Medicinal and Recreational Marijuana: Review of the Literature and Recommendations for the Plastic Surgeon
Bibliographic record
Abstract
With the shift in public opinion and legalization of cannabis for therapeutic and recreational use, cannabis consumption has become more common. This trend will likely continue as decriminalization and legalization of marijuana and associated cannabinoids expand. Despite this increase in use, our familiarity with this drug and its associated effects remains incomplete. The aim of this review is to describe the physiologic effects of marijuana and its related compounds, review current literature related to therapeutic applications and consequences, discuss potential side effects of marijuana in surgical patients, and provide recommendations for the practicing plastic surgeon. Special attention is given to areas that directly impact plastic surgery patients, including postoperative pain, nausea and vomiting and wound healing. Although the literature demonstrates substantial support for marijuana in areas such as chronic pain and nausea and vomiting associated with chemotherapy, the data supporting its use for common perioperative problems are lacking. Its use for treating perioperative problems, such as pain and nausea, is poorly supported and requires further research.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".