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Enregistrement W2806774532 · doi:10.1097/xeb.0000000000000145

Medicinal cannabis

2018· editorial· en· W2806774532 sur OpenAlexaboutno aff
Hanan Khalil

Notice bibliographique

RevueInternational Journal of Evidence-Based Healthcare · 2018
Typeeditorial
Langueen
DomaineMedicine
ThématiqueCannabis and Cannabinoid Research
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésCannabidiolCannabisSynthetic cannabinoidsTetrahydrocannabinolDronabinolEndocannabinoid systemCannabinoidPharmacologyCannabinolMedicineCannabinoid receptorEffects of cannabisTraditional medicineReceptorPsychiatryInternal medicine

Résumé

récupéré en direct d'OpenAlex

Cannabis is the most popular recreational drug used in the world. It is estimated that 178 million people aged 15–64 years used cannabis at least once in 2012.1 Cannabis or cannabinoids used to manage medical conditions is referred to as medicinal cannabis. There are various formulations of cannabis available on the market. Cannabis can be administered orally, sublingually, or topically; it can be smoked, inhaled, mixed with food, or made into tea. It can be taken in herbal form, extracted naturally from the plant, gained by isomerization of cannabidiol (CBD), or manufactured synthetically. The commercially available prescribed cannabinoids include dronabinol capsules, nabilone capsules, and the oromucosal spray nabiximols.2 Canada and the Netherlands have government-run programs in which dedicated companies supply quality-controlled herbal cannabis. In the United States, 23 states and Washington, DC (May 2015) have introduced laws permitting the medical use of cannabis; other countries have similar laws.3 The recently discovered endocannabinoid system has significantly increased our understanding of the actions of exogenous cannabis. Endocannabinoids appear to control pain, muscle tone, mood state, appetite, and inflammation, among other effects. Cannabis contains more than 100 different cannabinoids and has the capacity for analgesia through neuromodulation in ascending and descending pain pathways, neuroprotection, and anti-inflammatory mechanisms.4,5 The most well known cannabinoids are delta-9 tetrahydrocannabinol (THC), CBD, and cannabinol (CBN). All cannabinoids are ligands for CB receptors. CB 1 receptors are present mainly in the brain and CB 2 receptors are in the immune system.6 THC is the main cannabinoid that is responsible for the euphoric feelings and psychoactive effects of cannabis. CBD does not activate CB receptors but interacts with other noncannabinoid systems to modulate the psychoactive activity of THC. CBN is mildly psychoactive as it has a higher affinity to CB 2 than CB 1 receptors.6 Medicinal cannabis has been used in the management of various conditions including: palliative care, chemotherapy-induced nausea and vomiting, chronic pain, multiple sclerosis, and epilepsy in paediatric and adult patients with different degrees of benefits. To date, only a few studies addressing the benefits and studies of medicinal cannabis are published.7,8 The introduction of medicinal cannabis has presented some challenges for health professionals because its introduction has not followed the usual research-based safety and effectiveness processes required by the Therapeutic Goods Administration (TGA) in Australia and other countries. These practices include pharmaceutical, animal, pharmacological, and clinical research recommended under national medicines frameworks upheld by the TGA in Australia and the New Zealand Medicines and Medical Devices Safety Authority (Medsafe), as well as by legislation such as the Narcotic Drugs Act 1967. Therefore, careful consideration by healthcare professionals is required to ensure the appropriate prescribing and dispensing of medicinal cannabis. There is also a concern for the use of medicinal cannabis on public health and its legalizations in many countries without enough evidence to support its use. There is also fear about the use of medicinal cannabis to overcome overdose and deaths from the high use of opioids. There is still not enough evidence to support the use of medicinal cannabis for chronic conditions as the evidence is still very modest.9 Opioids have extremely high risk of dependence and fatal overdose. Despite this, more than 20 million opioid prescriptions are filled each year in Canada. Moreover, drug overdoses are now the leading cause of death among Americans under the age of 50. Opioids are involved in nearly half of these deaths. Given these facts, this has led to the proposition of using medicinal cannabis as an alternative treatment to opioids for various conditions including chronic pain.9 To date, there is not enough robust evidence to support or refute the benefits and safety of medicinal cannabis in the management of various chronic conditions. Therefore, there is a substantial need for larger, high-quality studies to investigate the potential benefits, limitations, and safety issues associated with medicinal cannabis treatment for a number of health conditions and symptoms. Future rigorous research has the potential to increase the amount and quality of evidence for the use of medicinal cannabis as an approved treatment for various health conditions. This will also provide governing organizations with more information about the most effective cannabis products, doses, and administration methods. Another huge gap that will need to be addressed is how cannabis is interacting with other medications that patients are taking. This is important to explore as many of the patients who will resolve to using cannabis will have chronic conditions and are possibly on several medications. Future studies should assess patient-relevant outcomes (including disease-specific end points, quality of life, and adverse events) using standardized outcome measures. Comparative trials addressing the benefits of medicinal cannabis against the currently approved treatment will also provide valuable information regarding the efficacy of medicinal cannabis as a new or add on treatment for many chronic conditions. Acknowledgements Conflicts of interest The author reports no conflicts of interest.

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,003
score de la tête « metaresearch » (Gemma)0,011
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMétarecherche, Méta-épidémiologie (sens strict), Intégrité de la recherche, Charge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Éditorial · Signal consensuel: Éditorial
Score de désaccord entre enseignants0,291
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0030,011
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0010,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0010,003
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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.

Tête enseignante Opus0,102
Tête enseignante GPT0,448
Écart entre enseignants0,346 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeSans objet
Domainenon disponible
GenreÉditorial

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2018
Routes d'admission1
Résumé présentoui

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