Evidence map›Paper›PMID 38433494›Full record

ArticleAnnals of clinical and translational neurology2024

The thalamic covariance network is associated with cognitive deficits in patients with cerebral small vascular disease.

Wei Yan, Siwei Tang, Li Chen, Ting Lei, Haiqing Li, Yuxing Jiang, Miao He, Lijing Zhou, Yajun Li, Chen Zeng and 1 more

Open access · goldAbstract read
In one paragraph

Article in Annals of clinical and translational neurology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.5field-weighted citation impact, top 19% 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

5 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Article
  5. 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

11 authors at 1 institution in 1 country.

Wei YanDepartment of Radiology, Affilated Hospital of North Sichuan Medical College, NanChong, 637000, Sichuan, China.
Siwei TangDepartment of Radiology, Affilated Hospital of North Sichuan Medical College, NanChong, 637000, Sichuan, China.
Li ChenDepartment of Radiology, Affilated Hospital of North Sichuan Medical College, NanChong, 637000, Sichuan, China.ORCID 0009-0007-9049-2561
Ting LeiDepartment of Radiology, Affilated Hospital of North Sichuan Medical College, NanChong, 637000, Sichuan, China.
Haiqing LiDepartment of Radiology, Affilated Hospital of North Sichuan Medical College, NanChong, 637000, Sichuan, China.
Yuxing JiangDepartment of Radiology, Affilated Hospital of North Sichuan Medical College, NanChong, 637000, Sichuan, China.
Miao HeDepartment of Radiology, Affilated Hospital of North Sichuan Medical College, NanChong, 637000, Sichuan, China.
Lijing ZhouDepartment of Radiology, Affilated Hospital of North Sichuan Medical College, NanChong, 637000, Sichuan, China.
Yajun LiDepartment of Radiology, Affilated Hospital of North Sichuan Medical College, NanChong, 637000, Sichuan, China.
Chen ZengDepartment of Radiology, Affilated Hospital of North Sichuan Medical College, NanChong, 637000, Sichuan, China.
Hongjian LiDepartment of Radiology, Affilated Hospital of North Sichuan Medical College, NanChong, 637000, Sichuan, China.
North Sichuan Medical University · CN

Funding

Bureau of Science and Technology Nanchong Municipality 20SXZRKX0011Health and Family Planning Commission of Sichuan ProvinceSichuan Province Science and Technology Support Program 2019YJ0380
6 · The paper itself

Abstract

objectiveAbnormalities in the gray matter structure of cerebral small vessel disease (CSVD) have been observed throughout the brain. However, whether cortico-cortical connections exist between regions of gray matter atrophy in patients with CSVD has not been fully elucidated. This question was tested by comparing the gray matter covariance networks in CSVD patients with and without cognitive impairment (CI).

methodsWe performed multivariate modeling of the gray matter volume measurements of 61 patients with CI (CSVD-CI), 85 patients without CI (CSVD-NC), and 108 healthy controls using source-based morphological analysis (SBM) to obtain gray matter structural covariance networks at the population level. Then, correlations between structural covariance networks and cognitive functions were analyzed in CSVD patients. Finally, a support vector machine (SVM) classifier was used with the gray matter covariance network as a classification feature to identify CI among the CSVD population.

resultsThe results of the analysis of all the subjects showed that compared with healthy controls, the expression of the thalamic covariance network, cerebellum covariance network, and calcarine cortex covariance network was reduced in patients with CSVD. Moreover, CSVD-CI patients showed a significant reduction in the expression of the thalamic covariance network, encompassing the thalamus and the parahippocampal gyrus, relative to CSVD-NC patients, which persisted after excluding CSVD patients with thalamic lacunes. In patients with CSVD, cognitive functions were positively correlated with measures of the thalamic covariance network. More than 80% of CSVD patients with CI were correctly identified by the SVM classifier.

interpretationOur findings provide new evidence to explain the distribution state of gray matter reduction in CSVD patients, and the thalamic covariance network is the core region for early gray matter reduction during the development of CSVD disease, which is related to cognitive deficits. Reduced expression of thalamic covariance networks may provide a neuroimaging biomarker for the early identification of cognitive impairment in CSVD patients.

Indexed as

Cerebral Small Vessel DiseasesCognitive DysfunctionGray MatterMagnetic Resonance ImagingThalamusAgedFemaleHumansMaleMiddle AgedNerve NetSupport Vector Machine

Identifiers

PMID38433494
PMCPMC11093250
OpenAlexW4392372895

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.