Therapeutic Cannabis Use in Kidney Disease: A Survey of Canadian Nephrologists
Bibliographic record
Abstract
Rationale & Objective: Cannabis use may be helpful for symptom management in patients with chronic kidney disease (CKD). Knowledge, attitudes, and comfort with use of medical cannabis among kidney care providers may be limiting more widespread evaluation and use. We surveyed Canadian nephrologists regarding current prescribing habits, attitudes, and overall comfort level with cannabis products. Study Design: We carried out a nationwide, mail-in survey focused on capturing general and practice demographics, current cannabis prescribing status, and knowledge and attitudes regarding therapeutic cannabis use in patients with CKD. Setting & Population: This survey was distributed to every registered nephrologist in Canada. Analytical Approach: The results of this survey are reported descriptively. Results: Responses were received from 208 of 723 (29%) nephrologists. Only 21 (10.1%) respondents currently prescribe cannabis, with chronic pain syndromes being the most frequent reason for cannabis prescription (95.2%). Overall, 116 (55.5%) participants reported that changes in legality of cannabis did not influence their decision to prescribe cannabis. The majority of respondents (n = 123; 59%) indicated that they were uncomfortable with their knowledge of the medical cannabis literature. Most respondents (n=188; 91%) indicated that further studies exploring the efficacy and safety of cannabis would likely influence their prescribing habits. Limitations: Limitations of this study include possible nonresponse bias and a lack of specific data on practice considerations for specific subpopulations, such as transplant patients. Conclusions: Only a small minority of Canadian nephrologists currently prescribe cannabis, with relatively little practice change after legalization. There is broad support amongst Canadian nephrologists for encouraging their patients to enroll in efficacy/safety studies of cannabis in the CKD population. Ultimately, given limited therapeutic options available for symptom control in CKD, this survey demonstrates the potential for nationwide practice change if cannabis efficacy and safety can be demonstrated in this population.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".