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Record W2806774532 · doi:10.1097/xeb.0000000000000145

Medicinal cannabis

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

Bibliographic record

VenueInternational Journal of Evidence-Based Healthcare · 2018
Typeeditorial
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsnot available
Fundersnot available
KeywordsCannabidiolCannabisSynthetic cannabinoidsTetrahydrocannabinolDronabinolEndocannabinoid systemCannabinoidPharmacologyCannabinolMedicineCannabinoid receptorEffects of cannabisTraditional medicineReceptorPsychiatryInternal medicine

Abstract

fetched live from 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.

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)0.003
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.291
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0010.000

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 head0.102
GPT teacher head0.448
Teacher spread0.346 · 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 designNot applicable
Domainnot available
GenreEditorial

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

Citations1
Published2018
Admission routes1
Has abstractyes

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