Evidence map›Paper›PMID 37454057›Full record

ArticleBMC neurology2023

Structural brain network analysis in occipital lobe epilepsy.

Dong Ah Lee, Ho-Joon Lee, Kang Min Park

Open access · goldAbstract read
In one paragraph

Article in BMC neurology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.9field-weighted citation impact, top 28% 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

2 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. 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

3 authors at 1 institution in 1 country.

Dong Ah Lee *Department of Neurology, Haeundae Paik Hospital, Inje University College of Medicine, Busan, Korea.
Ho-Joon Lee *Department of Radiology, Haeundae Paik Hospital, Inje University College of Medicine, Busan, Korea.
Kang Min ParkDepartment of Neurology, Haeundae Paik Hospital, Inje University College of Medicine, Busan, Korea. smilepkm@hanmail.net.
Inje University Haeundae Paik Hospital · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThis study aimed to analyze the structural brain network in patients with occipital lobe epilepsy (OLE) and investigate the differences in structural brain networks between patients with OLE and healthy controls.

methodsPatients with OLE and healthy controls with normal brain MRI findings were enrolled. They underwent diffusion tensor imaging using a 3.0T MRI scanner, and we computed the network measures of global and local structural networks in patients with OLE and healthy controls using the DSI studio program. We compared network measures between the groups.

resultsWe enrolled 23 patients with OLE and 42 healthy controls. There were significant differences in the global structural network between patients with OLE and healthy controls. The assortativity coefficient (-0.0864 vs. -0.0814, p = 0.0214), mean clustering coefficient (0.0061 vs. 0.0064, p = 0.0203), global efficiency (0.0315 vs. 0.0353, p = 0.0086), and small-worldness index (0.0001 vs. 0.0001, p = 0.0175) were lower, whereas the characteristic path length (59.2724 vs. 53.4684, p = 0.0120) was higher in patients with OLE than those in the healthy controls. There were several nodes beyond the occipital lobe that showed significant differences in the local structural network between the groups. In addition, the assortativity coefficient was negatively correlated with the duration of epilepsy (r=-0.676, p = 0.001).

Indexed as

Diffusion Tensor ImagingEpilepsies, PartialBrainHumansMagnetic Resonance ImagingNerve NetOccipital LobeDiffusion tensor imagingEpilepsyOccipital lobe

Identifiers

PMID37454057
PMCPMC10349483
OpenAlexW4384406182

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.