Distinct Factors Associated With Better Self-care in Heart Failure Patients With and Without Mild Cognitive Impairment
Bibliographic record
Abstract
BACKGROUND: A decline in cognition may limit patients' ability to effectively engage in self-care in those with heart failure (HF). However, several studies have shown no difference in self-care between HF patients with and without cognitive impairment. This may indicate that there are more salient factors associated with self-care in HF patients with cognitive impairment compared with those without cognitive impairment. OBJECTIVE: The aim of this study was to explore which factors are related to self-care based on the presence and absence of mild cognitive impairment (MCI) among patients with HF. METHODS: Patients with HF were recruited from outpatient settings. The Montreal Cognitive Assessment was used to screen for MCI. Self-care was measured with the Self-care of HF Index v.6.2. Two separate stepwise linear regressions were performed to identify which factors (HF knowledge, perceived control, functional status, multimorbidity, executive function, and social support) predicted self-care in HF patients with and without MCI. RESULTS: Of the 132 patients in this study, 36 (27.3%) had MCI. Self-care maintenance and management were associated with social support (β = 0.489) and executive function (β = 0.484), respectively, in patients with MCI. Perceived control was associated with both self-care maintenance and management in patients without MCI (βs = 0.404 and 0.262, respectively). CONCLUSION: We found that social support and executive function were associated with self-care in HF patients with MCI, whereas perceived control was associated with self-care in HF patients with intact cognition. Clinicians should develop tailored interventions to enhance self-care by considering the distinct factors associated with self-care based on the presence or absence of MCI.
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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 | 0.004 |
| 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 | 0.001 | 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".