Driving outcomes among older adults: A systematic review on racial and ethnic differences over 20 years

The population of older adults (aged 65 years and older) in the United States will become more racially and ethnically diverse in the next three decades. Additionally, the growth of the aging population will come with an expansion in the number of older drivers and an increased prevalence of chronic neurological conditions. A major gap in the aging literature is an almost exclusive focus on homogenous, non-Hispanic white samples of older adults. It is unclear if this extends to the driving literature. A systematic review of SCOPUS, PubMed, CINAHL Plus, and Web of Science examined articles on driving and racial/ethnic differences among older adults. Eighteen studies met inclusion criteria and their results indicate that racial and ethnic minorities face a greater risk for driving reduction, mobility restriction, and driving cessation. The majority of studies compared African Americans to non-Hispanic whites but only examined race as a covariate. Only four studies explicitly examined racial/ethnic differences. Future research in aging and driving research needs to be more inclusive and actively involve different racial/ethnic groups in study design and analysis

A systematic review examining associations between cardiovascular conditions and driving outcomes among older drivers

There is a vast literature on stroke as a cardiovascular disease and driving outcomes, however little is known about other cardiovascular conditions and driving. The purpose of this review is to examine the literature for studies assessing the effect of non-stroke, vascular conditions on daily driving, reported crash risk and driving decline in older adult drivers as captured by naturalistic methodologies. A systematic review of Embase, Ovid and Scopus Plus examined articles on driving and vascular conditions among older adults. A search yielded 443 articles and, following two screenings, no articles remained that focused on non-stroke, vascular conditions and naturalistic driving. As a result, this review examined non-stroke, vascular conditions in nine driving studies of older adults that used road testing, driving simulators and self-report measures. These studies fell into three categories-heart failure, vascular dementia and white matter hyperintensities/leukoaraiosis. The combined findings of the studies suggest that heart failure, vascular dementia and white matter hyperintensities (WMH) negatively impact driving performance and contribute to driving cessation among older adults. Future research should examine cardiovascular risk factors like hypertension, hypercholesterolemia, myocardial infraction or atherosclerosis using naturalistic driving measurement, as well as traditional measures, in order to more fully characterize how these conditions impact older adult driving

Using the A/T/N framework to examine driving in preclinical Alzheimer’s disease

The A/T/N classification system is the foundation of the 2018 NIA-AA Research Framework and is intended to guide the Alzheimer disease (AD) research agenda for the next 5–10 years. Driving is a widespread functional activity that may be particularly useful in investigation of functional changes in pathological AD before onset of cognitive symptoms. We examined driving in preclinical AD using the A/T/N framework and found that the onset of driving difficulties is most associated with abnormality of both amyloid and tau pathology, rather than amyloid alone. These results have implications for participant selection into clinical trials and for the application time of interventions aimed at prolonging the time of safe driving among older adults with preclinical AD

Development and interval testing of a naturalistic driving methodology to evaluate driving behavior in clinical research [version 2; referees: 2 approved]

Background: The number of older adults in the United States will double by 2056. Additionally, the number of licensed drivers will increase along with extended driving-life expectancy. Motor vehicle crashes are a leading cause of injury and death in older adults. Alzheimer’s disease (AD) also negatively impacts driving ability and increases crash risk. Conventional methods to evaluate driving ability are limited in predicting decline among older adults. Innovations in GPS hardware and software can monitor driving behavior in the actual environments people drive in. Commercial off-the-shelf (COTS) devices are affordable, easy to install and capture large volumes of data in real-time. However, adapting these methodologies for research can be challenging. This study sought to adapt a COTS device and determine an interval that produced accurate data on the actual route driven for use in future studies involving older adults with and without AD.  Methods: Three subjects drove a single course in different vehicles at different intervals (30, 60 and 120 seconds), at different times of day, morning (9:00-11:59AM), afternoon (2:00-5:00PM) and night (7:00-10pm). The nine datasets were examined to determine the optimal collection interval. Results: Compared to the 120-second and 60-second intervals, the 30-second interval was optimal in capturing the actual route driven along with the lowest number of incorrect paths and affordability weighing considerations for data storage and curation. Discussion: Use of COTS devices offers minimal installation efforts, unobtrusive monitoring and discreet data extraction.  However, these devices require strict protocols and controlled testing for adoption into research paradigms.  After reliability and validity testing, these devices may provide valuable insight into daily driving behaviors and intraindividual change over time for populations of older adults with and without AD.  Data can be aggregated over time to look at changes or adverse events and ascertain if decline in performance is occurring

Bridging the technological divide: Stigmas and challenges with technology in digital brain health studies of older adults

The COVID-19 pandemic has increased adoption of remote assessments in clinical research. However, longstanding stereotypes persist regarding older adults\u27 technology familiarity and their willingness to participate in technology-enabled remote studies. We examined the validity of these stereotypes using a novel technology familiarity assessment

Spectrum of immune checkpoint inhibitors-induced endocrinopathies in cancer patients: a scoping review of case reports

