Evidence map›Paper›PMID 40217323›Full record

ArticleActa epileptologica2023

Identification of a common brain network associated with lesional epilepsy.

Di Wu, Jinghui Liu, Liankun Ren

Abstract readLetter
In one paragraph

Article in Acta epileptologica, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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.

Di WuDepartment of Neurology, Clinical Center for Epilepsy, Xuanwu Hospital, Capital Medical University, NO.45 Changchun Street, Beijing, 100053, Xicheng District, China.
Jinghui LiuDepartment of Neurology, Clinical Center for Epilepsy, Xuanwu Hospital, Capital Medical University, NO.45 Changchun Street, Beijing, 100053, Xicheng District, China.
Liankun RenDepartment of Neurology, Clinical Center for Epilepsy, Xuanwu Hospital, Capital Medical University, NO.45 Changchun Street, Beijing, 100053, Xicheng District, China. renlk2022@outlook.com.ORCID http://orcid.org/0000-0001-5147-3068

Funding

Beijing Municipal Science & Technology Commission No. Z211100002921032National Key R&D Program of China No. 2022YFC2503800National Natural Science Foundation of China No. 82071454
6 · The paper itself

Abstract

Stroke is the leading cause of neurological diseases globally. Remarkably, epilepsy is a common complication of stroke, which greatly impairs the quality of life of patients and poses a significant clinical challenge. Therefore, a better understanding of the risk factors for poststroke epilepsy is crucial. A recent study published in JAMA Neurology studied the brain network associated with poststroke epilepsy in a group of 76 patients compared to a cohort of 625 control patients using lesion mapping techniques. The results showed that negative functional connectivity between lesion locations and regions in the basal ganglia and cerebellum confers a higher risk of developing epilepsy after stroke. The lesion network nodes associated with epilepsy were identical across different lesion types including hematomas, traumas, tumors, and tubers. Furthermore, the poststroke epilepsy brain network has potential therapeutic relevance to deep brain stimulation (DBS). In a cohort of 30 patients, the functional connectivity between anterior thalamic DBS sites and the lesion network nodes was found to correlate with seizure control after DBS. In summary, the finding provides a novel method for predicting the risk of poststroke epilepsy in patients and may guide brain stimulation treatments for epilepsy.

Indexed as

Brain networkLesion network mappingNeuromodulationPoststroke epilepsy

Identifiers

PMID40217323
PMCPMC11960254

What OpenQuestion holds

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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.