Evidence map›Paper›PMID 41357947›Full record

ArticleWorld journal of psychiatry2025

Correlation between anxiety-depression disorders and brain structural connectivity abnormalities after subarachnoid hemorrhage.

Lei Qin, Kai Wang, Li-Ping Jiang, Zhang Xiao, Song Luo

Abstract read
In one paragraph

Article in World journal of psychiatry, 2025. 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.

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2 · The registry

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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.

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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

5 authors.

Lei QinDepartment of Radiology, The First Affiliated Hospital of Bengbu Medical University, Bengbu 233004, Anhui Province, China.
Kai WangDepartment of Radiology, The First Affiliated Hospital of Bengbu Medical University, Bengbu 233004, Anhui Province, China.
Li-Ping JiangDepartment of Radiology, The Second Affiliated Hospital of Bengbu Medical University, Bengbu 233002, Anhui Province, China.
Zhang XiaoDepartment of Radiology, The First Affiliated Hospital of Bengbu Medical University, Bengbu 233004, Anhui Province, China.
Song LuoDepartment of Neurology, The First Affiliated Hospital of Bengbu Medical University, Bengbu 233004, Anhui Province, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSubarachnoid hemorrhage (SAH) is associated with high incidence of anxiety and depression disorders (27%-54% and 20%-42%, respectively), significantly affecting patient quality of life. However, the pathophysiological mechanisms underlying post-SAH emotional disorders remain poorly understood, limiting targeted therapeutic interventions.

aimTo identify potential biomarkers and therapeutic targets through comprehensive analysis of behavioral, neuroimaging, and inflammatory parameters in a rat SAH model.

methodsWe established a rat SAH model using cisternal injection of autologous blood and conducted comprehensive assessments including behavioral tests (elevated plus maze, forced swimming test, sucrose preference test), diffusion tensor imaging (DTI), and inflammatory factor detection. Seventy-two male SD rats were randomly divided into sham and SAH groups, with evaluations performed at multiple time points (1 hour to 72 hours post-hemorrhage). DTI parameters including fractional anisotropy (FA) and apparent diffusion coefficient were measured in limbic-prefrontal circuits. Serum and cerebrospinal fluid inflammatory markers [interleukin-6 (IL-6), IL-1β, tumor necrosis factor-α] were quantified using enzyme-linked immunosorbent assay.

resultsSAH rats exhibited significant anxiety-like and depression-like behaviors at 12 hours, which further deteriorated at 24 hours (open arm time: 30.3 ± 4.7 seconds

conclusionThis study demonstrates that post-SAH emotional disorders result from a temporal cascade involving early neuroinflammation and progressive limbic-prefrontal circuit microstructural damage.

Indexed as

AnxietyDepressionDiffusion tensor imagingLimbic-prefrontal circuitNeuroinflammationSubarachnoid hemorrhage

Identifiers

PMID41357947
PMCPMC12679098

What Socratic 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 Socratic graph.