Blunted Responses to Heart Failure Symptoms in Adults With Mild Cognitive Dysfunction
Bibliographic record
Abstract
INTRODUCTION: Mild cognitive dysfunction is common among adults with heart failure (HF). We hypothesized that mild cognitive dysfunction would be associated with poor HF self-care behaviors, particularly patients' ability to respond to symptoms. METHODS: We analyzed data on 148 participants in an observational study of symptoms in adults with moderate-to-advanced HF. Mild cognitive dysfunction was measured with the Montreal Cognitive Assessment (MoCA; range, 0-30), using cutoff scores for the general population (26) and for adults with cardiovascular disease (24). Heart failure self-care management (evaluation and response to HF symptoms) was measured with the Self-care of HF Index, and consulting behaviors (calling a provider when symptoms occur) were measured using the European HF Self-care Behavior Scale-9. Generalized linear modeling and hierarchical linear modeling were used to quantify the relationship between MoCA cutoff scores and indices of HF self-care. RESULTS: The mean age of the sample was 57 ± 12 years, 61.5% were men, and 58.8% had class III/IV HF; the mean left ventricular ejection fraction was 28% ± 12%. Using MoCA scores of 26 and 24, respectively, 33.1% and 14.2% of the sample had mild cognitive dysfunction. Controlling for common confounders, participants with MoCA scores lower than 26 reported self-care comparable with that of participants with MoCA scores of 26 or higher. Participants with MoCA scores lower than 24, however, reported 21.5% worse self-care management (P = 0.014) and 51% worse consulting behaviors (P < 0.001) compared with participants with MoCA scores of 24 or higher. CONCLUSIONS: A disease-specific cutoff for mild cognitive dysfunction reveals marked differences patients' ability to recognize and respond to HF symptoms when they occur. Adults with HF and mild cognitive dysfunction are a vulnerable patient group in great need of interventions that complement HF self-care.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 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".