Marijuana use in transplantation: A call for clarity
Bibliographic record
Abstract
Transplant centers have varying policies for marijuana (MJ) use in donors, transplant candidates, and recipients. Rationales for these differences range from concerns for fungal complications, impaired adherence, and drug interactions. This paper reviews the current status of MJ policies and practices in transplant centers and results of a survey sent to the American Society of Transplantation (AST) membership by the Executive Committee of the AST Infectious Diseases Community of Practice.The purpose of the survey was to compare policies and concerns of MJ use to actual observed complications. Of the 3321 surveys sent, 225 members (8%) responded. Transplant centers varied in their approval processes, differing even in organ types within the same institutions. Furthermore, there was discordance among transplant centers in their perceived risks of marijuana use as opposed to complications actually observed. An increasing number of states continue to legalize medical and recreational MJ resulting in widespread availability. Further research is needed to assess the validity of concerns for complications of MJ use in potential donors and recipients. Ultimately, standardized guidelines should be established based on studies and evidence-based criteria to assist transplant programs in their policies around the use of cannabis in their donors and recipients.
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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 | 0.022 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.007 |
| Scholarly communication | 0.006 | 0.020 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.009 | 0.016 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".