Benefit of Tetrahydrocannabinol versus Cannabidiol for Common Palliative Care Symptoms
Bibliographic record
Abstract
Abstract Objectives: To determine the relative contributions of tetrahydrocannabinol (THC) and cannabidiol (CBD) to patients' self-ratings of efficacy for common palliative care symptoms. Design: This is an electronic record-based retrospective cohort study. Model development used logistic regression with bootstrapped confidence intervals (CIs), with standard errors clustered to account for multiple observations by each patient. Setting: This is a national Canadian patient portal. Participants: A total of 2,431 patients participated. Main Outcome Measures: Self-ratings of efficacy of cannabis, defined as a three-point reduction in neuropathic pain, anorexia, anxiety symptoms, depressive symptoms, insomnia, and post-traumatic flashbacks. Results: We included 26,150 observations between October 1, 2017 and November 28, 2018. Of the six symptoms, response was associated with increased THC:CBD ratio for neuropathic pain (odds ratio [OR]: 3.58; 95% CI: 1.32–9.68; p = 0.012), insomnia (OR: 2.93; 95% CI: 1.75–4.91; p < 0.001), and depressive symptoms (OR: 1.63; 95% CI: 1.07–2.49; p = 0.022). Increased THC:CBD ratio was not associated with a greater response of post-traumatic stress disorder (PTSD)-related flashbacks (OR: 1.43; 95% CI: 0.60–3.41; p = 0.415) or anorexia (OR: 1.61; 95% CI: 0.70–3.73; p = 0.265). The response for anxiety symptoms was not significant (OR: 1.13; 95% CI: 0.77–1.64; p = 0.53), but showed an inverted U-shaped curve, with maximal benefit at a 1:1 ratio (50% THC). Conclusions: These preliminary results offer a unique view of real-world medical cannabis use and identify several areas for future research.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".