Evidence map›Paper›PMID 33807226›Full record

ArticleJournal of clinical medicine2021

Anhedonia Relates to the Altered Global and Local Grey Matter Network Properties in Schizophrenia.

Byung-Hoon Kim, Hesun Erin Kim, Jung Suk Lee, Jae-Jin Kim

Open access · goldAbstract read
In one paragraph

Article in Journal of clinical medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.6field-weighted citation impact, top 38% 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

1 citing paper in PubMed, 5 citations in OpenAlex.

  1. 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

4 authors at 1 institution in 1 country.

Byung-Hoon KimDepartment of Psychiatry, Yonsei University College of Medicine, Seoul 03722, Korea.
Hesun Erin KimInstitute of Behavioral Science in Medicine, Yonsei University College of Medicine, Seoul 03722, Korea.ORCID 0000-0001-9855-9475
Jung Suk LeeInstitute of Behavioral Science in Medicine, Yonsei University College of Medicine, Seoul 03722, Korea.
Jae-Jin KimDepartment of Psychiatry, Yonsei University College of Medicine, Seoul 03722, Korea.ORCID 0000-0002-1395-4562
Yonsei University · KR

Funding

National Research Foundation of Korea NRF-2016R1A2A2A10921744
6 · The paper itself

Abstract

Anhedonia is one of the major negative symptoms in schizophrenia and defined as the loss of hedonic experience to various stimuli in real life. Although structural magnetic resonance imaging has provided a deeper understanding of anhedonia-related abnormalities in schizophrenia, network analysis of the grey matter focusing on this symptom is lacking. In this study, single-subject grey matter networks were constructed in 123 patients with schizophrenia and 160 healthy controls. The small-world property of the grey matter network and its correlations with the level of physical and social anhedonia were evaluated using graph theory analysis. In the global scale whole-brain analysis, the patients showed reduced small-world property of the grey matter network. The local-scale analysis further revealed reduced small-world property in the default mode network, salience/ventral attention network, and visual network. The regional-level analysis showed an altered relationship between the small-world properties and the social anhedonia scale scores in the cerebellar lobule in patients with schizophrenia. These results indicate that anhedonia in schizophrenia may be related to abnormalities in the grey matter network at both the global whole-brain scale and local-regional scale.

Indexed as

anhedoniagraph theorygrey matter networkschizophrenia

Identifiers

PMID33807226
PMCPMC8038049
OpenAlexW3146389255

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.