Cerebrovascular compromise and cognitive decline driven by chronic heart failure
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".