Alzheimer's disease and driving: review of the literature and consensus guideline from Belgian dementia experts and the Belgian road safety institute endorsed by the Belgian Medical Association

Performance Analysis of Driving Ability (P-Drive): Investigating Construct Validity and Concordance of Australasian Data

On-road assessment is optimal for determining medical fitness-to-drive but unreliable if determined by global pass/fail decisions alone. Occupational therapists need standardized, psychometrically sound on-road scoring procedures. Performance Analysis of Driving Ability (P-Drive) is a promising on-road test developed in Sweden, but it has not been standardized for Australasia. We investigated the psychometric properties and concordance with an on-road decision of data gathered with the Australasian version of P-Drive. P-Drive was administered to older and cognitively impaired drivers (N = 134) aged 18 to 91 years (mean age 68) who were referred to 10 driving clinics in Australia and New Zealand to determine driving performance. Rasch analysis provided evidence for construct validity and concordance of the data gathered. An optimal cut-off score of 85 was set, yielding evidence of good sensitivity at 88% and specificity at 88%. The Australasian version of P-Drive produces valid and reliable data regarding on-road driving performance.

Refining a Driving Retirement Program for Persons With Dementia and Their Care Partners: A Mixed Methods Evaluation of CarFreeMe™-Dementia

OBJECTIVES

We adapted the CarFreeMe™-Dementia program created by The University of Queensland for drivers in the United States. CarFreeMe™-Dementia aims to assist drivers living with dementia and their care partners as they plan for or adjust to driving retirement. This semistructured program focuses on driving retirement education and support. Topics include how dementia affects driving, lifestyle planning, stress management, and alternative transportation options. This study evaluated the feasibility, acceptability, and utility of the CarFreeMe™-Dementia intervention.

METHODS

This pilot phase of the study included 16 care partners and 11 drivers with memory loss who were preparing for or adjusting to driving retirement. Participants completed 4-8 CarFreeMe™-Dementia intervention telehealth sessions. Online surveys (baseline, 1- and 3-month) and postintervention semistructured interviews informed evaluation of the intervention program using a mixed methods approach.

RESULTS

This study established initial support for CarFreeMe™-Dementia in the United States. Participants indicated the program facilitated dialogue around driving retirement and provided guidance on community engagement without driving. Respondents appreciated the program's emphasis on overall well-being, promoted through lifestyle planning and stress management. They also reported the program offered practical preparation for transitioning to driving retirement.

DISCUSSION

The CarFreeMe™-Dementia intervention, tailored to an American audience, appears to be a feasible, acceptable, and useful support program for drivers with memory loss (and/or their care partners) who are preparing for or adjusting to driving retirement. Further investigations of the efficacy of the CarFreeMe™-Dementia intervention in the United States, as well as in other countries and cultural contexts, are warranted.

Evaluation of Error Production in Animal Fluency and Its Relationship to Frontal Tracts in Normal Aging and Mild Alzheimer's Disease: A Combined LDA and Time-Course Analysis Investigation

Semantic verbal fluency (VF), assessed by animal category, is a task widely used for early detection of dementia. A feature not regularly assessed is the occurrence of errors such as perseverations and intrusions. So far, no investigation has analyzed the how and when of error occurrence during semantic VF in aging populations, together with their possible neural correlates. The present study aims to address the issue using a combined methodology based on latent Dirichlet allocation (LDA) analysis for word classification together with a time-course analysis identifying exact time of errors' occurrence. LDA is a modeling technique that discloses hidden semantic structures based on a given corpus of documents. We evaluated a sample of 66 participants divided into a healthy young group (n = 24), healthy older adult group (n = 23), and group of patients with mild Alzheimer's disease (AD) (n = 19). We performed DTI analyses to evaluate the white matter integrity of three frontal tracts purportedly underlying error commission: anterior thalamic radiation, frontal aslant tract, and uncinate fasciculus. Contrasts of DTI metrics were performed on the older groups who were further classified into high-error rate and low-error rate subgroups. Results demonstrated a unique deployment of error commission in the patient group characterized by high incidence of intrusions in the first 15 s and higher rate of perseverations toward the end of the trial. Healthy groups predominantly showed very low incidence of perseverations. The DTI analyses revealed that the patients with AD committing high-error rate presented significantly more degenerated frontal tracts in the left hemisphere. Thus, our findings demonstrated that the appearance of intrusions, together with left hemisphere degeneration of frontal tracts, is a pathognomic trait of mild AD. Furthermore, our data suggest that the error commission of patients with AD arises from executive and working memory impairments related partly to deteriorated left frontal tracts.

