Evidence map›Paper›PMID 31121601›Full record

ArticleBrain : a journal of neurology2019

Differentiation of mild cognitive impairment using an entorhinal cortex-based test of virtual reality navigation.

David Howett, Andrea Castegnaro, Katarzyna Krzywicka, Johanna Hagman, Deepti Marchment, Richard Henson, Miguel Rio, John A King, Neil Burgess, Dennis Chan

Abstract read
In one paragraph

Article in Brain : a journal of neurology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 108 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
108citing papers in PubMed, 5 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

108 citing papers in PubMed, 5 syntheses or guidelines pooled it.

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48 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors.

David HowettDepartment of Clinical Neurosciences, University of Cambridge, Cambridge, UK.
Andrea CastegnaroInstitute of Cognitive Neuroscience, University College London, London, UK.
Katarzyna KrzywickaDepartment of Clinical Neurosciences, University of Cambridge, Cambridge, UK.
Johanna HagmanDepartment of Clinical Neurosciences, University of Cambridge, Cambridge, UK.
Deepti MarchmentDepartment of Clinical Neurosciences, University of Cambridge, Cambridge, UK.
Richard HensonMRC Cognition and Brain Sciences Unit, and Department of Psychiatry, University of Cambridge, UK.
Miguel RioDepartment of Electrical Engineering, University College London, London, UK.
John A KingDepartment of Clinical, Educational and Health Psychology, University College London, London, UK.
Neil BurgessInstitute of Cognitive Neuroscience, University College London, London, UK.
Dennis ChanDepartment of Clinical Neurosciences, University of Cambridge, Cambridge, UK.

Funding

Medical Research Council MC_UU_00005/8Medical Research Council SUAG/010 RG91365Wellcome Trust 202805/Z/16/Z
6 · The paper itself

Abstract

The entorhinal cortex is one of the first regions to exhibit neurodegeneration in Alzheimer's disease, and as such identification of entorhinal cortex dysfunction may aid detection of the disease in its earliest stages. Extensive evidence demonstrates that the entorhinal cortex is critically implicated in navigation underpinned by the firing of spatially modulated neurons. This study tested the hypothesis that entorhinal-based navigation is impaired in pre-dementia Alzheimer's disease. Forty-five patients with mild cognitive impairment (26 with CSF Alzheimer's disease biomarker data: 12 biomarker-positive and 14 biomarker-negative) and 41 healthy control participants undertook an immersive virtual reality path integration test, as a measure of entorhinal-based navigation. Behavioural performance was correlated with MRI measures of entorhinal cortex volume, and the classification accuracy of the path integration task was compared with a battery of cognitive tests considered sensitive and specific for early Alzheimer's disease. Biomarker-positive patients exhibited larger errors in the navigation task than biomarker-negative patients, whose performance did not significantly differ from controls participants. Path-integration performance correlated with Alzheimer's disease molecular pathology, with levels of CSF amyloid-β and total tau contributing independently to distance error. Path integration errors were negatively correlated with the volumes of the total entorhinal cortex and of its posteromedial subdivision. The path integration task demonstrated higher diagnostic sensitivity and specificity for differentiating biomarker positive versus negative patients (area under the curve = 0.90) than was achieved by the best of the cognitive tests (area under the curve = 0.57). This study demonstrates that an entorhinal cortex-based virtual reality navigation task can differentiate patients with mild cognitive impairment at low and high risk of developing dementia, with classification accuracy superior to reference cognitive tests considered to be highly sensitive to early Alzheimer's disease. This study provides evidence that navigation tasks may aid early diagnosis of Alzheimer's disease, and the basis of this in animal cellular and behavioural studies provides the opportunity to answer the unmet need for translatable outcome measures for comparing treatment effect across preclinical and clinical trial phases of future anti-Alzheimer's drugs.

Indexed as

Early DiagnosisVirtual RealityAgedAged, 80 and overAlzheimer DiseaseAmyloid beta-PeptidesBiomarkersCognitive DysfunctionDiagnosis, DifferentialEntorhinal CortexFemaleHumansMagnetic Resonance ImagingMaleMiddle AgedNeuropsychological TestsAmyloid beta-PeptidesBiomarkersAlzheimer’s diseaseentorhinal cortexmild cognitive impairmentpath integrationvirtual reality

Identifiers

PMID31121601
PMCPMC6536917

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Registered trials

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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.