Palliative care in heart failure: addressing the largest care gap
Bibliographic record
Abstract
PURPOSE OF REVIEW: Heart failure is a chronic, fatally progressive and incurable condition characterized by periods of apparent stability interspersed with acute exacerbations. Treatment models have historically emphasized management of acute exacerbations of cardiovascular disease, during which end-of-life issues figure frequently and prominently, though in a setting that is inappropriate to address the comprehensive needs of patients and their families. Consequently, in comparison to patients with malignancy, heart failure patients at the end of life are less likely to access palliative resources, and more likely to access in-patient care and cardiovascular procedures. RECENT FINDINGS: Recent reports and position statements have emphasized the following critical needs for provision of optimal heart failure care: a) Cardiovascular specialists require training to obtain basic skills for provision of palliative care to management of end-of-life issues; b) Discussion of end-of-life issues should be introduced as early as feasible in patients with heart failure and should be updated with changes in clinical status; c) Provision of palliative care should be integrated into a team approach; d) Patients with heart failure frequently suffer symptoms which are not typically considered 'cardiovascular', such as pain, social/functional and psychological. Patients should be assessed for these symptoms, which should be treated. SUMMARY: This report summarizes many of these suggestions and outlines future directions for the expansion and improvement of this critical need for heart failure 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 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".