n = 30) or normal (n = 113). Participants were grouped a priori based on RBANS Total Index scores with impairment defined as scores 15th percentile. Logistic regression analysis was conducted to evaluate the classification accuracy of the ANAM GNS. The predictor variables were the Throughput scores from seven selected ANAM GNS subtests. The full model significantly predicted impairment status, sensitivity was 81% and specificity was 89.1%. Overall classification rate was 87.9% and the Odds Ratio for the overall model was 34.65. Positive predictive value was 56.7% and negative predictive value was 96.4%. This study represents the first clinical data on the ANAM GNS, and documents that it has good concurrent and predictive validity with a well-established neuropsychological measure.