A Systematic Review and Meta-Analysis of On-Road Simulator and Cognitive Driving Assessment in Alzheimer’s Disease and Mild Cognitive Impairment

Article type: Research Article

Authors: Hird, Megan A.^{a; b} | Egeto, Peter^c | Fischer, Corinne E.^{a; d} | Naglie, Gary^{e; f; g} | Schweizer, Tom A.^{a; h; i; *}

Affiliations: [a] Neuroscience Research Program, St. Michael’s Hospital, Toronto, ON, Canada | [b] Institute of Medical Science, University of Toronto, Toronto, ON, Canada | [c] Department of Psychology, Ryerson University, Toronto, ON, Canada | [d] Department of Psychiatry, Division of Geriatric Psychiatry, St. Michael’s Hospital, University of Toronto, Toronto, ON, Canada | [e] Department of Medicine and Rotman Research Institute, Baycrest Health Sciences, Toronto, ON, Canada | [f] Department of Medicine and Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada | [g] Department of Research, Toronto Rehabilitation Institute - University Health Network, Toronto, ON, Canada | [h] Department of Surgery, Neurosurgery Division, University of Toronto, Toronto, ON, Canada | [i] Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, ON, Canada

Correspondence: [*] Correspondence to: Dr. Tom Schweizer, Keenan Research Centre of the Li Ka Shing Knowledge Institute, St. Michael’s Hospital, 30 Bond Street, Toronto, M5B 1W8, ON, Canada. Tel.: +1 416 864 5504; Fax: +1 416 864 5857; E-mail: SchweizerT@smh.ca.

Abstract: Background: Many individuals with Alzheimer’s disease (AD) and mild cognitive impairment (MCI) are at an increased risk of driving impairment. There is a need for tools with sufficient validity to help clinicians assess driving ability. Objective: Provide a systematic review and meta-analysis of the primary driving assessment methods (on-road, cognitive, driving simulation assessments) in patients with MCI and AD. Methods: We investigated (1) the predictive utility of cognitive tests and domains, and (2) the areas and degree of driving impairment in patients with MCI and AD. Effect sizes were derived and analyzed in a random effects model. Results: Thirty-two articles (including 1,293 AD patients, 92 MCI patients, 2,040 healthy older controls) met inclusion criteria. Driving outcomes included: On-road test scores, pass/fail classifications, errors; caregiver reports; real world crash involvement; and driving simulator collisions/risky behavior. Executive function (ES [95% CI]; 0.61 [0.41, 0.81]), attention (0.55 [0.33, 0.77]), visuospatial function (0.50 [0.34, 0.65]), and global cognition (0.61 [0.39, 0.83]) emerged as significant predictors of driving performance. Trail Making Test Part B (TMT-B, 0.61 [0.28, 0.94]), TMT-A (0.65 [0.08, 1.21]), and Maze test (0.88 [0.60, 1.15]) emerged as the best single predictors of driving performance. Patients with very mild AD (CDR = 0.5) mild AD (CDR = 1) were more likely to fail an on-road test than healthy control drivers (CDR = 0), with failure rates of 13.6%, 33.3% and 1.6%, respectively. Conclusion: The driving ability of patients with MCI and AD appears to be related to degree of cognitive impairment. Across studies, there are inconsistent cognitive predictors and reported driving outcomes in MCI and AD patients. Future large-scale studies should investigate the driving performance and associated neural networks of subgroups of AD (very mild, mild, moderate) and MCI (amnestic, non-amnestic, single-domain, multiple-domain).

Keywords: KeywordsAlzheimer’s disease, automobile driving, cognition, mild cognitive impairment

DOI: 10.3233/JAD-160276

Journal: Journal of Alzheimer's Disease, vol. 53, no. 2, pp. 713-729, 2016