Development of a Clinical Practice Guideline for Palliative Sedation
Bibliographic record
Abstract
Palliative sedation is an effective symptom control strategy for patients who suffer from intractable symptoms at the end of life. Evidence suggests that the use of this practice varies considerably. In order to minimize variation in the practice of palliative sedation within our health region, we developed a clinical practice guideline (CPG) for the use of palliative sedation. Using available evidence from the literature, a five step process was employed to develop the CPG: (1) a working group was charged with the mandate to develop a draft guideline; (2) a working definition for palliative sedation was developed; (3) criteria for use of sedation were determined; (4) critical steps to be taken prior to initiation of sedation were defined; and (5) the CPG was reviewed by local stakeholders. Feedback from the wider group of stakeholders was used to arrive at the final CPG, which subsequently received approval from the local Medical Advisory Board. The process used to develop the CPG served to develop consensus within the local community of palliative care clinicians regarding the practice of palliative sedation. Subsequently, the CPG was used as a tool for educating other health care providers.
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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 | 0.052 | 0.093 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.009 | 0.005 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.008 | 0.004 |
| Research integrity | 0.011 | 0.015 |
| Insufficient payload (model declined to judge) | 0.004 | 0.005 |
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".