Evidence map›Paper›PMID 29614664›Full record

ArticleJournal of Alzheimer's disease : JAD2018

Gait in Mild Alzheimer's Disease: Feasibility of Multi-Center Measurement in the Clinic and Home with Body-Worn Sensors: A Pilot Study.

Ríona Mc Ardle, Rosie Morris, Aodhán Hickey, Silvia Del Din, Ivan Koychev, Roger N Gunn, Jennifer Lawson, Giovanna Zamboni, Basil Ridha, Barbara J Sahakian and 7 more

Erratum issuedOpen access · greenAbstract readMulticenter Study
In one paragraph

Article in Journal of Alzheimer's disease : JAD, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 34 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed, 4 pooled it
4.7field-weighted citation impact, top 4% of its field
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

34 citing papers in PubMed, 4 syntheses or guidelines pooled it, 59 citations in OpenAlex.

  1. Pooled it
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  9. Capture of Longitudinal Change in Real-Life Walking in Cerebellar Ataxia Increases Patient Relevance and Effect Size.Movement disorders : official journal of the Movement Disorder Society · 2025
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  10. Review
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  12. DUI Detection From Gait Using a Multichannel 1DCNN-Attention-BiLSTM Framework.IEEE access : practical innovations, open solutions · 2025
    Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

17 authors at 5 institutions in 2 countries.

Ríona Mc ArdleInstitute of Neuroscience, Newcastle University, Newcastle, UK.
Rosie MorrisInstitute of Neuroscience, Newcastle University, Newcastle, UK.
Aodhán HickeyInstitute of Neuroscience, Newcastle University, Newcastle, UK.
Silvia Del DinInstitute of Neuroscience, Newcastle University, Newcastle, UK.
Ivan KoychevUK Department of Psychiatry, University of Oxford, UK.
Roger N GunnMANOVA Ltd, London, UK.
Jennifer LawsonUK Department of Psychiatry, University of Oxford, UK.
Giovanna ZamboniUK Department of Psychiatry, University of Oxford, UK.
Basil RidhaNIHR Queen Square Dementia Biomedical Research Unit, University College London, UK.
Barbara J SahakianDepartment of Psychiatry, University of Cambridge, UK.
James B RoweDepartment of Clinical Neurosciences, University of Cambridge, UK and MRC Cognition and Brain Sciences Unit, Cambridge, UK.
Alan ThomasInstitute of Neuroscience, Newcastle University, Newcastle, UK.
Henrik ZetterbergClinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden.
Clare MacKayUK Department of Psychiatry, University of Oxford, UK.
Simon LovestoneUK Department of Psychiatry, University of Oxford, UK.
Lynn RochesterInstitute of Neuroscience, Newcastle University, Newcastle, UK.
Deep and Frequent Phenotyping study team (
University of Oxford · GBNewcastle University · GBMRC Cognition and Brain Sciences Unit · GBSahlgrenska University Hospital · SEUniversity of Cambridge · GB

Funding

Medical Research Council MC_U105597119Medical Research Council MC_UU_00005/12Medical Research Council MR/L023784/1Medical Research Council MR/L023784/2Medical Research Council MR/N029941/1Wellcome Trust 103838
6 · The paper itself

Abstract

Gait is emerging as a potential diagnostic tool for cognitive decline. The 'Deep and Frequent Phenotyping for Experimental Medicine in Dementia Study' (D&FP) is a multicenter feasibility study embedded in the United Kingdom Dementia Platform designed to determine participant acceptability and feasibility of extensive and repeated phenotyping to determine the optimal combination of biomarkers to detect disease progression and identify early risk of Alzheimer's disease (AD). Gait is included as a clinical biomarker. The tools to quantify gait in the clinic and home, and suitability for multi-center application have not been examined. Six centers from the National Institute for Health Research Translational Research Collaboration in Dementia initiative recruited 20 individuals with early onset AD. Participants wore a single wearable (tri-axial accelerometer) and completed both clinic-based and free-living gait assessment. A series of macro (behavioral) and micro (spatiotemporal) characteristics were derived from the resultant data using previously validated algorithms. Results indicate good participant acceptability, and potential for use of body-worn sensors in both the clinic and the home. Recommendations for future studies have been provided. Gait has been demonstrated to be a feasible and suitable measure, and future research should examine its suitability as a biomarker in AD.

Indexed as

Wearable Electronic DevicesAccelerometryAgedAged, 80 and overAlzheimer DiseaseCognition DisordersFeasibility StudiesFemaleGait Disorders, NeurologicHumansMaleMiddle AgedNeuropsychological TestsPilot ProjectsPsychiatric Status Rating ScalesTime FactorsAlzheimer’s diseasecognitionfree-livinggaitphenotypingwearables

Identifiers

PMID29614664
PMCPMC7617011
OpenAlexW2786725461

What OpenQuestion holds

Textmetadata
LicenceTDM
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 OpenQuestion graph.