Cannabinoids Used for Medical Purposes in Children and Adolescents
Notice bibliographique
Résumé
Importance: Cannabinoids are increasingly used for medical purposes in children. Evidence of the safety of cannabinoids in this context is sparse, creating a need for reliable information to close this knowledge gap. Objective: To study the adverse event profile of cannabinoids used for medical purposes in children and adolescents. Data Sources: For this systematic review and meta-analysis, MEDLINE, Embase, PsycINFO, and the Cochrane Library were searched for randomized clinical trials published from database inception to March 1, 2024, for subject terms and keywords focused on cannabis and children and adolescents. Search results were restricted to human studies in French or English. Study Selection: Two reviewers independently performed the title, abstract, and full-text review, data extraction, and quality assessment. Included studies enrolled at least 1 individual 18 years or younger, had a natural or pharmaceutical cannabinoid used as an intervention to manage any medical condition, and had an active comparator or placebo. Data Extraction and Synthesis: Two reviewers performed data extraction and quality assessment independently. The Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guideline and PRISMA-S guideline were used. Data were pooled using a random-effects model. Main Outcomes and Measures: The primary outcome was the incidence of withdrawals, withdrawals due to adverse events, overall adverse events, and serious adverse events in the cannabinoid and control arms. Secondary outcomes were the incidence of specific serious adverse events and adverse events based on organ system involvement. Results: Of 39 175 citations, 23 RCTs with 3612 participants were included (635 [17.6%] female and 2071 [57.3%] male; data not available from 2 trials); 11 trials (47.8%) included children and adolescents only, and the other 12 trials (52.2%) included children, adolescents, and adults. Interventions included purified cannabidiol (11 [47.8%]), nabilone (4 [17.4%]), tetrahydrocannabinol (3 [13.0%]), cannabis herbal extract (3 [13.0%]), and dexanabinol (2 [8.7%]). The most common indications were epilepsy (9 [39.1%]) and chemotherapy-induced nausea and vomiting (7 [30.4%]). Compared with the control, cannabinoids were associated with an overall increased risk of adverse events (risk ratio [RR], 1.09; 95% CI, 1.02-1.16; I2 = 54%; 12 trials), withdrawals due to adverse events (RR, 3.07; 95% CI, 1.73-5.43; I2 = 0%; 14 trials), and serious adverse events (RR, 1.81; 95% CI, 1.21-2.71; I2 = 59%; 11 trials). Cannabinoid-associated adverse events with higher RRs were diarrhea (RR, 1.82; 95% CI, 1.30-2.54; I2 = 35%; 10 trials), increased serum levels of aspartate aminotransferase (RR, 5.69; 95% CI, 1.74-18.64; I2 = 0%; 5 trials) and alanine aminotransferase (RR, 5.67; 95% CI, 2.23-14.39; I2 = 0%; 6 trials), and somnolence (RR, 2.28; 95% CI, 1.83-2.85; I2 = 8%; 14 trials). Conclusions and Relevance: In this systematic review and meta-analysis, cannabinoids used for medical purposes in children and adolescents in RCTs were associated with an increased risk of adverse events. The findings suggest that long-term safety studies, including those exploring cannabinoid-related drug interactions and tools that improve adverse event reporting, are needed.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,011 | 0,054 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,004 | 0,005 |
| Bibliométrie | 0,006 | 0,008 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».