Changes in Driving Patterns May Signal Early Cognitive Decline

 

Your competent? doctor already knew about this earlier research, right? Oh no, you DON'T have a functioning stroke doctor, do you?

Driving Patterns Pinpoint Early Alzheimer's Disease July 2021

And your patient's health will deteriorate after stopping driving.

Health goes downhill when older adults stop driving 

The latest here:

Changes in Driving Patterns May Signal Early Cognitive Decline

A change in driving patterns may be an indicator of cognitive decline in older adults, a long-term study suggested.

Using driving data, researchers were able to predict the development of mild cognitive impairment (MCI) with 82% accuracy. Over 3 years, compared with those with normal cognition, older adults with MCI drove less at night, made fewer monthly trips, and did not stray as much from regular routes.

“We found that using a GPS [Global Positioning System] data tracking device, we could more accurately determine who had developed cognitive issues than looking at just factors such as age, cognitive test scores, and whether they had a genetic risk factor related to Alzheimer’s disease,” principal investigator Ganesh M. Babulal, PhD, OTD, of Washington University School of Medicine in St. Louis, said in a news release.

The study was published online on November 26 in Neurology.

New Opportunities for Early Detection

In the US, older adults make up roughly 20% of drivers. In addition, an estimated one third of this population experiences cognitive impairment. Previous studies have shown that those with early-stage dementia scored worse on driving tests and had a greater risk of a crash.

Timely, scalable solutions are needed to monitor safety in this at-risk population of drivers, the researchers noted, highlighting that recent advances in vehicular tracking technology might provide useful data to identify MCI.

To test this hypothesis, the investigators analyzed driving data from 298 participants (mean age, 75.1 years; 45.6% female). Of these, 56 were older adults with MCI, while the rest had normal cognition (NC).

Participants underwent the Clinical Dementia Rating, a series of neuropsychological assessments, and were genotyped for the APOE epsilon 4 allele, a known risk factor for Alzheimer’s disease. Investigators calculated individuals’ Preclinical Alzheimer Cognitive Composite (PACC) score based on results from a battery of standardized cognitive tests.

An in-vehicle GPS tracker recorded participants’ driving behavior daily for up to 40 months, capturing total trips, average distance, nighttime driving, speeding episodes, and route variation.

Changes in longitudinal driving behavior were assessed using a linear mixed model, adjusted for baseline age, race, education, sex, and APOE epsilon 4 status. Logistic regression with receiver operator curve analysis was used to distinguish older adults with MCI and those with NC.

At baseline, the driving habits of the NC and MCI groups were similar. However, over time, older adults with MCI made fewer trips per month (P < .001) and fewer nighttime trips (P < .001). They also drove more familiar routes, as evidenced by statistically significantly lower random entropy, a measure of trip unpredictability.

Specifically, driving factors like speeding, route variation, and medium and maximum distance were found to distinguish drivers with MCI from those with NC (area under the curve, 0.82; 95% CI, 0.75-0.89).

When demographic factors, PACC score, and APOE epsilon 4 status were added to the model, the investigators were able to identify MCI with 87% accuracy (95% CI, 0.81-0.93). Without the driving data, accuracy decreased to 76%.

“Looking at people’s daily driving behavior is a relatively low-burden, unobtrusive way to monitor people’s cognitive skills and ability to function,” Babulal said. “This could help identify drivers who are at risk earlier for early intervention, before they have a crash or near miss, which is often what happens now.”

The investigators noted that the study’s limitations included the fact that the majority of participants were predominantly White individuals and highly educated and that the data were not externally validated.

The study was supported by the National Institutes of Health and the National Institute on Aging. See the study for the full list of author disclosures.