Evidence map›Paper›PMID 32314197›Full record

ArticleBrain imaging and behavior2021

Altered resting-state functional networks in patients with hemodialysis: a graph-theoretical based study.

Mei Jin, Liyan Wang, Hao Wang, Xue Han, Zongli Diao, Wang Guo, Zhenghan Yang, Heyu Ding, Zheng Wang, Peng Zhang and 4 more

Abstract read
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In one paragraph

Article in Brain imaging and behavior, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
1.8field-weighted citation impact, top 15% 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

12 citing papers in PubMed, 1 synthesis or guideline pooled it, 23 citations in OpenAlex.

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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.

Mei JinDepartment of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China.
Liyan WangDepartment of Nephrology, Faculty of Kidney Diseases, Beijing Friendship Hospital, Capital Medical University, Beijing, China.
Hao WangDepartment of Nephrology, Faculty of Kidney Diseases, Beijing Friendship Hospital, Capital Medical University, Beijing, China.
Xue HanDepartment of Nephrology, Faculty of Kidney Diseases, Beijing Friendship Hospital, Capital Medical University, Beijing, China.
Zongli DiaoDepartment of Nephrology, Faculty of Kidney Diseases, Beijing Friendship Hospital, Capital Medical University, Beijing, China.
Wang GuoDepartment of Nephrology, Faculty of Kidney Diseases, Beijing Friendship Hospital, Capital Medical University, Beijing, China.
Zhenghan YangDepartment of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China.
Heyu DingDepartment of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China.
Zheng WangDepartment of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China.
Peng ZhangDepartment of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China.
Pengfei ZhaoDepartment of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China.
Han LvDepartment of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China.
Wenhu LiuDepartment of Nephrology, Faculty of Kidney Diseases, Beijing Friendship Hospital, Capital Medical University, Beijing, China.
Zhenchang WangDepartment of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China. cjr.wzhch@vip.163.com.
Beijing Friendship Hospital · CNCapital Medical University · CN

Funding

Beijing Friendship Hospital, Capital Medical University YYZZ2017B01Beijing Municipal Administration of Hospitals PX2018001Beijing Municipal Administration of Hospitals QML20180103Beijing Municipal Administration of Hospitals SML20150101Beijing Natural Science Foundation 7162048Beijing Natural Science Foundation 7172064Beijing Natural Science Foundation 7182044Beijing Scholars Program [2015] 160National Natural Science Foundation of China 61527807National Natural Science Foundation of China 61801311National Natural Science Foundation of China 81701644
6 · The paper itself

Abstract

Recent studies have demonstrated that hemodialysis patients exhibit disruptions in functional networks with invisible cerebral alterations. We explored the alterations of functional connectivity in hemodialysis patients using the graph-theory method. A total of 46 hemodialysis patients (53.11 ± 1.58 years, 28 males) and 47 healthy controls (55.57 ± 0.86 years, 22 males) were scanned by using resting-state functional magnetic resonance imaging. The brains of these patients were divided into 90 regions and functional connectivity was constructed with the automatic anatomical labeling atlas. In the defined threshold range, the graph-theory analysis was performed to compare the topological properties including global, regional and edge parameters between the hemodialysis and the healthy control groups. Both hemodialysis patients and healthy control subjects demonstrated common small-world property of the brain functional connections. At the global level, the parameters normalized clustering coefficients and small-worldness were significantly decreased in hemodialysis patients compared with those noted in healthy controls. At the regional level, abnormal nodal metrics (increased or decreased nodal degree, betweenness centrality and efficiency) were widely found in hemodialysis patients compared with those of healthy controls. The network-based statistical method was employed and two disrupted neural circuits with 18 nodes and 19 edges (P = 0.0139, corrected) and 10 nodes and 11 edges (P = 0.0399, corrected) were detected. Of note, the edge-increased functional connectivity was associated with the salience network and the frontal-temporal-basal ganglia connection, whereas the edge-decreased functional connectivity was associated with the frontoparietal network. The graph-theory method may be one of the potential tools to detect disruptions of cerebral functional connectivity and provide important evidence for understanding the neuropathology of hemodialysis patients from the disrupted network organization perspective.

Indexed as

BrainMagnetic Resonance ImagingBrain MappingHumansMaleModels, TheoreticalNerve NetRenal DialysisEnd-stage renal diseaseFunctional magnetic resonance imagingGraph-theory analysisHemodialysisNetwork-based statistics

Identifiers

PMID32314197
OpenAlexW3016939712

What OpenQuestion holds

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Read underepoch 390

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.