Cannabis Use, Perspectives, and Experiences Among Patients Receiving Hemodialysis: A Descriptive Patient Survey
Bibliographic record
Abstract
Background: Patients with chronic kidney disease experience high burden of symptoms, negatively affecting their quality of life. Medication therapy is often initiated to address these symptoms but is limited by variable efficacy and high pill burden. There is interest among clinicians and patients to explore cannabis and cannabinoids as an alternative treatment to manage symptoms related to kidney disease. Objective: The objectives were to characterize cannabis use among patients receiving maintenance hemodialysis (HD), to describe patient perspectives on cannabis, and to explore patient experiences with their kidney health care team related to cannabis. Design: This was a descriptive, cross-sectional paper-based patient survey. Setting/Participants: Patients receiving maintenance HD at Toronto General Hospital in the ambulatory setting between July and August 2020 were included. Methods: A 33-item questionnaire was developed to address the study questions based on existing cannabis questionnaires and input from kidney specialist physicians, pharmacists, kidney nurse practitioners, and patients. The questionnaire was distributed to patients during their in-center HD session. Patients who chose to participate in the study completed the questionnaire and returned it to the study team. Results: In total, there were 52 respondents, of which 11 (21%) reported cannabis use in the preceding 3 months, and 23 (44%) reported historical cannabis use. Baseline characteristics were similar between those who used cannabis and those who did not, with a possible trend of cannabis users being younger. The most commonly reported reasons for using cannabis were recreation and symptom management. Those who reported using cannabis for symptom management were doing so without medical authorization or documentation. Common symptoms that cannabis was used to self-treat were insomnia, anxiety, and/or non-neuropathic pain. Dried flower was the most common type of product used, and smoking was the most common route. Care gaps and opportunities to improve patient care related to cannabis use were identified, related to monitoring and management of adverse effects, management of drug interactions, harm reduction strategies, informed decision-making, and prescriber education. Limitations: The overall participation rate was low, at approximately 17%, possibly related to the COVID-19 pandemic, lack of interest, or fear of revealing cannabis use. Non-response bias is a possible limitation as this was a voluntary survey. The questionnaire was limited to multiple-choice and Likert scale questions, therefore limiting the depth of patient responses. Conclusions: Our study showed that cannabis use among patients receiving HD is common and comparable with the general population. Patients may be using cannabis to self-manage symptoms related to kidney disease, without the involvement of the health care team. Multiple opportunities to improve patient care related to cannabis use were identified.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".