Evidence map›Paper›PMID 35911591›Full record

ArticleFrontiers in human neuroscience2022

Causal Structural Covariance Network Suggesting Structural Alterations Progression in Type 2 Diabetes Patients.

Jiang Zhang, Yuyan Liu, Xiaonan Guo, Jing Guo, Zhengcong Du, Muyuan He, Qihong Liu, Dundi Xu, Taiyuan Liu, Junran Zhang and 3 more

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in human neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 2 pooled it
0.6field-weighted citation impact, top 36% 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

4 citing papers in PubMed, 2 syntheses or guidelines pooled it, 8 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Article
  4. 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

13 authors at 4 institutions in 2 countries.

Jiang ZhangCollege of Electrical Engineering, Sichuan University, Chengdu, China.
Yuyan LiuCollege of Electrical Engineering, Sichuan University, Chengdu, China.
Xiaonan GuoSchool of Information Science and Engineering, Yanshan University, Qinhuangdao, China.
Jing GuoMOE Key Lab for Neuroinformation, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, China.
Zhengcong DuSchool of Information Science and Technology, Xichang University, Xichang, China.
Muyuan HeCollege of Electrical Engineering, Sichuan University, Chengdu, China.
Qihong LiuCollege of Biomedical Engineering, Sichuan University, Chengdu, China.
Dundi XuCollege of Electrical Engineering, Sichuan University, Chengdu, China.
Taiyuan LiuDepartment of Medical Imaging, Henan Provincial People's Hospital, Zhengzhou, China.
Junran ZhangCollege of Electrical Engineering, Sichuan University, Chengdu, China.
Huijuan YuanDepartment of Endocrinology, Henan Provincial People's Hospital, Zhengzhou, China.
Meiyun WangDepartment of Medical Imaging, Henan Provincial People's Hospital, Zhengzhou, China.
Shasha LiThe Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, United States.
Sichuan University · CNHarvard University · USUniversity of Electronic Science and Technology of China · CNHenan Provincial People's Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and Purpose: According to reports, type 2 diabetes (T2D) is a progressive disease. However, no known research has examined the progressive brain structural changes associated with T2D. The purpose of this study was to determine whether T2D patients exhibit progressive brain structural alterations and, if so, how the alterations progress. Materials and Methods: Structural magnetic resonance imaging scans were collected for 81 T2D patients and 48 sex-and age-matched healthy controls (HCs). Voxel-based morphometry (VBM) and causal structural covariance network (CaSCN) analyses were applied to investigate gray matter volume (GMV) alterations and the likely chronological processes underlying them in T2D. Two sample Results: Our findings demonstrated that GMV alterations progressed in T2D patients as disease duration increased. In the early stages of the disease, the right temporal pole of T2D patients had GMV atrophy. As the diseases duration prolonged, the limbic system, cerebellum, subcortical structures, parietal cortex, frontal cortex, and occipital cortex progressively exhibited GMV alterations. The patients also exhibited a GMV alterations sequence exerting from the right temporal pole to the limbic-cerebellum-striatal-cortical network areas. Conclusion: Our results indicate that the progressive GMV alterations of T2D patients manifested a limbic-cerebellum-striatal-cortical sequence. These findings may contribute to a better understanding of the progression and an improvement of current diagnosis and intervention strategies for T2D.

Indexed as

causal structural covariance network analysisgray matter volumestructural magnetic resonance imagingtype 2 diabetesvoxel-based morphometry

Identifiers

PMID35911591
PMCPMC9336220
OpenAlexW4285492718

What Socratic holds

Textmetadata
LicenceCC BY
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 Socratic graph.