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Record W4415623230 · doi:10.3389/fneur.2025.1644634

Cerebrovascular compromise and cognitive decline driven by chronic heart failure

2025· article· en· W4415623230 on OpenAlexaboutno aff
Fuliang Du, Xiaoxia Hou, Guanhui Wu, Xiaoyu Cheng, Qingzhang Cheng, Hongxuan Feng, Hao‐Jie Zhu, Meixia Wang

Bibliographic record

VenueFrontiers in Neurology · 2025
Typearticle
Languageen
FieldMedicine
TopicHeart Failure Treatment and Management
Canadian institutionsnot available
FundersNanjing Medical UniversityNational Natural Science Foundation of China
KeywordsHeart failureCognitive declineEjection fractionCognitionCognitive impairmentChronic disease

Abstract

fetched live from OpenAlex

Objective: This study investigated the effects of chronic heart failure with decreased LVEF on small cerebral vascular disease (CSVD) and associated cognitive impairment. Methods: This study encompassed a cohort of 73 patients diagnosed with chronic heart failure (CHF) at the Cardiovascular Department of Suzhou Municipal Hospital, spanning the period from June 2018 to August 2022. Participants were stratified into two groups based on a left ventricular ejection fraction (LVEF) threshold of 50%: 40 patients were categorized into the LVEF≥50% group, representing 54.8% of the cohort, while 33 patients were assigned to the LVEF<50% group, constituting 45.2% of the cohort. Each subject underwent a series of assessments, including brain magnetic resonance imaging (MRI), cardiac ultrasound, and neurocognitive function tests. For the analysis of diffusion tensor imaging (DTI), the tract-based spatial statistics (TBSS) method was employed to evaluate the DTI parameters of the participants' brain white matter. Due to the extended duration of the DTI examination and the stringent requirements for patient compliance, only 37 patients, accounting for 50.7% of the total cohort, completed the DTI scans. This subset included 20 patients from the LVEF≥50% group and 17 patients from the LVEF<50% group. Results: = 0.042) was found to be associated with LVEF in CHF patients, independent of the severity of WMH. Furthermore, LVEF in CHF patients demonstrated a positive correlation with total MoCA scores, as well as with visuospatial/executive functions, attention, and delayed recall. Tract-based spatial statistics (TBSS) analysis revealed that, in comparison to CHF patients with LVEF ≥ 50%, those with LVEF < 50% exhibited a significant decrease in fractional anisotropy (FA) and significant increases in mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD). In CHF patients, FA was positively correlated with visuospatial/executive functions, attention, and delayed recall, whereas MD, AD, and RD were negatively correlated with these cognitive domains. Conclusion: Chronic heart failure is significantly associated with the presence of CSVD (especially WMH) and the severity of cognitive impairment, with decreased LVEF correlating with worse outcomes.

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)0.002
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 score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
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 head0.005
GPT teacher head0.240
Teacher spread0.236 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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