Evidence map›Paper›PMID 28537993›Full record

ReviewCurrent opinion in neurology2017

Measuring compensation in neurodegeneration using MRI.

Sarah Gregory, Jeffrey D Long, Sarah J Tabrizi, Geraint Rees

Abstract readReview
In one paragraph

Review in Current opinion in neurology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
–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

20 citing papers in PubMed.

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  14. Differentiating white matter measures that protect against vs. predispose to bipolar disorder and other psychopathology in at-risk youth.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2021
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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

4 authors.

Sarah GregoryaHuntington's Disease Research Centre, UCL Institute of Neurology, London, UK bDepartments of Psychiatry and Biostatistics, University of Iowa, Iowa City, Iowa, USA cWellcome Trust Centre for Neuroimaging dInstitute of Cognitive Neuroscience, University College London, London, UK.
Jeffrey D Long
Sarah J Tabrizi
Geraint Rees

Funding

Wellcome Trust 200181
6 · The paper itself

Abstract

purpose of reviewDespite signs of cortical and subcortical loss, patients with prodromal and early-stage neurodegenerative disease are able to perform at a level comparable to the normal population. It is presumed that the onset of compensatory processes, that is changes in brain activation within a function-specific network or in the recruitment of a region outside of the task-network, underlies this maintenance of normal performance. However, in most studies to date, increased brain activity is not correlated with indices of both disease and performance and what appears to be compensation could simply be a symptom of neurodegeneration. RECENT

findingsMRI studies have explored compensation in neurodegenerative disease, claiming that compensation is evident across a number of disorders, including Alzheimer's and Parkinson's disease, but generally always in early stages; after this point, compensation is generally no longer able to operate under the severe burden of disease. However, none of these studies explicitly adopted a particular model of compensation. Thus, we also discuss our recent attempts to operationalize compensation for empirical testing. SUMMARY: There is clear evidence of compensatory processes in the early stages of neurodegenerative disease. However, for a more complete understanding, this requires more explicit empirical modelling.

Indexed as

Disease ProgressionHumansMagnetic Resonance ImagingNeurodegenerative Diseases

Identifiers

PMID28537993
PMCPMC5837021

What OpenQuestion holds

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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.