Cognitive impairment in malnourished heart failure patients
Bibliographic record
Abstract
Abstract Background Malnutrition is common in heart failure (HF) and is associated with poor outcomes, including increased mortality and hospitalizations. However, its impact on cognitive function in patients with HF is less well understood. The Geriatric Nutritional Risk Index (GNRI) is a validated marker of nutritional status that has been associated with adverse clinical outcomes in various populations. Purpose The objective of this study was to examine whether low GNRI (high nutrition-related risk) is associated with worse cognitive performance in patients hospitalized for HF. Methods We analyzed data from 384 patients hospitalized for HF between March 2014 and February 2025. Cognitive function was assessed using the Montreal Cognitive Assessment (MoCA), the Symbol Digit Modalities Test (SDMT), and Trail Making Test A (TMT-A). GNRI was categorized into high risk of malnutrition-related morbidity corresponding to GNRI <82, and all others (GNRI ≥ 82). Multivariable linear regression models were used to evaluate the association between GNRI and cognitive test performance, adjusting for age, sex, systolic blood pressure, education level (≥12 years vs. <12 years), and history of stroke. Results A total of 384 patients (mean age 73.8 (±12.6) years, 68.2% men) had complete cognitive assessments and covariate data. Patients with high nutritional risk (GNRI <82) performed significantly worse on MoCA (beta -1.57, 95% CI -3.10 to -0.04, p=0.045) and SDMT (beta -4.07, 95% CI -8.00 to -0.15, p=0.045) compared to those without high nutritional risk (Table 1). These associations remained significant after adjusting for covariates. In contrast, GNRI was not significantly associated with performance on TMT-A (mean difference -0.03, 95% CI -0.25 to 0.20, p=0.80). Conclusions Our findings indicate that malnutrition, as assessed by GNRI, is associated with lower cognitive performance in HF patients, particularly in global cognition (MoCA) and processing speed (SDMT). These results suggest that nutritional status should be considered when evaluating cognitive impairment in HF. However, GNRI was not associated with performance on TMT-A, suggesting that executive function and psychomotor speed may be less affected in this population. Alternatively, TMT-A may not be an optimal instrument for assessing cognitive impairment in hospitalized HF patients due to factors such as frailty, motor impairments, or fluctuating attention. Future research is needed to explore the underlying mechanisms linking malnutrition and cognitive decline in HF patients, as well as the suitability of different cognitive tests in this clinical context.Table 1.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".