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Maintaining attention underlies many aspects of cognition and becomes compromised early in neurodegenerative diseases like Alzheimer’s disease (AD). The consistency of maintaining attention can be measured with reaction time (RT) variability. Previous work has focused on measuring such fluctuations during in-clinic testing, but recent developments in remote, smartphone-based cognitive assessments can allow one to test if these fluctuations in attention are evident in naturalistic settings and if they are sensitive to traditional clinical and cognitive markers of AD.
Method:
Three hundred and seventy older adults (aged 75.8 +/− 5.8 years) completed a week of remote daily testing on the Ambulatory Research in Cognition (ARC) smartphone platform and also completed clinical, genetic, and conventional in-clinic cognitive assessments. RT variability was assessed in a brief (20-40 seconds) processing speed task using two different measures of variability, the Coefficient of Variation (CoV) and the Root Mean Squared Successive Difference (RMSSD) of RTs on correct trials.
Results:
Symptomatic participants showed greater variability compared to cognitively normal participants. When restricted to cognitively normal participants, APOE ε4 carriers exhibited greater variability than noncarriers. Both CoV and RMSSD showed significant, and similar, correlations with several in-clinic cognitive composites. Finally, both RT variability measures significantly mediated the relationship between APOE ε4 status and several in-clinic cognition composites.
Conclusions:
Attentional fluctuations over 20–40 seconds assessed in daily life, are sensitive to clinical status and genetic risk for AD. RT variability appears to be an important predictor of cognitive deficits during the preclinical disease stage.
The purpose of the present study was to study the clinical significance of fluctuations in cognitive impairment status in longitudinal studies of normal aging and dementia. Several prior studies have shown fluctuations in cognition in longitudinal studies is associated with greater risk of conversion to dementia. The present study defines “reverters” as participants who revert between cognitive normality and abnormality according to the Clinical Dementia Rating (CDRTM). A defining feature of the CDR at the Knight Alzheimer’s Disease Research Center (Knight ADRC) at Washington University in St. Louis is that the CDR is calculated by clinicians blinded to cognitive data and any prior assessments so that conclusions are drawn free of circularity and examiner bias. We hypothesized reverters, when compared to cognitively normal participants who remain unimpaired, would have worse cognition, abnormal biomarkers, and would eventually progress to a stable diagnosis of cognitive impairment.
Participants and Methods:
From ongoing studies of aging and dementia at the Knight ADRC, we selected cognitively normal participants with at least three follow-up visits. Participants fell into three categories: stable cognitively normal (“stable CN”), converters to stable dementia (“converters”), and reverters. Cognitive scores at each visit were z-scored for comparison between groups. A subset of participants had fluid biomarker data available including cerebrospinal fluid (CSF) amyloid and phosphorylated-tau species, and plasma neurofilament light chain (NfL). Mixed effect models evaluated group relationships between biomarker status, APOE £4 status, and CDR progression.
Results:
930 participants were included in the study with an average of 5 years of follow-up (Table 1). 661 participants remained cognitively normal throughout their participation while 142 progressed to stable dementia and 127 participants had at least one instance of reversion. Compared to stable CN, reverters had more abnormal biomarkers at baseline, were more likely to carry an APOE £4 allele, and had better cognitive performance at baseline (Table 2, Figure 1). Compared to converters, reverters had less abnormal biomarkers at baseline, were less likely to carry an APOE £4 allele, and had overall better cognitive performance at baseline. In longitudinal analyses, cognitive trajectories of reverters exhibited a larger magnitude of decline compared to stable CNs but the magnitude of decline was not as steep as converters.
Conclusions:
Our results confirm prior studies that showed reversion in cognitive status, when compared to stable cognitive normality, is associated with worse overall genetic, biomarker and cognitive outcomes. Longitudinal analyses demonstrated reverters show significantly more decline than stable participants and a higher likelihood of eventual conversion to a stable dementia diagnosis. Reverters’ cognitive trajectories appear to occupy a transitional phase in disease progression between that of cognitive stability and more rapid and consistent progression to stable dementia. Identifying participants in the preclinical phase of AD who are most likely to convert to symptomatic AD is critical for secondary prevention clinical trials. Our results suggest that examining intraindividual variability in cognitive impairment using unbiased, longitudinal CDR scores may be a good indicator of preclinical AD and predict eventual conversion to symptomatic AD.
Smartphones have the potential for capturing subtle changes in cognition that characterize preclinical Alzheimer’s disease (AD) in older adults. The Ambulatory Research in Cognition (ARC) smartphone application is based on principles from ecological momentary assessment (EMA) and administers brief tests of associative memory, processing speed, and working memory up to 4 times per day over 7 consecutive days. ARC was designed to be administered unsupervised using participants’ personal devices in their everyday environments.
Methods:
We evaluated the reliability and validity of ARC in a sample of 268 cognitively normal older adults (ages 65–97 years) and 22 individuals with very mild dementia (ages 61–88 years). Participants completed at least one 7-day cycle of ARC testing and conventional cognitive assessments; most also completed cerebrospinal fluid, amyloid and tau positron emission tomography, and structural magnetic resonance imaging studies.
Results:
First, ARC tasks were reliable as between-person reliability across the 7-day cycle and test-retest reliabilities at 6-month and 1-year follow-ups all exceeded 0.85. Second, ARC demonstrated construct validity as evidenced by correlations with conventional cognitive measures (r = 0.53 between composite scores). Third, ARC measures correlated with AD biomarker burden at baseline to a similar degree as conventional cognitive measures. Finally, the intensive 7-day cycle indicated that ARC was feasible (86.50% approached chose to enroll), well tolerated (80.42% adherence, 4.83% dropout), and was rated favorably by older adult participants.
Conclusions:
Overall, the results suggest that ARC is reliable and valid and represents a feasible tool for assessing cognitive changes associated with the earliest stages of AD.
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