The Association Between Mild Cognitive Impairment and Self-care in Adults With Chronic Heart Failure
Bibliographic record
Abstract
BACKGROUND: Emerging evidence suggests that heart failure (HF) patients who have mild cognitive impairment (MCI) may experience greater difficulty with self-care. OBJECTIVE: This article reports a systematic review that addressed the objective "What is the evidence for an association between MCI and self-care, measured in 1 or more of the self-care domains related to HF, in adults who have a diagnosis of chronic HF?" METHOD: We adopted Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines for the review and synthesis of quantitative research studies that formally measured both cognitive function and self-care in HF patients and sought to describe the relationship between these factors. RESULTS: Ninety-one potentially relevant studies were located; 10 studies (2006-2014) were included. Because of heterogeneity in the retrieved studies, meta-analysis was not possible. Narrative synthesis found growing evidence regarding the association between MCI and adverse effects on self-care in HF. Nine studies reported significant positive associations between MCI and self-care in HF, either specifically in relation to medication adherence or more generic measures of self-care activity. One study reported a significant, negative correlation between cognitive function and self-care, suggesting that worse cognitive function was associated with better self-care; however, this is partially explained by a small sample size and mixed methodology. CONCLUSIONS: These findings have implications for clinical practice. It is known that HF patients have difficulty with self-care, and the influence of cognitive function needs to be considered when providing professional support. Further research to determine the feasibility and acceptability of cognitive assessment in routine clinical care is recommended.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.010 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 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".