Evidence map›Paper›PMID 37527837›Full record

ArticleThe journals of gerontology. Series A, Biological sciences and medical sciences2024

Structural Network Efficiency Predicts Conversion to Incident Parkinsonism in Patients With Cerebral Small Vessel Disease.

Mengfei Cai, Mina A Jacob, José Marques, David G Norris, Marco Duering, Rianne A J Esselink, Yuhu Zhang, Frank-Erik de Leeuw, Anil M Tuladhar

Open access · hybridAbstract read
In one paragraph

Article in The journals of gerontology. Series A, Biological sciences and medical sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.8field-weighted citation impact, top 25% 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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Article
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

9 authors at 3 institutions in 4 countries.

Mengfei CaiDepartment of Neurology, Guangdong Cardiovascular Institute, Guangdong Neuroscience Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, People's Republic of China.ORCID 0000-0003-0927-2558
Mina A JacobDepartment of Neurology, Radboud University Medical Center, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands.
José MarquesDonders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands.
David G NorrisDonders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands.
Marco DueringMedical Image Analysis Center (MIAC AG) and qbig, Department of Biomedical Engineering, University of Basel, Basel, Switzerland.ORCID 0000-0003-2302-3136
Rianne A J EsselinkDepartment of Neurology, Radboud University Medical Center, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands.
Yuhu ZhangDepartment of Neurology, Guangdong Neuroscience Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, People's Republic of China.
Frank-Erik de LeeuwDepartment of Neurology, Radboud University Medical Center, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands.
Anil M TuladharDepartment of Neurology, Radboud University Medical Center, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands.
Radboud University Nijmegen · NLGuangdong Academy of Medical Sciences · CNUniversity of Basel · CH

Funding

Dutch Heart Foundation 2016 T044Netherlands CardioVascular Research Initiative: the Dutch Heart Foundation CVON 2018-28Netherlands Organization for Health Research and Development 016.126.351
6 · The paper itself

Abstract

backgroundTo investigate whether structural network disconnectivity is associated with parkinsonian signs and their progression, as well as with an increased risk of incident parkinsonism.

methodsIn a prospective cohort (Radboud University Nijmegen Diffusion Tensor and Magnetic Resonance Cohort study) consisting of 293 participants with small vessel disease (SVD), we assessed parkinsonian signs and incident parkinsonism over an 8-year follow-up. In addition, we reconstructed the white matter network followed by graph-theoretical analyses to compute the network metrics. Conventional magnetic resonance imaging markers for SVD were assessed.

resultsWe included 293 patients free of parkinsonism at baseline (2011), with a mean age 68.8 (standard deviation [SD] 8.4) years, and 130 (44.4%) were men. Nineteen participants (6.5%) developed parkinsonism during a median (SD) follow-up time of 8.3 years. Compared with participants without parkinsonism, those with all-cause parkinsonism had higher Unified Parkinson's Disease Rating scale (UPDRS) scores and lower global efficiency at baseline. Baseline global efficiency was associated with UPDRS motor scores in 2011 (β = -0.047, p < .001) and 2015 (β = -0.84, p < .001), as well as with the changes in UPDRS scores during the 4-year follow-up (β = -0.63, p = .004). In addition, at the regional level, we identified an inter-hemispheric disconnected network associated with an increased UPDRS motor score. Besides, lower global efficiency was associated with an increased risk of all-cause and vascular parkinsonism independent of SVD markers.

conclusionsOur findings suggest that global network efficiency is associated with a gradual decline in motor performance, ultimately leading to incident parkinsonism in the elderly with SVD. Global network efficiency may have the added value to serve as a useful marker to capture changes in motor signs.

Indexed as

Cerebral Small Vessel DiseasesParkinsonian DisordersAgedCohort StudiesFemaleHumansMagnetic Resonance ImagingMaleProspective StudiesMotor disturbanceNetwork efficiencyParkinsonismSmall vessel disease

Identifiers

PMID37527837
PMCPMC10733213
OpenAlexW4385443293

What Socratic holds

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LicenceCC BY-NC
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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 Socratic graph.