Evidence map›Paper›PMID 29997531›Full record

ArticleFrontiers in psychiatry2018

Deterioration in Global Organization of Structural Brain Networks in Schizophrenia: A Diffusion MRI Tractography Study.

Seung-Hyun Shon, Woon Yoon, Harin Kim, Sung Woo Joo, Yangsik Kim, Jungsun Lee

Abstract read
In one paragraph

Article in Frontiers in psychiatry, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Negative symptoms are associated with modularity and thalamic connectivity in schizophrenia.European archives of psychiatry and clinical neuroscience · 2023
    Article
  9. Increased structural connectivity in high schizotypy.Network neuroscience (Cambridge, Mass.) · 2023
    Article
  10. Article
  11. Article
  12. Article
  13. Diagnosing schizophrenia with network analysis and a machine learning method.International journal of methods in psychiatric research · 2020
    Article
  14. Review
  15. 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

6 authors.

Seung-Hyun ShonDepartment of Psychiatry, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea.
Woon YoonDepartment of Psychiatry, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea.
Harin KimKorea Armed Forces Capital Hospital, Department of Psychiatry, Seongnam, South Korea.
Sung Woo JooRepublic of Korea Marine Corps, Pohang, South Korea.
Yangsik KimGraduated School of Medical Science and Engineering, Korea Advanced Institute for Science and Technology, Daejeon, South Korea.
Jungsun LeeDepartment of Psychiatry, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Schizophrenia is a heterogenous neuropsychiatric disorder with varying degrees of altered connectivity in a wide range of brain areas. Network analysis using graph theory allows researchers to integrate and quantify relationships between widespread changes in a network system. This study examined the organization of brain structural networks by applying diffusion MRI, probabilistic tractography, and network analysis to 48 schizophrenia patients and 24 healthy controls. T1-weighted MR images obtained from all participants were parcellated into 87 regions of interests (ROIs) according to a prior anatomical template and registered to diffusion-weighted images (DWI) of the same subjects. Probabilistic tractography was performed to obtain sets of white matter tracts between any two ROIs and determine the connection probabilities between them. Connectivity matrices were constructed using these estimated connectivity probabilities, and several network properties related to network effectiveness were calculated. Global efficiency, local efficiency, clustering coefficient, and mean connectivity strength were significantly lower in schizophrenia patients (

Indexed as

connectivitydiffusion MRInetwork analysisprobabilistic tractographyschizophrenia

Identifiers

PMID29997531
PMCPMC6028716

What OpenQuestion 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 OpenQuestion graph.