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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
General cognitive impairment as a risk factor for motor vehicle collision involvement: a prospective population-based
Carrie Huisingh1, Cynthia Owsley1, Virginia G Wadley2
1Department of Ophthalmology, School of Medicine, University of Alabama at Birmingham, Birmingham, AL 35294.
Abstract:
This study examined whether cognitive impairment and decline as assessed by a brief mental status screening test is associated with future crash risk in a cohort of older drivers. A three-year prospective study was conducted in a population-based sample of 2000 licensed drivers aged 70 years and older. At the baseline visit, cognitive impairment was defined as <24 on the Mini Mental State Exam (MMSE). Decline was defined as those with a 1-year change in MMSE scores in the lowest quartile (largest decrease). Motor vehicle collision involvement was obtained from the Alabama Department of Public Safety. Poisson regression was used to calculate crude and adjusted rate ratios (RR). There were 278 crashes during the follow-up period. Rates of crash involvement were higher for those with cognitive impairment (crude RR=2.33) compared to those without impairment at baseline; adjustment for potential confounders namely age and visual processing speed attenuated this relationship (adjusted RR=1.26, 95% CI 0.65-2.44). Drivers who experienced a pronounced decline in estimated MMSE scores in one year were 1.64 (95% CI 1.04-2.57) times more likely to have a future at-fault crash compared to those whose scores did not decline. Evaluation of MMSE over time may provide important insight in an older driver's future risk of at-fault crash involvement.
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