Deep transfer learning of structural magnetic resonance imaging fused with blood parameters improves brain age prediction

Machine learning has been applied to neuroimaging data for estimating brain age and capturing early cognitive impairment in neurodegenerative diseases. Blood parameters like neurofilament light chain are associated with aging. In order to improve brain age predictive accuracy, we constructed a model based on both brain structural magnetic resonance imaging (sMRI) and blood parameters. Healthy subjects (n = 93; 37 males; aged 50–85 years) were recruited. A deep learning network was firstly pretrained on a large set of MRI scans (n = 1,481; 659 males; aged 50–85 years) downloaded from multiple open‐source datasets, to provide weights on our recruited dataset. Evaluating the network on the recruited dataset resulted in mean absolute error (MAE) of 4.91 years and a high correlation (r = .67, p <.001) against chronological age. The sMRI data were then combined with five blood biochemical indicators including GLU, TG, TC, ApoA1 and ApoB, and 9 dementia‐associated biomarkers including ApoE genotype, HCY, NFL, TREM2, Aβ40, Aβ42, T‐tau, TIMP1, and VLDLR to construct a bilinear fusion model, which achieved a more accurate prediction of brain age (MAE, 3.96 years; r = .76, p <.001). Notably, the fusion model achieved better improvement in the group of older subjects (70–85 years). Extracted attention maps of the network showed that amygdala, pallidum, and olfactory were effective for age estimation. Mediation analysis further showed that brain structural features and blood parameters provided independent and significant impact. The constructed age prediction model may have promising potential in evaluation of brain health based on MRI and blood parameters.

Driving and Alzheimer's dementia or mild cognitive impairment: a systematic review of the existing guidelines emphasizing on the neurologist's role

BACKGROUND

Driving is a complex task requiring the integrity and the cooperation of cognition, motor, and somatosensory skills, all of which are impacted by neurological diseases.

OBJECTIVE

Identification of neurologist's role when assessing fitness to drive of cognitively impaired individuals.

METHODS

We performed a systematic review of the guidelines/recommendations (G/Rs) regarding the evaluation of driving fitness of patients with mild cognitive impairment (MCI) and/or dementia. Emphasis was put on the neurological and neuropsychological aspects of the evaluation.

RESULTS

Eighteen G/Rs were included in the review (9 national guidelines, 5 recommendation papers, 3 consensus statements, and 1 position paper). All G/Rs referred to drivers with dementia and 9/18 referred to drivers with MCI. A common approach among G/Rs is the initial trichotomization of patients in safe to drive, unsafe to drive, and undetermined cases, which are referred to a second-line evaluator. First-line evaluators are general practitioners in 10/18 G/Rs; second-line evaluators are neurologists in 7/18 G/Rs. Specific neuropsychological tests are proposed in 11/18 G/Rs and relative cut-off values in 7/18. The most commonly used tests are the MMSE, TMT, and CDT. A thorough neurological examination is proposed in only 1/18 G/R.

CONCLUSION

Although extensive multi-disciplinary research has provided useful information for driving behavior of cognitively impaired individuals, we are still far from a widely accepted approach of driving ability evaluation in this increasing population. A comprehensive assessment from a multi-disciplinary team in which the neurologist plays a critical role seems to be required, although this has not yet been implemented in any G/Rs.

The management of dementia by flemish GPs: it remains a difficult job

Objective: The following study examines how GPs in Flanders deal with dementia in terms of detection, diagnosis, care diagnosis and treatment.Methods: An online survey was sent out by mail to 5113 Flemish GP's. Data were collected in 2016. The results were processed in a univariate and multivariate analysis with SAS 9.4Results: 331 GPs completed the survey in full (response rate 6.47%). The results are representative of GPs of the Flemish Region in terms of distribution across the provinces and university of graduation. 82.78% use the MMSE and 5.44% the DSM criteria. A blood analysis was performed by 80.97%, aCT or MRI by 23.56% and 17,22% respectively. Nine out of 331 mapped out the full care planning. The Katz scale was used rarely or never by 25.38%. The physical condition of the caregivers was enquired about by 91.69% and their mental state by 96.92%. Acetylcholinesterase inhibitors were prescribed by 94.56%, memantine by 57.70%, ginkgo biloba by 49.85%. 89.73% prefers a medical approach for hallucinations and delusions, 65.26% for aggression, 50.78% for agitation, 71.30% for depression and 48.34% for sleep disorders. Older GPs felt their knowledge was insufficient and used more pharmacological treatments.Conclusion: GPs are unfamiliar with available detection and diagnostic possibilities. GPs include history taking of carers but underuse available support tools, biochemical analyses and imaging. Post diagnostic care is mapped out insufficiently, despite the fact that GPs focus adequately on their patients' caregivers. In the pharmacological treatment there is a notable discrepancy between what GPs think and do. Pharmacological policy in behavioural bymptoms is most common. GPs highly value the possibility of receiving support by reference physicians.

