Cortical amyloid deposition is one of the hallmark biomarkers of Alzheimer's disease. However, given how cost- and time-intensive amyloid imaging can be, there is a continued need for a lowcost, non-invasive, and accessible enrichment strategy to pre-screen individuals for their likelihood of amyloid prior to imaging. Previous work supports the use of coordinated limb movement as a potential screening tool, even after controlling for cognitive and daily function. Thirty-six patients diagnosed with amnestic Mild Cognitive Impairment over the age of 65 underwent 18F-Flutemetamol amyloid-positron emission tomography imaging, then completed a timed motor task involving upper limb coordination. This task takes ~5 minutes to administer and score. Multivariate linear regression and Receiver Operator Characteristic analyses showed that including motor task performance improved model prediction of amyloid burden. Results support the rationale for including functional upper extremity motor assessment as a cost- and time-effective means to screen participants for amyloid deposition.
Hippocampal atrophy is a widely used biomarker for Alzheimer's disease (AD), but the cost, time, and contraindications associated with magnetic resonance imaging (MRI) limit its use. Recent work has shown that a low-cost upper extremity motor task has potential in identifying AD risk. Fifty-four older adults (15 cognitively unimpaired, 24 amnestic Mild Cognitive Impairment, and 15 AD) completed six motor task trials and a structural MRI. Motor task acquisition significantly predicted bilateral hippocampal volume, controlling for age, sex, education, and memory. Thus, this motor task may be an affordable, non-invasive screen for AD risk and progression.
Background and Purpose: Cognitive impairment has been linked to poor motor learning and rehabilitation outcomes in older adult and stroke populations, but this remains unexplored in individuals with Parkinson disease (PD). The purpose of this secondary data analysis from a recent clinical trial (NCT02600858) was to determine if global cognition was related to nine-day skill retention after upper-extremity motor training in individuals with PD. Methods: Twenty-three participants with idiopathic PD completed three consecutive days of training on an upper-extremity task. For the purposes of the original clinical trial, participants trained either on or off their dopamine replacement medication. Baseline, training, and shorter-term (48-hour) retention data have been previously published. Global cognition was evaluated using the Montreal Cognitive Assessment (MoCA). Participant age, baseline performance, MoCA score, and group (medication on/off) were included in a multivariate linear regression model to predict longer-term (nine day) follow-up performance. Baseline and follow-up performance were assessed for all participants while on their medication. Results: MoCA score was positively related to follow-up performance, such that individuals with better cognition performed better than those with poorer cognition. Participant age, baseline performance, and medication status were unrelated to follow-up performance. Discussion and Conclusions: Results of this secondary analysis align with previous work that suggest cognitive impairment may interfere with motor learning in PD, and that assessing cognition could provide prognostic information about an individuals responsiveness to motor rehabilitation for a number of clinical populations.
Given the time-and resource-intense nature of human subjects research, we have developed a more intelligent approach to participant recruitment above and beyond random sampling that leverages pilot or preliminary results to reduce the overall number of participants needed for recruitment from an existing electronic cohort or database. Using open-access data from the General Social Survey (GSS) of the National Opinion Research Center, we generated pilot and validation datasets through a simulation to establish moderate and weak relationships based on linear regression. We then compared the performance of our residual-matching method against random sampling in their probabilities of achieving a given level of statistical power as well as their prediction accuracies. Results showed that the residual-matching method was superior to random sampling, yielding smaller sample sizes with equivalent mean square error. We therefore advocate the use of residual matching when scaling up pilot studies to conserve time and resources in larger follow-up studies.
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