Evidence map›Paper›PMID 33892789›Full record

ArticleAlzheimer's research & therapy2021

Remote monitoring technologies in Alzheimer's disease: design of the RADAR-AD study.

Marijn Muurling, Casper de Boer, Rouba Kozak, Dorota Religa, Ivan Koychev, Herman Verheij, Vera J M Nies, Alexander Duyndam, Meemansa Sood, Holger Fröhlich and 14 more

Abstract read
In one paragraph

Article in Alzheimer's research & therapy, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

30 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  9. Dream content influences daily spirituality.Frontiers in psychology · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

24 authors.

Marijn MuurlingAlzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands. m.muurling@amsterdamumc.nl.ORCID 0000-0001-9397-4602
Casper de BoerAlzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands.
Rouba KozakTakeda Pharmaceuticals International Co., Cambridge, MA, USA.
Dorota ReligaDepartment of Neurobiology, Care Sciences and Society, Karolinska Insitutet, Stockholm, Sweden.
Ivan KoychevDepartment of Psychiatry, University of Oxford, Oxford, UK.
Herman VerheijLygature, Utrecht, The Netherlands.
Vera J M NiesLygature, Utrecht, The Netherlands.
Alexander DuyndamLygature, Utrecht, The Netherlands.
Meemansa SoodFraunhofer Institute for Algorithms and Scientific Computing, University of Bonn, Bonn, Germany.
Holger FröhlichFraunhofer Institute for Algorithms and Scientific Computing, University of Bonn, Bonn, Germany.
Kristin HannesdottirNovartis Institutes for BioMedical Research, Cambridge, MA, USA.
Gul ErdemliNovartis Institutes for BioMedical Research, Cambridge, MA, USA.
Federica LuciveroEthox and Welcome Centre for Ethics and Humanities, University of Oxford, Oxford, UK.
Claire LancasterBig Data Institute, University of Oxford, Oxford, UK.
Chris HindsBig Data Institute, University of Oxford, Oxford, UK.
Thanos G StravopoulosInformation Technologies Institute, Center for Research and Technology Hellas (CERTH-ITI), Thessaloniki, Greece.
Spiros NikolopoulosInformation Technologies Institute, Center for Research and Technology Hellas (CERTH-ITI), Thessaloniki, Greece.
Ioannis KompatsiarisInformation Technologies Institute, Center for Research and Technology Hellas (CERTH-ITI), Thessaloniki, Greece.
Nikolay V ManyakovData Science and Clinical Insights, Janssen Research & Development, Beerse, Belgium.
Andrew P OwensDepartment of Old Age Psychiatry, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.
Vaibhav A NarayanJanssen Neuroscience Research & Development, Titusville, NJ, USA.
Dag AarslandDepartment of Old Age Psychiatry, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.
Pieter Jelle VisserAlzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands.
RADAR-AD Consortium

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundFunctional 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.

methodsThis 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.

resultsFirst results are expected to be disseminated in 2022.

conclusionOur 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.

Indexed as

Alzheimer DiseaseCaregiversEuropeHumansNeuropsychological TestsTechnologyAlzheimer’s diseaseRemote monitoring technologiesWearable technologies

Identifiers

PMID33892789
PMCPMC8063580

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.