Cannabis in palliative care: current challenges and practical recommendations
Bibliographic record
Abstract
Pain and symptom control challenges are common in palliative care, and the search for other therapeutic strategies is ongoing. Unfortunately, patients and their caregivers are receiving little information or support from healthcare providers regarding the increasingly popular cannabinoid-based medicines (CBM). Clinicians, meanwhile, feel understandably perplexed by the discrepancy between the available evidence and the rapid interest in which patients and their families have demonstrated for CBM. There is an urgent need to address the many challenges that are delaying the appropriate integration of CBM into clinical practice, notwithstanding the obvious need for a solid general knowledge of pharmacology, mechanism of action and available clinical evidence supporting its use. The authors will address these challenges and provide practical recommendations regarding patient assessment for the use of CBM. The authors will also make suggestions regarding patient expectations in order to define clear objectives, review the necessary precautions prior to initiating treatment, aid in selecting the appropriate strain and route of administration as well as establishing proper titration and monitoring protocols. The authors will also discuss the lesser known but potentially therapeutic psychoactive effects of cannabis. As this class of therapeutic agents are likely to play a major role in palliative medicine in the near future, clinicians would benefit from familiarizing themselves with CBM and we can expect that patients and their caregivers will appreciate receiving support in their search for safe and effective therapeutic alternatives.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".