Palliative and end-of-life care issues in chronic kidney disease
Bibliographic record
Abstract
PURPOSE OF REVIEW: Patients with progressive chronic kidney disease (CKD) have high morbidity, mortality, and symptom burden. Cardiovascular disease (CVD) and congestive heart failure (CHF) often contribute to these burdens and should be considered when providing recommendations for care. This review aims to summarize recent literature relevant to the provision of palliative and end-of-life care for patients with progressive CKD and specifically highlights issues relevant to those with CVD and CHF. RECENT FINDINGS: Dialysis may not benefit older, frail patients with progressive CKD, especially those with other comorbidities. Patients managed conservatively (i.e., without dialysis) may live as long as patients who elect to start dialysis, with better preservation of function and quality of life and with fewer acute care admissions. Decisions regarding dialysis initiation should be made on an individual basis, keeping in mind each patient's goals, comorbidities, and underlying functional status. Conservative management of progressive kidney disease is frequently not offered but is likely to benefit many older, frail patients with comorbidities such as CHF and CVD. SUMMARY: A palliative approach to the care of many patients with progressive CKD is essential to ensuring they receive appropriate quality care.
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 | 0.005 |
| 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 | 0.001 | 0.002 |
| 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".