Abstract 18993: High Prevalence of Cognitive Impairment in Older Heart Failure Patients at Hospital Discharge
Bibliographic record
Abstract
Background: Evidence suggests that HF patients do not consistently engage in self-care. One possible reason may be the presence of undetected mild cognitive deficits (MCD). The primary objective of this study was to prospectively evaluate whether MCD measured with the Montreal Cognitive Assessment (MoCA) test in HF patients aged ≥60 years at hospital discharge is associated with impaired ability to self-care (measured with the Self-Care Heart Failure Index (SCHFI), patient is considered adequate if score ≥70/100). Methods / Results: We prospectively recruited HF patients within 48 hours from hospital discharge. In addition to the assessment of cognitive function, we measured baseline intelligence (NAART35), depression (Geriatric Depression Scale, GDS15 ), caregiver burden (modified Oberst Caregiver Burden Scale), activities of daily living (Barthel index), and frailty (Clinical Frailty Scale, CFS). We have recruited 51 patients (mean age 78, SD 7 years, 51% male) in this study. Sixty eight percent of patients have a high school education or less, 45% are married, 42% widowed, and 64% of patients have a total household income of <$40,000. Fifty three percent of patients have a left ventricular ejection fraction >45%. The mean number of medications at hospital discharge is 10 (SD 4). The mean MoCA score at baseline was 22 (SD 4) and 87% of patients had a MoCA score <26 (indicating cognitive impairment). The SCHFI at baseline was 64 for self-maintenance, 46 for self-management, and 63 for self-confidence. Caregiver burden was low for the 2 subscales (Demand: 1.9, Difficulty: 1.3). The mean score for the GDS15 was 4/15 (no depression: 0-4/15), Barthel index was 82/100 indicating that the patients are not fully independent for ADLs. The mean CFS score was 4/7 indicating that these individuals are limited by symptoms during their activities. Conclusion: To our knowledge, this is the first prospective study at hospital discharge indicating a high prevalence of cognitive impairment. These results suggest that older HF patients have significant undetected cognitive deficits which may impact on their ability to self-care, which may in turn potentially lead to re-hospitalization early after hospital 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".