Cannabinoids and the Endocannabinoid System in the Treatment of Chronic Rhinosinusitis
Bibliographic record
Abstract
OBJECTIVE: Recently, the endocannabinoid system (ECS) has emerged as a therapeutic target for various inflammatory diseases, including those of the respiratory tract. The objective of this scoping review is to explore the role of the ECS in the pathophysiology of CRS. Moreover, we sought to identify, appraise, and summarize the available evidence for cannabinoids as a potential treatment for CRS. DATA SOURCES: Six databases and four clinical trial registries were searched from inception to February 2025. REVIEW METHODS: All identified studies investigating the role of the ECS in sinonasal inflammatory disease were included for review. RESULTS: A total of 1534 studies were identified in the initial search. Following screening and full-text analysis by three authors, five studies were included in the final scoping review. Four of the studies were preclinical and in vitro in nature, examining the effects of ECS modulation through CB1 and/or CB2 receptors. The findings of each study support a common conclusion that the ECS is implicated in regulating cellular inflammatory pathways potentially involved in sinonasal disease. The final study investigated the effect of marijuana smoking on subjective and objective measures of CRS severity. There were no clinical studies identified investigating the use of cannabinoids for the treatment of sinonasal inflammatory conditions. CONCLUSION: Current literature examining the role of ECS in sinonasal inflammatory disease is highly limited, though it indicates ECS may play a role in the complex pathophysiology of sinonasal inflammatory disease. Further work is warranted to assess ECS as a potential therapeutic target for CRS.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".