EEG-Based Neurocognitive Metrics May Predict Simulated and On-Road Driving Performance in Older Drivers

The number of older drivers is steadily increasing, and advancing age is associated with a high rate of automobile crashes and fatalities. This can be attributed to a combination of factors including decline in sensory, motor, and cognitive functions due to natural aging or neurodegenerative diseases such as HIV-Associated Neurocognitive Disorder (HAND). Current clinical assessment methods only modestly predict impaired driving. Thus, there is a need for inexpensive and scalable tools to predict on-road driving performance. In this study EEG was acquired from 39 HIV+ patients and 63 healthy participants (HP) during: 3-Choice-Vigilance Task (3CVT), a 30-min driving simulator session, and a 12-mile on-road driving evaluation. Based on driving performance, a designation of Good/Poor (simulator) and Safe/Unsafe (on-road drive) was assigned to each participant. Event-related potentials (ERPs) obtained during 3CVT showed increased amplitude of the P200 component was associated with bad driving performance both during the on-road and simulated drive. This P200 effect was consistent across the HP and HIV+ groups, particularly over the left frontal-central region. Decreased amplitude of the late positive potential (LPP) during 3CVT, particularly over the left frontal regions, was associated with bad driving performance in the simulator. These EEG ERP metrics were shown to be associated with driving performance across participants independent of HIV status. During the on-road evaluation, Unsafe drivers exhibited higher EEG alpha power compared to Safe drivers. The results of this study are 2-fold. First, they demonstrate that high-quality EEG can be inexpensively and easily acquired during simulated and on-road driving assessments. Secondly, EEG metrics acquired during a sustained attention task (3CVT) are associated with driving performance, and these metrics could potentially be used to assess whether an individual has the cognitive skills necessary for safe driving.

Vestibular Function and Beta-Amyloid Deposition in the Baltimore Longitudinal Study of Aging

Beta-amyloid (Aβ) plaque deposition is a key feature of Alzheimer’s disease (AD), and occurs years before the onset of symptoms. Aβ plaque deposition has been shown to be present in ~30% of cognitively normal older adults using amyloid C-11 labeled Pittsburgh Compound B (¹¹C-PiB) Positron Emission Tomography (PET) imaging. Prior studies have reported a link between reduced vestibular function and poorer cognition in healthy older adults. It is unknown whether vestibular impairment occurs in association with AD pathology among individuals in the preclinical phase of AD, which could contribute to the observed association between vestibular and cognitive function in healthy older adults. Using the Baltimore Longitudinal Study of Aging (BLSA), we analyzed the association between a comprehensive set of vestibular function measures and PiB status in 98 healthy participants with a mean age of 77.3 (±8.26). We did not observe a significant relationship between any vestibular function measure and PiB status in cognitively-intact older adults in the BLSA. This finding suggests that Aβ deposition does not explain the observed association between reduced vestibular function and poorer cognition in healthy older adults.

The MMSE should not be the sole indicator of fitness to drive in mild Alzheimer's dementia

Since Alzheimer’s disease may affect driving performance, patients with Alzheimer’s disease are assessed on fitness to drive. On-road driving assessments are widely used, and attempts have also been made to develop strategies to assess fitness to drive in a clinical setting. Preferably, a first indication of fitness to drive is obtained quickly after diagnosis using a single test such as the Mini-Mental State Examination (MMSE). The aim of this study is to investigate whether the MMSE can be used to predict whether patients with Alzheimer’s disease will pass or fail an on-road driving assessment. Patients with Alzheimer’s disease (n = 81) participated in a comprehensive fitness-to-drive assessment which included the MMSE as well as an on-road driving assessment [PLoS One 11(2):e0149566, 2016]. MMSE cutoffs were applied as suggested by Versijpt and colleagues [Acta Neurol Belg 117(4):811–819, 2017]. All patients with Alzheimer’s disease who scored below the lower cutoff (MMSE ≤ 19) failed the on-road driving assessment. However, a third of the patients with Alzheimer’s disease who scored above the upper cutoff (MMSE ≥ 25) failed the on-road driving assessment as well. We conclude that the MMSE alone has insufficient predictive value to correctly identify fitness to drive in patients with very mild-to-mild Alzheimer’s disease implicating the need for comprehensive assessments to determine fitness to drive in a clinical setting.