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Record W4289783259 · doi:10.1136/bmjopen-2021-054282

Long-term and serious harms of medical cannabis and cannabinoids for chronic pain: a systematic review of non-randomised studies

2022· review· en· W4289783259 on OpenAlexaff
Dena Zeraatkar, Matthew Cooper, Arnav Agarwal, Robin W.M. Vernooij, Gareth Leung, Kevin Loniewski, Jared Dookie, Muhammad Muneeb Ahmed, Brian Y. Hong, Chris J. Hong, Patrick Jiho Hong, Rachel Couban, Thomas Agoritsas, Jason W. Busse

Bibliographic record

VenueBMJ Open · 2022
Typereview
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsWestern UniversityYork UniversityUniversity of TorontoMcMaster UniversityImpact
Fundersnot available
KeywordsMedicineCannabisAdverse effectDiscontinuationChronic painMEDLINESystematic reviewCochrane LibraryPsychiatryMeta-analysisInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: To establish the prevalence of long-term and serious harms of medical cannabis for chronic pain. DESIGN: Systematic review and meta-analysis. DATA SOURCES: MEDLINE, EMBASE, PsycINFO and CENTRAL from inception to 1 April 2020. STUDY SELECTION: Non-randomised studies reporting on harms of medical cannabis or cannabinoids in adults or children living with chronic pain with ≥4 weeks of follow-up. DATA EXTRACTION AND SYNTHESIS: A parallel guideline panel provided input on the design and interpretation of the systematic review, including selection of adverse events for consideration. Two reviewers, working independently and in duplicate, screened the search results, extracted data and assessed risk of bias. We used random-effects models for all meta-analyses and the Grades of Recommendations, Assessment, Development and Evaluation approach to evaluate the certainty of evidence. RESULTS: We identified 39 eligible studies that enrolled 12 143 adult patients with chronic pain. Very low certainty evidence suggests that adverse events are common (prevalence: 26.0%; 95% CI 13.2% to 41.2%) among users of medical cannabis for chronic pain, particularly any psychiatric adverse events (prevalence: 13.5%; 95% CI 2.6% to 30.6%). Very low certainty evidence, however, indicates serious adverse events, adverse events leading to discontinuation, cognitive adverse events, accidents and injuries, and dependence and withdrawal syndrome are less common and each typically occur in fewer than 1 in 20 patients. We compared studies with <24 weeks and ≥24 weeks of cannabis use and found more adverse events reported among studies with longer follow-up (test for interaction p<0.01). Palmitoylethanolamide was usually associated with few to no adverse events. We found insufficient evidence addressing the harms of medical cannabis compared with other pain management options, such as opioids. CONCLUSIONS: There is very low certainty evidence that adverse events are common among people living with chronic pain who use medical cannabis or cannabinoids, but that few patients experience serious adverse events.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.013
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.173
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0130.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0090.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.116
GPT teacher head0.485
Teacher spread0.370 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations63
Published2022
Admission routes1
Has abstractyes

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