Does Cognitive Impairment Predict Poor Self-Care in Patients with Heart Failure?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
AIMS: Cognitive impairment occurs often in patients with chronic heart failure (CHF) and may contribute to sub-optimal self-care. This study aimed to test the impact of cognitive impairment on self-care. METHODS AND RESULTS: In 93 consecutive patients hospitalized with CHF, self-care (Self-Care of Heart Failure Index) was assessed. Multiple regression analysis was used to test a model of variables hypothesized to predict self-care maintenance, management, and confidence. Variables in the model were mild cognitive impairment (MCI; Mini-Mental State Exam and Montreal Cognitive Assessment), depressive symptoms (Cardiac Depression Scale), age, gender, social isolation, education level, new diagnosis, and co-morbid illnesses. Sixty-eight patients (75%) were coded as having MCI and had significantly lower self-care management (eta(2)= 0.07, P < 0.01) and self-confidence scores (eta(2)= 0.05, P < 0.05). In multivariate analysis, MCI, co-morbidity index, and NYHA class III or IV explained 20% of the variance in self-care management (P < 0.01); MCI made the largest contribution explaining 9% of the variance. Increasing age and symptoms of depression explained 13% of the variance in self-care confidence scores (P < 0.01). CONCLUSION: Cognitive impairment, a hidden co-morbidity, may impede patients' ability to make appropriate self-care decisions. Screening for MCI may alert health professionals to those at greater risk of failed self-care.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it