Remote monitoring technologies in Alzheimer's disease: design of the RADAR-AD study.
Alzheimer’s disease
Remote monitoring technologies
Wearable technologies
Journal
Alzheimer's research & therapy
ISSN: 1758-9193
Titre abrégé: Alzheimers Res Ther
Pays: England
ID NLM: 101511643
Informations de publication
Date de publication:
23 04 2021
23 04 2021
Historique:
received:
28
07
2020
accepted:
11
04
2021
entrez:
24
4
2021
pubmed:
25
4
2021
medline:
25
6
2021
Statut:
epublish
Résumé
Functional decline in Alzheimer's disease (AD) is typically measured using single-time point subjective rating scales, which rely on direct observation or (caregiver) recall. Remote monitoring technologies (RMTs), such as smartphone applications, wearables, and home-based sensors, can change these periodic subjective assessments to more frequent, or even continuous, objective monitoring. The aim of the RADAR-AD study is to assess the accuracy and validity of RMTs in measuring functional decline in a real-world environment across preclinical-to-moderate stages of AD compared to standard clinical rating scales. This study includes three tiers. For the main study, we will include participants (n = 220) with preclinical AD, prodromal AD, mild-to-moderate AD, and healthy controls, classified by MMSE and CDR score, from clinical sites equally distributed over 13 European countries. Participants will undergo extensive neuropsychological testing and physical examination. The RMT assessments, performed over an 8-week period, include walk tests, financial management tasks, an augmented reality game, two activity trackers, and two smartphone applications installed on the participants' phone. In the first sub-study, fixed sensors will be installed in the homes of a representative sub-sample of 40 participants. In the second sub-study, 10 participants will stay in a smart home for 1 week. The primary outcome of this study is the difference in functional domain profiles assessed using RMTs between the four study groups. The four participant groups will be compared for each RMT outcome measure separately. Each RMT outcome will be compared to a standard clinical test which measures the same functional or cognitive domain. Finally, multivariate prediction models will be developed. Data collection and privacy are important aspects of the project, which will be managed using the RADAR-base data platform running on specifically designed biomedical research computing infrastructure. First results are expected to be disseminated in 2022. Our study is well placed to evaluate the clinical utility of RMT assessments. Leveraging modern-day technology may deliver new and improved methods for accurately monitoring functional decline in all stages of AD. It is greatly anticipated that these methods could lead to objective and real-life functional endpoints with increased sensitivity to pharmacological agent signal detection.
Sections du résumé
BACKGROUND
Functional decline in Alzheimer's disease (AD) is typically measured using single-time point subjective rating scales, which rely on direct observation or (caregiver) recall. Remote monitoring technologies (RMTs), such as smartphone applications, wearables, and home-based sensors, can change these periodic subjective assessments to more frequent, or even continuous, objective monitoring. The aim of the RADAR-AD study is to assess the accuracy and validity of RMTs in measuring functional decline in a real-world environment across preclinical-to-moderate stages of AD compared to standard clinical rating scales.
METHODS
This study includes three tiers. For the main study, we will include participants (n = 220) with preclinical AD, prodromal AD, mild-to-moderate AD, and healthy controls, classified by MMSE and CDR score, from clinical sites equally distributed over 13 European countries. Participants will undergo extensive neuropsychological testing and physical examination. The RMT assessments, performed over an 8-week period, include walk tests, financial management tasks, an augmented reality game, two activity trackers, and two smartphone applications installed on the participants' phone. In the first sub-study, fixed sensors will be installed in the homes of a representative sub-sample of 40 participants. In the second sub-study, 10 participants will stay in a smart home for 1 week. The primary outcome of this study is the difference in functional domain profiles assessed using RMTs between the four study groups. The four participant groups will be compared for each RMT outcome measure separately. Each RMT outcome will be compared to a standard clinical test which measures the same functional or cognitive domain. Finally, multivariate prediction models will be developed. Data collection and privacy are important aspects of the project, which will be managed using the RADAR-base data platform running on specifically designed biomedical research computing infrastructure.
RESULTS
First results are expected to be disseminated in 2022.
CONCLUSION
Our study is well placed to evaluate the clinical utility of RMT assessments. Leveraging modern-day technology may deliver new and improved methods for accurately monitoring functional decline in all stages of AD. It is greatly anticipated that these methods could lead to objective and real-life functional endpoints with increased sensitivity to pharmacological agent signal detection.
Identifiants
pubmed: 33892789
doi: 10.1186/s13195-021-00825-4
pii: 10.1186/s13195-021-00825-4
pmc: PMC8063580
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
89Investigateurs
Maximilian Buegler
(M)
Richard Fischer
(R)
Robbert Harms
(R)
Irene B Meier
(IB)
Ioannis Tarnanas
(I)
Ana Diaz
(A)
Jean Georges
(J)
Dianne Gove
(D)
Casper de Boer
(C)
Marijn Muurling
(M)
Pieter Jelle Visser
(PJ)
Ioannis Kompatsiaris
(I)
Ioulietta Lazarou
(I)
Lampros Mpaltadoros
(L)
Spiros Nikolopoulos
(S)
Asterios Papastergiou
(A)
Thanos Stavropoulos
(T)
Dimitris Strantsalis
(D)
Holger Froehlich
(H)
Martin Hoffman-Apitius
(M)
Meemansa Sood
(M)
Nikolay Manyakov
(N)
Vaibhav A Narayan
(VA)
Jerry G Novak
(JG)
Dorota Religa
(D)
Emilia Schwertner
(E)
Juraj Secnik
(J)
Bengt Winblad
(B)
Dag Aarsland
(D)
Pauline Conde
(P)
Amos Folarin
(A)
Grace Lavelle
(G)
Andrew P Owens
(AP)
Andrew McCarthy
(A)
Aidan Nickerson
(A)
Janneke Boere
(J)
Bruna Consiglio
(B)
Yoanna Daskalova
(Y)
Alexander Duyndam
(A)
Irene Kanter-Schlifke
(I)
Vera J M Nies
(VJM)
Pieter Stolk
(P)
Herman Verheij
(H)
Neva Coello
(N)
Jelena Curcic
(J)
Gul Erdemli
(G)
Tilo Hache
(T)
Kristin Hannesdottir
(K)
Alex Sverdlov
(A)
Vanessa Vallejo
(V)
Eric Yang
(E)
Ariel Dowling
(A)
Rouba Kozak
(R)
Melissa Naylor
(M)
Rodrigo Palma Dos Reis
(RP)
Gene Shin
(G)
Joris Borgdorff
(J)
Elisa Cirillo
(E)
Keyvan Hedayati
(K)
Nivethika Mahasivam
(N)
Aidan Doherty
(A)
Chris Hinds
(C)
Ivan Koychev
(I)
Claire Lancaster
(C)
Sebastien Libert
(S)
Federica Lucivero
(F)
Yuhao Wu
(Y)
Andre Durudas
(A)
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