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Record W7115919836 · doi:10.2147/ndt.s557670

Residual Inflammatory Risk Is Associated with Cognitive Impairment After Acute Ischemic Stroke

2025· article· en· W7115919836 on OpenAlexaboutno aff

Bibliographic record

VenueNeuropsychiatric Disease and Treatment · 2025
Typearticle
Languageen
FieldNeuroscience
TopicNeuroinflammation and Neurodegeneration Mechanisms
Canadian institutionsnot available
FundersAnhui University of Science and TechnologyAnhui University
KeywordsCognitive impairmentIschemic strokeStroke (engine)ResidualCognitionAcute stroke

Abstract

fetched live from OpenAlex

Objective: Acute ischemic stroke (AIS) may lead to varying degrees of cognitive impairment, while the inflammatory response plays a significant role in this process. This study aims to examine the relationship between residual inflammation risk (RIR) and the development of post-stroke cognitive impairment (PSCI) in patients with acute ischemic stroke. Methods: This prospective cohort study enrolled a total of 172 patients diagnosed with AIS over the study period from January 2024 to December 2024. They were divided into four groups: RIR only [low-density lipoprotein cholesterol (LDL-C) < 2.6 mmol/L and high-sensitivity CRP (hsCRP) ≥ 2 mg/L], residual cholesterol risk (RCR) only (LDL-C ≥ 2.6 mmol/L and hsCRP < 2 mg/L), both risk or residual cholesterol and inflammatory risk (RCIR) (LDL-C ≥ 2.6 mmol/L and hsCRP ≥ 2 mg/L), and neither risk (LDL-C < 2.6mmol/L and hsCRP < 2 mg/L). PSCI is defined as a Montreal Cognitive Assessment (MoCA) score below 22 at 6 months after stroke. The final analysis included 172 patients who completed the follow-up. The association between RIR and PSCI was analyzed by multivariable logistic regression analyses. Results: Among the 172 enrolled patients, 58 (33.7%) developed PSCI. The proportion of patients with neither risk, RIR, RCR, and RCIR was 23.8% (n=41),18.6% (n=32), 32.0% (n=55) and 25.6% (n=44), respectively. Compared to those without PSCI, patients with PSCI had a higher prevalence of hyperlipidemia ( P = 0.026), a greater proportion of RIR ( P = 0.015), and higher white blood cell count ( P = 0.042) and neutrophil count ( P = 0.016). Logistic regression analysis, adjusting for major confounding factors, identified RIR as an independent factor associated with PSCI occurrence (OR 4.496, 95% CI 1.571– 17.477, P = 0.030; RCIR: OR 7.357, 95% CI 2.081– 26.006, P = 0.002). Conclusion: This study presents what is, to our knowledge, the first evidence that RIR is associated with PSCI among acute ischemic stroke patients. Keywords: residual inflammatory risk, post-stroke cognitive impairment, acute ischemic stroke

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)0.001
metaresearch head score (Gemma)0.003
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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.008
GPT teacher head0.233
Teacher spread0.225 · 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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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