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Published on: September 20, 2018
Clinical Manifestations
Emily W Paolillo1, Amy B Wise1, Sreya Dhanam1
1Memory and Aging Center, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA.
Objective monitoring of nighttime behaviors using bed sensors shows increased tossing and turning with greater frontotemporal dementia (FTD) severity. This technology can track disease progression and inform interventions for sleep disturbances in FTD patients.
Area of Science:
- Neuroscience
- Sleep Medicine
- Gerontology
Background:
- Sleep and circadian rhythm disturbances are prevalent but under-researched in frontotemporal dementia (FTD).
- Non-invasive sleep monitoring technologies offer objective, real-time data on sleep behaviors in naturalistic environments.
- This study investigates baseline and longitudinal nighttime bed behaviors in adults with FTD using an under-mattress sensor.
Purpose of the Study:
- To assess the feasibility of long-term, non-invasive monitoring of nighttime behaviors in individuals with FTD using bed sensors.
- To examine the relationship between clinical severity of FTD and objective measures of nighttime bed behaviors at baseline and longitudinally.
- To investigate potential differential seasonal influences on sleep behaviors across varying FTD severity levels.
Main Methods:
- 16 adults with FTD syndromes and 12 controls were monitored using an under-mattress Emfit sensor for up to two years.
- Key metrics included duration in bed, clock times of bed entry/exit, tosses/turns, and bed exits.
- Statistical analyses included Pearson correlations, linear mixed-effects regressions, and Fourier analysis to model seasonal effects.
Main Results:
- Greater FTD clinical severity correlated with longer duration in bed, more tosses/turns, and more bed exits at baseline.
- Longitudinally, higher baseline severity predicted steeper increases in tosses/turns over time.
- Individuals with moderate-to-severe FTD exhibited an attenuated response to seasonal daylight shifts compared to controls and mild FTD.
Conclusions:
- Long-term nighttime behavior monitoring via bed sensors is feasible and useful for tracking FTD progression.
- Objective sleep behavior data can provide insights into disease mechanisms and progression in FTD.
- Further research is warranted to develop targeted interventions for sleep disturbances to improve quality of life in FTD.
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