Evidence map›Paper›PMID 26469876›Full record

ArticleScientific reports2015

Dysfunctional Default Mode Network in Methadone Treated Patients Who Have a Higher Heroin Relapse Risk.

Wei Li, Qiang Li, Defeng Wang, Wei Xiao, Kai Liu, Lin Shi, Jia Zhu, Yongbin Li, Xuejiao Yan, Jiajie Chen and 4 more

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 1 pooled it
1.3field-weighted citation impact, top 20% 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

21 citing papers in PubMed, 1 synthesis or guideline pooled it, 41 citations in OpenAlex.

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  11. Temporal Dynamics of Large-Scale Networks Predict Neural Cue Reactivity and Cue-Induced Craving.Biological psychiatry. Cognitive neuroscience and neuroimaging · 2020
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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

14 authors at 2 institutions in 1 country.

Wei LiDepartment of Radiology, Tangdu Hospital, The Fourth Military Medical University, Baqiao District, Xi'an, Shaanxi 710038, China.
Qiang LiDepartment of Radiology, Tangdu Hospital, The Fourth Military Medical University, Baqiao District, Xi'an, Shaanxi 710038, China.
Defeng WangDepartment of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong.
Wei XiaoDepartment of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong.
Kai LiuDepartment of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong.
Lin ShiDepartment of Medicine and Therapeutics, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong.
Jia ZhuDepartment of Radiology, Tangdu Hospital, The Fourth Military Medical University, Baqiao District, Xi'an, Shaanxi 710038, China.
Yongbin LiDepartment of Radiology, Tangdu Hospital, The Fourth Military Medical University, Baqiao District, Xi'an, Shaanxi 710038, China.
Xuejiao YanDepartment of Radiology, Tangdu Hospital, The Fourth Military Medical University, Baqiao District, Xi'an, Shaanxi 710038, China.
Jiajie ChenDepartment of Radiology, Tangdu Hospital, The Fourth Military Medical University, Baqiao District, Xi'an, Shaanxi 710038, China.
Jianjun YeDepartment of Radiology, Tangdu Hospital, The Fourth Military Medical University, Baqiao District, Xi'an, Shaanxi 710038, China.
Zhe LiDepartment of Radiology, Tangdu Hospital, The Fourth Military Medical University, Baqiao District, Xi'an, Shaanxi 710038, China.
Yarong WangDepartment of Radiology, Tangdu Hospital, The Fourth Military Medical University, Baqiao District, Xi'an, Shaanxi 710038, China.
Wei WangDepartment of Radiology, Tangdu Hospital, The Fourth Military Medical University, Baqiao District, Xi'an, Shaanxi 710038, China.
Air Force Medical University · CNChinese University of Hong Kong · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The purpose of this study was to identify whether heroin relapse is associated with changes in the functional connectivity of the default mode network (DMN) during methadone maintenance treatment (MMT). Resting-state functional magnetic resonance imaging (fMRI) data of chronic heroin relapsers (HR) (12 males, 1 female, age: 36.1 ± 6.9 years) and abstainers (HA) (11males, 2 female; age: 42.1 ± 8.1 years) were investigated with an independent component analysis to address the functional connectivity of their DMN. Group comparison was then performed between the relapsers and abstainers. Our study found that the left inferior temporal gyrus and the right superior occipital gyrus associated with DMN showed decreased functional connectivity in HR when compared with HA, while the left precuneus and the right middle cingulum had increased functional connectivity. Mean intensity signal, extracted from left inferior temporal gyrus of HR patients, showed a significant negative correlation corresponding to the degree of heroin relapse. These findings suggest that altered functional connectivity of DMN may contribute to the potential neurobiological mechanism(s) of heroin relapse and have a predictive value concerning heroin relapse under MMT.

Indexed as

AdultBrainBrain MappingFemaleFollow-Up StudiesHeroin DependenceHumansMagnetic Resonance ImagingMaleMethadoneMiddle AgedNeural PathwaysRadiographyRecurrenceRiskTemporal LobeMethadone

Identifiers

PMID26469876
PMCPMC4606802
OpenAlexW2395333872

What OpenQuestion holds

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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.