Developing Guidelines on the Assessment and Treatment of Delirium in Older Adults at the End-of-Life
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Delirium at the end of life is common and can have serious consequences on an older person's quality of life and death. In spite of the importance of detecting, diagnosing, and managing delirium at the end of life, comprehensive clinical practice guidelines (CPG) are lacking. Our objective was to develop CPG for the assessment and treatment of delirium that would be applicable to seniors receiving end-of-life care in diverse settings. METHODS: Using as a starting point the 2006 Canadian Coalition for Seniors' Mental Health CPG on the assessment and treatment of delirium, a team of palliative care researchers and clinicians partnered with members of the original guideline development group to adapt the guidelines for an end-of-life care context. This process was supported by an extensive literature review. The final guidelines were reviewed by external experts. RESULTS: Comprehensive CPG on the assessment and treatment of delirium in older adults at the end of life were developed and can be downloaded from http://www.ccsmh.ca. CONCLUSIONS: Further research is needed on the implementation and evaluation of these adapted delirium guidelines for older patients receiving end-of-life care in various palliative care settings.
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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 | 0.036 | 0.129 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.007 | 0.003 |
| Research integrity | 0.008 | 0.007 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".