Measuring quality of life in advanced heart failure
Bibliographic record
Abstract
PURPOSE OF REVIEW: Patients with Stage D heart failure can benefit from palliative care consultation to help them manage unpleasant symptoms and improve quality of life. Although guidelines describe how to manage symptoms, very little direction is provided on how to evaluate the effectiveness of those interventions. RECENT FINDINGS: Numerous studies have used the measurement of symptoms, emotional distress, functional capacity and quality of life to evaluate the effectiveness of interventions in heart failure. There is limited evidence on the use of these instruments in heart failure palliative care. Four studies were identified that evaluate the effectiveness of palliative care consultation for patients with advanced heart failure. All four studies measured symptom severity, emotional distress, and quality of life. The application of appropriate instruments is discussed. Suggestions for scores that should trigger palliative care consultation are identified. SUMMARY: The routine administration of standardized instruments to measure symptom severity and quality of life may improve the assessment and management of patients with Stage D heart failure. Ongoing discussion and research is needed to determine if these instruments are the best tools to use with heart failure palliative care patients.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".