Department of Psychiatry and Psychotherapy, Eberhard Karls University, Tübingen, Germany.
Geriatric Center at the University Hospital, Eberhard Karls University, Tübingen, Germany.
Sci Rep. 2019 Mar 5;9(1):3543. doi: 10.1038/s41598-019-40010-0.
The early detection of cognitive impairment or dementia is in the focus of current research as the amount of cognitively impaired individuals will rise intensely in the next decades due to aging population worldwide. Currently available diagnostic tools to detect mild cognitive impairment (MCI) or dementia are time-consuming, invasive or expensive and not suitable for wide application as required by the high number of people at risk. Thus, a fast, simple and sensitive test is urgently needed to enable an accurate detection of people with cognitive dysfunction and dementia in the earlier stages to initiate specific diagnostic and therapeutic interventions. We examined digital Clock Drawing Test (dCDT) kinematics for their clinical utility in differentiating patients with amnestic MCI (aMCI) or mild Alzheimer's dementia (mAD) from healthy controls (HCs) and compared it with the diagnostic value of the Consortium to Establish a Registry for Alzheimer's Disease (CERAD) neuropsychological battery total score. Data of 381 participants (138 patients with aMCI, 106 patients with mAD and 137 HCs) was analyzed in the present study. All participants performed the clock drawing test (CDT) on a tablet computer and underwent the CERAD test battery and depression screening. CERAD total scores were calculated by subtest summation, excluding MMSE scores. All tablet variables (i.e. time in air, time on surface, total time, velocity, pressure, pressure/velocity relation, strokes per minute, time not painting, pen-up stroke length, pen-up/pen-down relation, and CDT score) during dCDT performance were entered in a forward stepwise logistic regression model to assess, which parameters best discriminated between aMCI or mAD and HC. Receiver operating characteristics (ROC) curves were constructed to visualize the specificity in relation to the sensitivity of dCDT variables against CERAD total scores in categorizing the diagnostic groups. dCDT variables provided a slightly better diagnostic accuracy of 81.5% for discrimination of aMCI from HCs than using CERAD total score (accuracy 77.5%). In aMCI patients with normal CDT scores, both dCDT (accuracy 78.0%) and CERAD total scores (accuracy 76.0%) were equally accurate in discriminating against HCs. Finally, in differentiating patients with mAD from healthy individuals, accuracy of both dCDT (93.0%) and CERAD total scores (92.3%) was excellent. Our findings suggest that dCDT is a suitable screening tool to identify early cognitive dysfunction. Its performance is comparable with the time-consuming established psychometric measure (CERAD test battery).
认知障碍或痴呆的早期检测是当前研究的重点，因为全球人口老龄化，认知障碍个体的数量将在未来几十年内大幅增加。目前用于检测轻度认知障碍（MCI）或痴呆的诊断工具耗时、侵入性或昂贵，并且不适合广泛应用，因为高危人群数量众多。因此，迫切需要一种快速、简单和敏感的测试方法，以便在早期阶段准确检测认知功能障碍和痴呆患者，从而进行特定的诊断和治疗干预。我们研究了数字钟画测试（dCDT）的运动学在区分遗忘型轻度认知障碍（aMCI）或轻度阿尔茨海默病（mAD）患者与健康对照组（HCs）中的临床应用，并将其与 Consortium to Establish a Registry for Alzheimer's Disease（CERAD）神经心理学成套测验总评分的诊断价值进行了比较。本研究分析了 381 名参与者（138 名 aMCI 患者、106 名 mAD 患者和 137 名 HCs）的数据。所有参与者均在平板电脑上进行钟画测试（CDT），并接受 CERAD 测试和抑郁筛查。CERAD 总评分通过子测试求和计算，不包括 MMSE 评分。在 dCDT 执行过程中，所有平板电脑变量（即空中时间、表面时间、总时间、速度、压力、压力/速度关系、每分钟笔划数、无画时间、抬笔笔划长度、抬笔/落笔关系和 CDT 分数）均输入向前逐步逻辑回归模型，以评估哪些参数最能区分 aMCI 或 mAD 和 HC。绘制了接收者操作特征（ROC）曲线，以可视化 dCDT 变量与 CERAD 总评分在分类诊断组时对特异性与敏感性的关系。dCDT 变量在区分 aMCI 与 HCs 方面的诊断准确性略高于 CERAD 总评分（准确性 77.5%），为 81.5%。在 CDT 评分正常的 aMCI 患者中，dCDT（准确性 78.0%）和 CERAD 总评分（准确性 76.0%）在区分 HCs 方面同样准确。最后，在区分 mAD 患者与健康个体时，dCDT（93.0%）和 CERAD 总评分（92.3%）的准确性均非常高。我们的研究结果表明，dCDT 是一种识别早期认知功能障碍的合适筛查工具。它的性能与耗时的既定心理计量测量（CERAD 测试）相当。
