Evidence map›Paper›PMID 34366726›Full record

ArticleContrast media & molecular imaging2021

Integration and Segregation of Dynamic Functional Connectivity States for Mild Cognitive Impairment Revealed by Graph Theory Indicators.

Zhuqing Jiao, Peng Gao, Yixin Ji, Haifeng Shi

Abstract read
In one paragraph

Article in Contrast media & molecular imaging, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
–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

10 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  10. BCNet: A Novel Network for Blood Cell Classification.Frontiers in cell and developmental biology · 2021
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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

4 authors.

Zhuqing JiaoSchool of Computer Science and Artificial Intelligence, Changzhou University, Changzhou 213164, China.ORCID 0000-0002-6547-8449
Peng GaoSchool of Computer Science and Artificial Intelligence, Changzhou University, Changzhou 213164, China.
Yixin JiSchool of Computer Science and Artificial Intelligence, Changzhou University, Changzhou 213164, China.
Haifeng ShiDepartment of Radiology, Changzhou Second People's Hospital Affiliated to Nanjing Medical University, Changzhou 213003, China.ORCID 0000-0002-5825-1959

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mild cognitive impairment (MCI) is an intermediate stage between normal aging and dementia. Researchers tend to discuss its early state (early MCI, eMCI) due to its high conversion rate of dementia and poor treatment effect in the middle and late stages. Currently, the research on the disease evolution of the brain functional networks of patients with MCI has gradually become a research hotspot. In this study, we compare the differences in dynamic functional connectivity among eMCI, late MCI (lMCI), and normal control (NC) groups, and their graph theory indicators reveal the integration and segregation of functional connectivity states. Firstly, dynamic functional network windows were constructed based on the sliding time window method, and then these window samples were clustered by

Indexed as

Neural PathwaysSignal Processing, Computer-AssistedBrain MappingCognitive DysfunctionFunctional NeuroimagingHumansMagnetic Resonance ImagingPrognosis

Identifiers

PMID34366726
PMCPMC8313367

What OpenQuestion holds

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LicenceCC BY
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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.