Abstract 4361637: Cognitive Impairment Impedes the Acquisition of Self-Care Management Skills in Patients with Heart Failure
Bibliographic record
Abstract
Background: Cognitive impairment (CI) is prevalent among patients with heart failure (HF) and is associated with adverse outcomes. Effective self-care management is crucial in preventing HF deterioration. However, the impact of CI on acquiring self-care management skills remains unclear. Hypothesis: CI impedes the acquisition of self-care management skills using the HF point system in patients with HF. Methods: We analyzed data from a prospective, multicenter HF registry that included 26 centers in Japan. Patients hospitalized for HF between July 2022 and June 2023 who underwent cognitive function testing were extracted. We introduced a new HF point self-care management system that assigns points to key HF symptoms (1 point for edema, dyspnea on exertion, heart rate >120 bpm; 3 points each for dyspnea at rest, and weight gain >5% above target). This system guides early ambulatory visits based on the total score of HF points. Patients were provided instruction on its use during hospitalization. Implementation of the system was assessed at discharge. CI was defined by Montreal Cognitive Assessment score <26. Logistic regression was used to evaluate the association between CI and implementation of the self-care management system. Cox proportional hazard model, adjusted for demographics, comorbidities, and medications, was used to assess the impact of the HF point system implementation on clinical outcomes. Results: Of the 618 patients (mean age 81±10.6 years, 49% male), 515 (83%) patients had CI. A total of 277 (45%) patients were able to implement our HF point self-care management system. Univariate analysis identified age, sex, anemia, dyslipidemia, GNRI, SPPB, and CI as factors associated with patients' implementation of the HF point self-care management system. Multivariate analysis showed that CI was an independent predictor of unsuccessful system implementation (odds ratio 0.395; 95% CI, 0.223-0.702; P=0.002). After a median follow-up of 14.4 months, patients who implemented the HF point self-care management system had significantly lower incidence of the composite outcome of all cause death and HF rehospitalization (adjusted HR 0.671; 95% CI, 0.46-0.97; P=0.03). Conclusions: The incidence of CI in HF patients is very high, and they are at high risk for poor self-care management. HF patients with CI may require tailored, intensive support to prevent HF deterioration after discharge.
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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 | 0.002 | 0.006 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".