Evidence map›Paper›PMID 42416184›Full record

ArticleAlpha psychiatry2026

Disrupted Functional Brain Network Topology in Etomidate Misuse.

Ying Tang, Xingmin Wang, Juan Le, Qiuping Huang, Hao Chen, Xinxin Chen, Xuhao Wang, Yunde Tang, Lishun Zhao, Lin Zhao and 2 more

Abstract read
In one paragraph

Article in Alpha psychiatry, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

12 authors.

Ying TangDepartment of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, 410011 Changsha, Hunan, China.ORCID https://orcid.org/0000-0001-6445-4958
Xingmin WangDepartment of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, 410011 Changsha, Hunan, China.ORCID https://orcid.org/0009-0009-5293-1644
Juan LeDepartment of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, 410011 Changsha, Hunan, China.ORCID https://orcid.org/0009-0004-8365-4583
Qiuping HuangDepartment of Psychology, School of Humanities and Management, Hunan University of Chinese Medicine, 410208 Changsha, Hunan, China.ORCID https://orcid.org/0000-0001-6899-9736
Hao ChenDepartment of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, 410011 Changsha, Hunan, China.ORCID https://orcid.org/0009-0005-2744-1759
Xinxin ChenDepartment of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, 410011 Changsha, Hunan, China.ORCID https://orcid.org/0000-0002-1447-2661
Xuhao WangDepartment of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, 410011 Changsha, Hunan, China.ORCID https://orcid.org/0009-0004-8348-0368
Yunde TangHunan Lituo Compulsory Isolation and Drug Rehabilitation Center, Hunan Lituo Drug Rehabilitation and Recovery Center, 410113 Changsha, Hunan, China.ORCID https://orcid.org/0009-0006-7969-3728
Lishun ZhaoDepartment of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, 410011 Changsha, Hunan, China.ORCID https://orcid.org/0009-0008-6161-9217
Lin ZhaoHunan Provincial Lushan Compulsory Isolation Detoxification Center, 410000 Changsha, Hunan, China.ORCID https://orcid.org/0009-0001-4714-6416
Hongxian ShenDepartment of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, 410011 Changsha, Hunan, China.ORCID https://orcid.org/0000-0002-1714-5084
Zhenjiang LiaoDepartment of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, 410011 Changsha, Hunan, China.ORCID https://orcid.org/0000-0003-3949-2682

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Etomidate misuse (EM) has recently become an increasing public health concern in East and Southeast Asia, but its neurobiological mechanisms are still not well understood. Although substance use disorders (SUDs) are commonly associated with disruptions in large-scale brain network organization, the effects of EM on brain network topology remain largely unexplored. Methods: Resting-state functional magnetic resonance imaging (rs-fMRI) data were acquired from individuals with EM and healthy controls (HC). Graph theoretical analyses were employed to and characterize global and nodal topological properties of functional brain networks. Clinical assessments captured substance use characteristics, craving, impulsivity, and addiction severity. Partial correlation analyses were conducted to examine associations between network metrics and substance use characteristics. Additonally, a support vector machine (SVM) classifier was implemented to discriminate individuals with EM from HC based on network features. Results: A total of 103 individuals with EM and 57 HC were included in the final analysis. Global topological organization that appeared was largely preserved in the EM group, with the exception of a significantly reduced clustering coefficient. At the nodal level, individuals with EM exhibited significant alterations in degree centrality, betweenness centrality, and nodal efficiency across regions predominantly distributed within the default mode, attention, and sensorimotor networks. Correlation analyses revealed no significant associations between network metrics and substance use characteristics following correction for multiple comparisons. Furthermore, the SVM model achieved moderate classification performance (accuracy = 66.7%) with an area under the curve (AUC) of 0.711. Conclusions: This study provides the first systematic investigation of the brain network topology in EM. The findings indicate widespread alterations in nodal network properties alongside relatively preserved global topological organization. While these results may offer preliminary indicators related to EM, their clinical relevance requires further in future research.

Indexed as

addictionbrain mappingetomidatemachine learningresting state functional magnetic resonance imagingsubstance-related disorders

Identifiers

PMID42416184
PMCPMC13339792

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LicenceCC BY
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Registered trials

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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.