Cerebral Hypometabolism Mediates the Effect of Stroke Volume on Cognitive Impairment in Heart Failure Patients
Bibliographic record
Abstract
AIMS: The present study aimed to phenotype the cerebral structural and glucose metabolic alterations in patients with heart failure (HF) using simultaneous positron emission tomography (PET)/magnetic resonance (MR) and to investigate their relationship to cardiac biomarkers and cognitive performance. METHODS AND RESULTS: F) fluorodeoxyglucose PET/MR followed by cardiac MR scan, and neuropsychological scores were obtained to assess cognitive performance. The grey matter volume (GMV) and standardized uptake value ratio (SUVR) were calculated to examine cerebral structural and metabolic alterations. Cardiac biomarkers included cardiac MR parameters and cardiac serum laboratory tests. Mediation analysis was performed to explore the associations among cerebral alterations, cardiac biomarkers, and cognitive performance. HF patients demonstrated notable cognitive impairment compared with normal controls (P < 0.001). Furthermore, HF patients exhibited regional brain hypometabolism in the bilateral calcarine cortex, caudate nucleus, thalamus, hippocampus, precuneus, posterior cingulate cortex, lingual and olfactory cortex, and GMV reduction in bilateral thalamus and hippocampus (cluster level at P < 0.05, Gaussian random field correction). The SUVR of the hypometabolic brain regions was correlated with the Montreal Cognitive Assessment (MoCA) scores (r = 0.55, P = 0.038) and cardiac stroke volume (r = 0.49, P = 0.002). Cerebral hypometabolism played a key role in the relationship between the decreased stroke volume and MoCA scores, with a mediation effect of 33.2%. CONCLUSIONS: HF patients suffered cerebral metabolic and structural alterations in regions associated with cognition. The observed correlation between cardiac stroke volume and cognitive impairment underscored the potential influence of cerebral hypometabolism, suggesting that cerebral hypometabolism due to chronic systemic hypoperfusion may significantly contribute to cognitive impairment in HF patients.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".