MétaCan
Menu
Back to cohort
Record W2465451082 · doi:10.1097/spc.0000000000000224

A systematic literature review on the ethics of palliative sedation: an update (2016)

2016· review· en· W2465451082 on OpenAlexaff
Blair Henry

Bibliographic record

VenueCurrent Opinion in Supportive and Palliative Care · 2016
Typereview
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsHealth Sciences CentreUniversity of TorontoSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicinePalliative sedationPalliative careMEDLINESedationEngineering ethicsIntensive care medicineNursingPharmacologyLawPolitical science

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: Palliative sedation has been the subject of intensive debate since its first appearance in 1990. In a 2010 review of palliative sedation, the following areas were identified as lacking in consensus: inconsistent terminology, its use in nonphysical suffering, the ongoing experience of distress, and concern that the practice of palliative sedation may hasten death. This review looks at the literature over the past 6 years and provides an update on these outstanding concerns. RECENT FINDINGS: Good clinical guidelines and policies are still required to address issues of emotional distress and waylay concerns that palliative sedation hastens death. SUMMARY: The empirical evidence suggests some movement toward consensus on the practice of palliative sedation. However, a continued need exists for evidence-informed practice guidelines, education, and research to support the ethical practice of palliative sedation at the end of life. Until that time, clinicians are advised to adopt a framework or guideline that has been expert driven to ensure consistent and ethical use of palliative sedation at the end of life.

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 imitation

Not 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.

metaresearch head score (Codex)0.013
metaresearch head score (Gemma)0.067
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.013
Threshold uncertainty score0.066

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.067
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.004
Bibliometrics0.0130.012
Science and technology studies0.0010.001
Scholarly communication0.0040.004
Open science0.0020.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0060.001

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.

Opus teacher head0.337
GPT teacher head0.530
Teacher spread0.193 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
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

Citations26
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueCurrent Opinion in Supportive and Palliative CareSame topicPalliative Care and End-of-Life IssuesFrench-language works237,207