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Record W4412138120 · doi:10.2147/jir.s515856

Aneurysm Wall Enhancement and Systemic Inflammation Jointly Contribute to Cognitive Dysfunction in Untreated Unruptured Intracranial Aneurysm Patients

2025· article· en· W4412138120 on OpenAlexaboutno aff
Xiao‐Bing Wu, Bin Luo, Xin Guo, Chi-Chen Liu, Yi‐Ao Liu, Jie-Shun Ye, Qing-Jian Li, Shengwen Wang

Bibliographic record

VenueJournal of Inflammation Research · 2025
Typearticle
Languageen
FieldMedicine
TopicIntracranial Aneurysms: Treatment and Complications
Canadian institutionsnot available
FundersBasic and Applied Basic Research Foundation of Guangdong ProvinceNational Natural Science Foundation of China
KeywordsAneurysmMedicineSystemic inflammationInflammationCognitionCardiologyInternal medicineRadiologyPsychiatry

Abstract

fetched live from OpenAlex

Background and Purpose: Peripheral inflammatory markers and aneurysm wall enhancement (AWE) on high-resolution vessel wall MRI (HR-VWI) may reflect inflammation in unruptured intracranial aneurysms (UIAs). We assessed cognitive function and its association with inflammatory markers in UIA patients. Methods: The study included 120 consecutive patients with UIAs diagnosed between September 2018 and December 2023 and a control group of 27 healthy adults at our institution. Neuropsychological function in these patients was evaluated using the Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), Hamilton Anxiety Scale (HAMA), and Self-Rating Depression Scale (SDS). A MoCA score of <23 was classified as cognitive decline, while scores of ≥23 indicated normal cognitive function. The peripheral blood inflammatory markers and radiological characteristics were compared between the patients with cognitive decline and those with normal cognitive function. The presence of AWE and white matter hyperintensities (WMH) in UIA was identified through HR-VWI. Results: UIA patients demonstrated significantly poorer cognitive performance than controls, with lower MMSE (27.0 vs 29.0, P < 0.001) and MoCA scores (23.0 vs 25.0, P = 0.020). Patients with cognitive decline were older and exhibited elevated inflammatory markers (NLR, SII, hsCRP; all P < 0.05), along with higher rates of AWE and white matter hyperintensities (WMH) (both P < 0.001). Multivariate analysis identified AWE (OR = 5.33, 95% CI:1.82-15.59), WMH (OR = 4.26, 95% CI:1.58-11.49), and age (OR = 1.07, 95% CI:1.02-1.12) as independent predictors of cognitive decline (all P ≤ 0.01). Moreover, the cognitive decline group also showed higher SDS and HAMA scores (P < 0.05), suggesting a correlation between emotional distress and cognitive impairment. Conclusion: Untreated UIA patients exhibit cognitive decline associated with systemic inflammation (NLR, SII, hs-CRP). AWE, WMH and age are independent risk factors, suggesting vascular inflammation contributes to cognitive dysfunction.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.021
GPT teacher head0.319
Teacher spread0.299 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2025
Admission routes1
Has abstractyes

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