Abstract Background Since 2011 six immune checkpoint inhibitors (ICI) have been approved to treat patients with many advanced solid tumor and hematological malignancies to improve their prognosis. Case reports of their endocrine immune-related adverse events [irAEs]) are increasingly published as more real-world patients with these malignancies are treated with these drugs. They alert physicians of a drug’s AEs (which may change during a drug’s life cycle) and contribute to post-marketing safety surveillance. Using a modified framework of Arksey and O’Malley, we conducted a scoping review of the spectrum and characteristics of ICI-induced endocrinopathies case reports before and after ICIs are marketed. Methods In July 2017, we searched, without date and language restrictions, 4 citation databases for ICI-induced endocrinopathies. We also hand-searched articles’ references, contents of relevant journals, and ran supplemental searches to capture recent reports through January 2018. For this study, a case should have information on type of cancer, type of ICI, clinical presentation, biochemical tests, treatment plus temporal association of ICI initiation with endocrinopathies. Two endocrinologists independently extracted the data which were then summarized and categorized. Results One hundred seventy nine articles reported 451 cases of ICI-induced endocrinopathies - 222 hypopituitarism, 152 thyroid disorders, 66 diabetes mellitus, 6 primary adrenal insufficiencies, 1 ACTH-dependent Cushing’s syndrome, 1 hypoparathyroidism and 3 diabetes insipidus cases. Their clinical presentations reflect hormone excess or deficiency. Some were asymptomatic and others life-threatening. One or more endocrine glands could be affected. Polyglandular endocrinopathies could present simultaneously or in sequence. Many occur within 5 months of therapy initiation; a few occurred after ICI was stopped. Mostly irreversible, they required long-term hormone replacement. High dose steroids were used when non-endocrine AEs coexisted or as therapy in adrenal insufficiency. There was variability of information in the case reports but all met the study criteria to make a diagnosis. Conclusions The spectrum of ICI-induced endocrinopathies is wide (5 glands affected) and their presentation varied (12 endocrinopathies). Clinical reasoning integrating clinical, biochemical and treatment information is needed to properly diagnose and manage them. Physicians should be vigilant for their occurrence and be able to diagnose, investigate and manage them appropriately at onset and follow-up.https://deepblue.lib.umich.edu/bitstream/2027.42/147443/1/40842_2018_Article_73.pd

Creating a driving profile for older adults using GPS devices and naturalistic driving methodology

Background/Objectives: Road tests and driving simulators are most commonly used in research studies and clinical evaluations of older drivers. Our objective was to describe the process and associated challenges in adapting an existing, commercial, off-the-shelf (COTS), in-vehicle device for naturalistic, longitudinal research to better understand daily driving behavior in older drivers. Design: The Azuga G2 Tracking DeviceTM was installed in each participant’s vehicle, and we collected data over 5 months (speed, latitude/longitude) every 30-seconds when the vehicle was driven.  Setting: The Knight Alzheimer’s Disease Research Center at Washington University School of Medicine. Participants: Five individuals enrolled in a larger, longitudinal study assessing preclinical Alzheimer disease and driving performance.  Participants were aged 65+ years and had normal cognition. Measurements:  Spatial components included Primary Location(s), Driving Areas, Mean Centers and Unique Destinations.  Temporal components included number of trips taken during different times of the day.  Behavioral components included number of hard braking, speeding and sudden acceleration events. Methods:  Individual 30-second observations, each comprising one breadcrumb, and trip-level data were collected and analyzed in R and ArcGIS.  Results: Primary locations were confirmed to be 100% accurate when compared to known addresses.  Based on the locations of the breadcrumbs, we were able to successfully identify frequently visited locations and general travel patterns.  Based on the reported time from the breadcrumbs, we could assess number of trips driven in daylight vs. night.  Data on additional events while driving allowed us to compute the number of adverse driving alerts over the course of the 5-month period. Conclusions: Compared to cameras and highly instrumented vehicle in other naturalistic studies, the compact COTS device was quickly installed and transmitted high volumes of data. Driving Profiles for older adults can be created and compared month-to-month or year-to-year, allowing researchers to identify changes in driving patterns that are unavailable in controlled conditions

Clinical impairment in premanifest and early Huntington's disease is associated with regionally specific atrophy.

TRACK-HD is a multicentre longitudinal observational study investigating the use of clinical assessments and 3-Tesla magnetic resonance imaging as potential biomarkers for future therapeutic trials in Huntington's disease (HD). The cross-sectional data from this large well-characterized dataset provide the opportunity to improve our knowledge of how the underlying neuropathology of HD may contribute to the clinical manifestations of the disease across the spectrum of premanifest (PreHD) and early HD. Two hundred and thirty nine gene-positive subjects (120 PreHD and 119 early HD) from the TRACK-HD study were included. Using voxel-based morphometry (VBM), grey and white matter volumes were correlated with performance in four domains: quantitative motor (tongue force, metronome tapping, and gait); oculomotor [anti-saccade error rate (ASE)]; cognition (negative emotion recognition, spot the change and the University of Pennsylvania smell identification test) and neuropsychiatric measures (apathy, affect and irritability). After adjusting for estimated disease severity, regionally specific associations between structural loss and task performance were found (familywise error corrected, P < 0.05); impairment in tongue force, metronome tapping and ASE were all associated with striatal loss. Additionally, tongue force deficits and ASE were associated with volume reduction in the occipital lobe. Impaired recognition of negative emotions was associated with volumetric reductions in the precuneus and cuneus. Our study reveals specific associations between atrophy and decline in a range of clinical modalities, demonstrating the utility of VBM correlation analysis for investigating these relationships in HD

