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Record W2037952949 · doi:10.1097/spc.0000000000000110

Palliative and end-of-life care issues in chronic kidney disease

2015· review· en· W2037952949 on OpenAlexaff
Sara Combs, Sara N. Davison

Bibliographic record

VenueCurrent Opinion in Supportive and Palliative Care · 2015
Typereview
Languageen
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsUniversity of Alberta
FundersNational Institute of Diabetes and Digestive and Kidney Diseases
KeywordsMedicinePalliative careIntensive care medicineKidney diseaseDialysisQuality of life (healthcare)DiseaseHeart failureAdvance care planningEnd-of-life careComorbidityInternal medicineNursing

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.891
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.142
GPT teacher head0.449
Teacher spread0.308 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations58
Published2015
Admission routes1
Has abstractyes

Explore more

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