Vincent Andrea S, Roebuck-Spencer Tresa M, Cox-Fuenzalida L Eugenia, Block Cady, Scott James G, Kane Robert
a Cognitive Science Research Center , University of Oklahoma , Norman , Okalahoma.
b Department of Psychiatry and Behavioral Sciences , University of Oklahoma Health Sciences Center , Oklahoma City , Oklahoma.
Appl Neuropsychol Adult. 2018 Jul-Aug;25(4):366-375. doi: 10.1080/23279095.2017.1314967. Epub 2017 Apr 27.
The Automated Neuropsychological Assessment Metrics (ANAM) is a library of computer based tests designed to measure cognitive function at a single time-point or longitudinally for detection of cognitive change. This study sought to validate ANAM as a cognitive screening tool for presence of confirmed neuropsychological diagnosis in an outpatient setting. Retrospective data analysis was conducted for 139 patients referred for outpatient neuropsychological assessment. Clinical diagnosis was made independent of ANAM test results and resulted in a diagnostic mix of both neurologic and psychologic etiologies. ANAM scores predictive of presence of confirmed diagnosis were identified using multiple logistic regression and the predictive ability of the resulting model was quantified using receiver operator characteristic analysis. Sensitivity and specificity for the ANAM when combined with anger and depressive symptom scores were 71% and 91%, respectively, with a positive predictive value of 97.5 and negative predictive value of 40.4. This combined approach provided the greatest accuracy for individual tests as well as the composite score of the ANAM in identifying those who received a subsequent clinical diagnosis. Although data should be replicated in larger samples, these results suggest that ANAM may have predictive value and may be a useful screening tool for identifying those who would likely benefit from neuropsychological services.
自动神经心理评估指标(ANAM)是一个基于计算机测试的库,旨在在单个时间点或纵向测量认知功能,以检测认知变化。本研究旨在验证ANAM作为门诊环境中确诊神经心理诊断存在的认知筛查工具。对139名转诊进行门诊神经心理评估的患者进行了回顾性数据分析。临床诊断独立于ANAM测试结果做出,结果导致了神经和心理病因的诊断组合。使用多元逻辑回归确定预测确诊诊断存在的ANAM分数,并使用受试者工作特征分析对所得模型的预测能力进行量化。当与愤怒和抑郁症状评分相结合时,ANAM的敏感性和特异性分别为71%和91%,阳性预测值为97.5,阴性预测值为40.4。这种联合方法在识别那些随后接受临床诊断的人时,为个体测试以及ANAM的综合评分提供了最高的准确性。尽管数据应在更大的样本中复制,但这些结果表明,ANAM可能具有预测价值,可能是识别那些可能从神经心理服务中受益的人的有用筛查工具。