White matter predicts functional connectivity in premanifest Huntington's disease

Objectives The distribution of pathology in neurodegenerative disease can be predicted by the organizational characteristics of white matter in healthy brains. However, we have very little evidence for the impact these pathological changes have on brain function. Understanding any such link between structure and function is critical for understanding how underlying brain pathology influences the progressive behavioral changes associated with neurodegeneration. Here, we demonstrate such a link between structure and function in individuals with premanifest Huntington's. Methods Using diffusion tractography and resting state functional magnetic resonance imaging to characterize white matter organization and functional connectivity, we investigate whether characteristic patterns of white matter organization in the healthy human brain shape the changes in functional coupling between brain regions in premanifest Huntington's disease. Results We find changes in functional connectivity in premanifest Huntington's disease that link directly to underlying patterns of white matter organization in healthy brains. Specifically, brain areas with strong structural connectivity show decreases in functional connectivity in premanifest Huntington's disease relative to controls, while regions with weak structural connectivity show increases in functional connectivity. Furthermore, we identify a pattern of dissociation in the strongest functional connections between anterior and posterior brain regions such that anterior functional connectivity increases in strength in premanifest Huntington's disease, while posterior functional connectivity decreases. Interpretation Our findings demonstrate that organizational principles of white matter underlie changes in functional connectivity in premanifest Huntington's disease. Furthermore, we demonstrate functional antero–posterior dissociation that is in keeping with the caudo–rostral gradient of striatal pathology in HD. The distribution of pathology in neurodegenerative disease can be predicted by the organizational characteristics of white matter in healthy brains. However, we have very little evidence for the impact these pathological changes have on brain function. Understanding any such link between structure and function is critical for understanding how underlying brain pathology influences the progressive behavioral changes associated with neurodegeneration. Here, we demonstrate such a link between structure and function in individuals with premanifest Huntington's. Methods Using diffusion tractography and resting state functional magnetic resonance imaging to characterize white matter organization and functional connectivity, we investigate whether characteristic patterns of white matter organization in the healthy human brain shape the changes in functional coupling between brain regions in premanifest Huntington's disease. Results We find changes in functional connectivity in premanifest Huntington's disease that link directly to underlying patterns of white matter organization in healthy brains. Specifically, brain areas with strong structural connectivity show decreases in functional connectivity in premanifest Huntington's disease relative to controls, while regions with weak structural connectivity show increases in functional connectivity. Furthermore, we identify a pattern of dissociation in the strongest functional connections between anterior and posterior brain regions such that anterior functional connectivity increases in strength in premanifest Huntington's disease, while posterior functional connectivity decreases. Interpretation Our findings demonstrate that organizational principles of white matter underlie changes in functional connectivity in premanifest Huntington's disease. Furthermore, we demonstrate functional antero–posterior dissociation that is in keeping with the caudo–rostral gradient of striatal pathology in HD

Visuomotor integration deficits are common to familial and sporadic preclinical Alzheimer's disease.

We investigated whether subtle visuomotor deficits were detectable in familial and sporadic preclinical Alzheimer's disease. A circle-tracing task-with direct and indirect visual feedback, and dual-task subtraction-was completed by 31 individuals at 50% risk of familial Alzheimer's disease (19 presymptomatic mutation carriers; 12 non-carriers) and 390 cognitively normal older adults (members of the British 1946 Birth Cohort, all born during the same week; age range at assessment = 69-71 years), who also underwent β-amyloid-PET/MRI to derive amyloid status (positive/negative), whole-brain volume and white matter hyperintensity volume. We compared preclinical Alzheimer's groups against controls cross-sectionally (mutation carriers versus non-carriers; amyloid-positive versus amyloid-negative) on speed and accuracy of circle-tracing and subtraction. Mutation carriers (mean 7 years before expected onset) and amyloid-positive older adults traced disproportionately less accurately than controls when visual feedback was indirect, and were slower at dual-task subtraction. In the older adults, the same pattern of associations was found when considering amyloid burden as a continuous variable (Standardized Uptake Value Ratio). The effect of amyloid was independent of white matter hyperintensity and brain volumes, which themselves were associated with different aspects of performance: greater white matter hyperintensity volume was also associated with disproportionately poorer tracing accuracy when visual feedback was indirect, whereas larger brain volume was associated with faster tracing and faster subtraction. Mutation carriers also showed evidence of poorer tracing accuracy when visual feedback was direct. This study provides the first evidence of visuomotor integration deficits common to familial and sporadic preclinical Alzheimer's disease, which may precede the onset of clinical symptoms by several years