Palliative care in end‐stage kidney disease
Bibliographic record
Abstract
Patients with end-stage kidney disease have significantly increased morbidity and mortality. While greater attention has been focused on advanced care planning, end-of-life decisions, conservative therapy and withdrawal from dialysis these must be supported by adequate palliative care incorporating symptom control. With the increase in the elderly, with their inherent comorbidities, accepted onto dialysis, patients, their nephrologists, families and multidisciplinary teams, are often faced with end-of-life decisions and the provision of palliative care. While dialysis may offer a better quality and quantity of life compared with conservative management, this may not always be the case; hence the patient is entitled to be well-informed of all options and potential outcomes before embarking on such therapy. They should be assured of adequate symptom control and palliative care whichever option is selected. No randomized controlled trials have been conducted in this area and only a small number of observational studies provide guidance; thus predicting which patients will have poor outcomes is problematic. Those undertaking dialysis may benefit from being fully aware of their choices between active and conservative treatment should their functional status seriously deteriorate and this should be shared with caregivers. This clarifies treatment pathways and reduces the ambiguity surrounding decision making. If conservative therapy or withdrawal from dialysis is chosen, each should be supported by palliative care. The objective of this review is to summarize published studies and evidence-based guidelines, core curricula, position statements, standards and tools in palliative care in end-stage kidney disease.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".