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Record W2912652643 · doi:10.1093/ecco-jcc/jjy222.572

P448 Cannabis and cannabinoids for the treatment of inflammatory bowel disease: a systematic review and meta-analysis

2019· review· en· W2912652643 on OpenAlexaboutno aff
Benthe H. Doeve, F van Schaik, Maartje van de Meeberg, H Fidder

Bibliographic record

VenueJournal of Crohn s and Colitis · 2019
Typereview
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineMeta-analysisInternal medicineRelative riskRandomized controlled trialConfidence intervalCochrane LibraryPublication biasStudy heterogeneityMEDLINECannabisStrictly standardized mean differenceInflammatory bowel diseaseSystematic reviewDiseasePsychiatry

Abstract

fetched live from OpenAlex

Inflammatory bowel disease (IBD) patients increasingly use complementary and alternative medicine such as cannabis and/or cannabinoids. Cannabinoids may have anti-inflammatory properties through interaction with the endocannabinoid system. We performed a systematic review with meta-analysis to assess the efficacy of cannabi(noid)s in treating IBD. We included randomised controlled trials (RCTs) and non-randomised studies (NRSs) analysing IBD patients of any age using cannabi(noid)s. Two reviewers searched MEDLINE, Embase and CENTRAL until 19 July 2018. A data extraction sheet included study characteristics, patient characteristics, intervention details, and disease activity scores. We assessed risk of bias with the Cochrane Risk of Bias tool and the Newcastle-Ottawa Quality Assessment Scale. Revman 5.3 computed relative risks (RR), mean differences (MD), and standardised mean differences (SMD) with a 95% confidence interval (95% CI) using the random-effects model. For the meta-analyses, only RCTs were included. The search identified 571 records of which 9 NRSs and 4 RCTs were eligible for inclusion. The meta-analysis included 100 randomised participants. Risk of bias was moderate to high. Cannabi(noid)s were not effective in inducing remission (RR = 1.29, 95% CI = 0.68–2.47; see figure). Statistical heterogeneity was low (I2 = 0%, p = 0.40). However, average disease activity score in the intervention group (SMD = 1.47, 95% CI = 1.00–1.94) was significantly different from the average disease activity score in the control group (SMD = 0.71, 95% CI = 0.31–1.15; p = 0.02, I2 = 81%). Effect on CRP and calprotectin was not significant (MD=0.50, 95% CI = −1.87–2.86; MD=−31, 95% CI = −162–101). Abdominal pain, general well-being, nausea, diarrhoea and poor appetite all improved with cannabi(noid)s on Likert-scales. Baseline quality of life was lower in patients using cannabis amongst cohort studies (MD = −0.64; 95% CI = −0.92 to −0.36) but improved significantly with cannabi(noid)s in a prospective NRS and two RCTs. Cannabi(noid)s seem ineffective in inducing remission in patients with IBD. However, IBD patients may benefit from cannabi(noid)s by improvement of symptoms and quality of life. Although statistical heterogeneity was low, studies were heterogeneous regarding patients and intervention and mostly included small numbers of patients. Larger uniform studies are needed. Additionally, the most effective formulation and dose as well as safety of cannabi(noid)s have to be further elucidated.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.027
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.020
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.027
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0200.041
Bibliometrics0.0100.011
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0030.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0080.001

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.

Opus teacher head0.055
GPT teacher head0.362
Teacher spread0.307 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
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

Citations3
Published2019
Admission routes1
Has abstractyes

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