The Relationship of Quality of Life, Depression, and Caregiver Burden in Outpatients With Congestive Heart Failure
Bibliographic record
Abstract
Primary caregivers of patients with congestive heart failure withstand enormous burden, often sacrificing their own quality of life. The relationship between caregiver burden and depression and patient quality of life and depression in this setting is unknown. Fifty outpatients were prospectively administered the Minnesota Living with Heart Failure Questionnaire and Beck Depression Inventory II (BDI-II). Caregivers were administered the Zarit Caregiver Burden Interview and BDI-II. The mean quality of life score was 35, and 26% had a BDI-II score >10. The mean Zarit Caregiver Burden Interview score was 16. Minnesota Living with Heart Failure Questionnaire, BDI-II, and Zarit Caregiver Burden Interview scores were all associated with lower ejection fraction, need for hospitalization, increased number of medications, and comorbidities. Patient Minnesota Living with Heart Failure Questionnaire score correlated with patient BDI-II, caregiver BDI-II, and Zarit Caregiver Burden Interview scores. Caregiver burden score correlated with both caregiver BDI-II and patient BDI-II. Death or hospitalization at 6 months was associated with caregiver burden and depressive symptoms and with patient quality of life and depressive symptoms. Caregivers of patients with congestive heart failure experience high caregiver burden and prevalence of depressive symptoms, which are related to the patient disease burden.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".