Introduction: Agitation, experienced by patients with dementia, is difficult to manage and stressful for caregivers. Currently, agitation is primarily assessed by caregivers or clinicians based on self-report or very brief periods of observation. This limits availability of comprehensive or sensitive enough reporting to detect early signs of agitation or identify its precipitants. The purpose of this article is to provide proof of concept for characterizing and predicting agitation using a system that continuously monitors patients' activities and living environment within memory care facilities.
Methods: Continuous and unobtrusive monitoring of a participant is achieved using behavioral sensors, which include passive infrared motion sensors, door contact sensors, a wearable actigraphy device, and a bed pressure mat sensor installed in the living quarters of the participant. Environmental sensors are also used to continuously assess temperature, light, sound, and humidity. Episodes of agitation are reported by nursing staff. Data collected for 138 days were divided by 8-hour nursing shifts. Features from agitated shifts were compared to those from non-agitated shifts using -tests.
Results: A total of 37 episodes of agitation were reported for a male participant, aged 64 with Alzheimer's disease, living in a memory care unit. Participant activity metrics (eg, transitions within the living room, sleep scores from the bedmat, and total activity counts from the actigraph) significantly correlated with occurrences of agitation at night ( < 0.05). Environmental variables (eg, humidity) also correlated with the occurrences of agitation at night ( < 0.05). Higher activity levels were also observed in the evenings before agitated nights.
Discussion: A platform of sensors used for unobtrusive and continuous monitoring of participants with dementia and their living space seems feasible and shows promise for characterization of episodes of agitation and identification of behavioral and environmental precipitants of agitation.
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http://dx.doi.org/10.1002/trc2.12079 | DOI Listing |
Postgrad Med J
January 2025
Proof of Concept Center, Eastern Hepatobiliary Surgery Hospital, Third Affiliated Hospital, Second Military Medical University, Naval Medical University, No. 255, Yangpu District, Shanghai, 200433, China.
Objectives: The objective was to investigate the role of double extraction in reducing data errors in evidence synthesis for pharmaceutical and non-pharmaceutical interventions.
Design: Crossover randomized controlled trial (RCT).
Setting: University and hospital with teaching programs in evidence-based medicine.
Front Transplant
December 2024
Laboratory of Respiratory Diseases and Thoracic Surgery (BREATHE), Department of CHROMETA, KU Leuven, Leuven, Belgium.
Long-term survival after lung transplantation is limited due to chronic lung allograft dysfunction (CLAD), which encompasses two main phenotypes: bronchiolitis obliterans syndrome (BOS) and restrictive allograft syndrome (RAS). Donor-derived cell-free DNA (dd-cfDNA) is a biomarker for (sub)clinical allograft injury and could be a tool for monitoring of lung allograft health across the (pre)clinical spectrum of CLAD. In this proof-of-concept study, we therefore assessed post-transplant plasma dd-cfDNA levels in 20 CLAD patients (11 BOS and 9 RAS) at three consecutive time points free from concurrent infection or acute rejection, during stable condition, preclinical CLAD, and established CLAD ( = 3 × 20 samples).
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