Fuermaier Anselm B M, Piersma Dafne, de Waard Dick, Davidse Ragnhild J, de Groot Jolieke, Doumen Michelle J A, Bredewoud Ruud A, Claesen René, Lemstra Afina W, Scheltens Philip, Vermeeren Annemiek, Ponds Rudolf, Verhey Frans, Brouwer Wiebo H, Tucha Oliver
a Department of Clinical and Developmental Neuropsychology , University of Groningen , Groningen , The Netherlands.
b SWOV Institute for Road Safety Research , The Hague , The Netherlands.
Traffic Inj Prev. 2017 Feb 17;18(2):145-149. doi: 10.1080/15389588.2016.1232809. Epub 2016 Sep 13.
There is no consensus yet on how to determine which patients with cognitive impairment are able to drive a car safely and which are not. Recently, a strategy was composed for the assessment of fitness to drive, consisting of clinical interviews, a neuropsychological assessment, and driving simulator rides, which was compared with the outcome of an expert evaluation of an on-road driving assessment. A selection of tests and parameters of the new approach revealed a predictive accuracy of 97.4% for the prediction of practical fitness to drive on an initial sample of patients with Alzheimer's dementia. The aim of the present study was to explore whether the selected variables would be equally predictive (i.e., valid) for a closely related group of patients; that is, patients with mild cognitive impairment (MCI).
Eighteen patients with mild cognitive impairment completed the proposed approach to the measurement of fitness to drive, including clinical interviews, a neuropsychological assessment, and driving simulator rides. The criterion fitness to drive was again assessed by means of an on-road driving evaluation. The predictive validity of the fitness to drive assessment strategy was evaluated by receiver operating characteristic (ROC) analyses.
Twelve patients with MCI (66.7%) passed and 6 patients (33.3%) failed the on-road driving assessment. The previously proposed approach to the measurement of fitness to drive achieved an overall predictive accuracy of 94.4% in these patients. The application of an optimal cutoff resulted in a diagnostic accuracy of 100% sensitivity toward unfit to drive and 83.3% specificity toward fit to drive. Further analyses revealed that the neuropsychological assessment and the driving simulator rides produced rather stable prediction rates, whereas clinical interviews were not significantly predictive for practical fitness to drive in the MCI patient sample.
The selected measures of the previously proposed approach revealed adequate accuracy in identifying fitness to drive in patients with MCI. Furthermore, a combination of neuropsychological test performance and simulated driving behavior proved to be the most valid predictor of practical fitness to drive.
对于如何确定哪些认知障碍患者能够安全驾驶汽车，哪些不能，目前尚无共识。最近，制定了一项驾驶适宜性评估策略，包括临床访谈、神经心理学评估和驾驶模拟器测试，并将其与道路驾驶评估的专家评估结果进行比较。在阿尔茨海默病痴呆患者的初始样本中，新方法的一系列测试和参数对实际驾驶适宜性的预测准确率为97.4%。本研究的目的是探讨所选变量对一组密切相关的患者，即轻度认知障碍（MCI）患者，是否具有同等的预测性（即有效性）。
18例轻度认知障碍患者完成了拟议的驾驶适宜性测量方法，包括临床访谈、神经心理学评估和驾驶模拟器测试。再次通过道路驾驶评估来评估驾驶适宜性标准。通过受试者操作特征（ROC）分析评估驾驶适宜性评估策略的预测有效性。
12例MCI患者（66.7%）通过了道路驾驶评估，6例患者（33.3%）未通过。先前提出的驾驶适宜性测量方法在这些患者中的总体预测准确率为94.4%。应用最佳临界值后，对不适宜驾驶的诊断敏感性为100%，对适宜驾驶的诊断特异性为83.3%。进一步分析表明，神经心理学评估和驾驶模拟器测试产生的预测率相当稳定，而临床访谈对MCI患者样本的实际驾驶适宜性没有显著预测作用。
先前提出的方法中所选的测量指标在识别MCI患者的驾驶适宜性方面显示出足够的准确性。此外，神经心理学测试表现和模拟驾驶行为的结合被证明是实际驾驶适宜性最有效的预测指标。
