Journal of cannabis research最新文献

Background: The Veterans Health Administration tracks urine drug tests (UDTs) among patients on long-term opioid therapy (LTOT) and recommends discussing the health effects of cannabis use.

Objective: To determine the occurrence of cannabis-related discussions between providers and patients on LTOT during six months following UDT positive for cannabis, and examine factors associated with documenting cannabis use.

Design: We identified patients prescribed LTOT with a UDT positive for cannabis in 2019. We developed a text-processing tool to extract discussions around cannabis use from their charts.

Subjects: Twelve thousand seventy patients were included. Chart review was conducted on a random sample of 1,946 patients.

Main measures: The presence of a cannabis term in the chart suggesting documented cannabis use or cannabis-related discussions. Content of those discussions was extracted in a subset of patients. Logistic regression was used to examine the association between patient factors, including state of residence legal status, with documentation of cannabis use.

Key results: Among the 12,070 patients, 65.8% (N = 7,948) had a cannabis term, whereas 34.1% (N = 4,122) of patients lacked a cannabis term, suggesting that no documentation of cannabis use or discussion between provider and patient took place. Among the subset of patients who had a discussion documented, 47% related to cannabis use for medical reasons, 35% related to a discussion of VA policy or legal issues, and 17% related to a discussion specific to medical risks or harm reduction strategies. In adjusted analyses, residents of states with legalized recreational cannabis were less likely to have any cannabis-related discussion compared to patients in non-legal states [OR 0.73, 95% CI 0.64-0.82].

Conclusions: One-third of LTOT patients did not have documentation of cannabis use in the chart in the 6 months following a positive UDT for cannabis. Discussions related to the medical risks of cannabis use or harm reduction strategies were uncommon.

Background: Cannabis policies have changed drastically over the last few years with many states enacting medical cannabis laws, and some authorizing recreational use; all against federal laws. As a result, cannabis products are marketed in dispensaries in different forms, most abundantly as flowers intended for smoking and sometimes vaping. All samples used in this study were obtained directly from law enforcement. The sample collection process was facilitated and funded by the National Marijuana Initiative (NMI), part of the High-Intensity Drug Trafficking Area (HIDTA) program. This initial report focuses on cannabis flowers. Similar studies with other cannabis products will be the subject of a future report.

Methods: A total of 107 Δ⁹-THC cannabis flower samples were collected by law enforcement from adult commercial use cannabis dispensaries, located in three different states (Colorado, Oregon, and California) and analyzed in this study for cannabinoid concentration. Samples were analyzed by GC-FID following our previously published procedure.

Discussion: The label claims for total Δ⁹-THC content ranged from 12.04 to 58.20% w/w, while GC-FID results showed a concentration ranging from 12.95 to 36.55% w/w. Of the evaluated 107 products, only 32 samples have Δ⁹-THC content within ± 20% of the labeled content. However, the remaining 75 samples were found to be out of the ± 20% acceptance criteria. The degree of agreement for the tested samples using ± 20% tolerance with label claims was only 30%. The results of this study indicate that there is a need for more stringent regulations to ensure that product labeling is accurate, as 70% of the evaluated products did not meet the ± 20% acceptance criteria. This highlights the importance of healthcare professionals and patients being vigilant about the Δ⁹-THC content, as inaccurate labeling of cannabis products could potentially result in adverse health effects. Furthermore, there is a pressing need for more rigorous regulation of commercial cannabis products in the United States.

Background: While the use of orally consumed Cannabis, cannabidiol (CBD) and tetrahydrocannabinol (THC) containing products, i.e. "edibles", has expanded, the health consequences are still largely unknown. This study examines the effects of oral consumption of whole Cannabis and a complex Cannabis extract on neurochemicals, endocannabinoids (eCB), and physiological parameters (body temperature, heart rate) in mice.

Methods: In this pilot study, C57BL/6 J mice were treated with one of the following every other day for 2 weeks: a complex Cannabis extract by gavage, whole Cannabis mixed with nutritional gel through free feeding, or purified THC/CBD by intraperitoneal (i.p.) injection. Treatments were conducted at 4 doses ranging from 0-100 mg/kg/day of CBD with THC levels of ≤ 1.2 mg/kg/day for free feeding and gavage and 10 mg/kg/day for i.p. Body temperature and heart rate were monitored using surgically implanted telemetry devices. Levels of neurochemicals, eCB, THC, CBD, and 11-OH-THC were measured using mass spectrometry 48 h after the final treatment. Statistical comparisons were conducted using ANOVA and t-tests.

Results: Differences were found between neurochemicals in the brains and plasma of mice treated by i.p. (e.g. dopamine, p < 0.01), gavage (e.g., phenylalanine, p < 0.05) and in mice receiving whole Cannabis (e.g., 3,4-dihydroxyphenylacetic DOPAC p < 0.05). Tryptophan trended downward or was significantly decreased in the brain and/or plasma of all mice receiving Cannabis or purified CBD/THC, regardless of dose, compared to controls. Levels of the eCB, arachidonoyl glycerol (2-AG) were decreased in mice receiving lowest doses of a complex Cannabis extract by gavage, but were higher in mice receiving highest doses compared to controls (p < 0.05). Plasma and brain levels of THC and 11-OH-THC were higher in mice receiving 1:1 THC:CBD by i.p. compared to those receiving 1:5 or 1:10 THC:CBD. Nominal changes in body temperature and heart rate following acute and repeated exposures were seen to some degree in all treatments.

Conclusions: Changes to neurochemicals and eCBs were apparent at all doses regardless of treatment type. Levels of neurochemicals seemed to vary based on the presence of a complex Cannabis extract, suggesting a non-linear response between THC and neurochemicals following repeated oral dosing.

Background: The primary components driving the current commercial fascination with cannabis products are phytocannabinoids, a diverse group of over 100 lipophilic secondary metabolites derived from the cannabis plant. Although numerous phytocannabinoids exhibit pharmacological effects, the foremost attention has been directed towards Δ⁹-tetrahydrocannabinol (THC) and cannabidiol, the two most abundant phytocannabinoids, for their potential human applications. Despite their structural similarity, THC and cannabidiol diverge in terms of their psychotropic effects, with THC inducing notable psychological alterations. There is a clear need for accurate and rapid THC measurement methods that offer dependable, readily accessible, and cost-effective analytical information. This review presents a comprehensive view of the present state of alternative technologies that could potentially facilitate the creation of portable devices suitable for on-site usage or as personal monitors, enabling non-intrusive THC measurements.

Method: A literature survey from 2017 to 2023 on the development of portable technologies and commercial products to detect THC in biofluids was performed using electronic databases such as PubMed, Scopus, and Google Scholar. A systematic review of available literature was conducted using Preferred Reporting Items for Systematic. Reviews and Meta-analysis (PRISMA) guidelines.

Results: Eighty-nine studies met the selection criteria. Fifty-seven peer-reviewed studies were related to the detection of THC by conventional separation techniques used in analytical laboratories that are still considered the gold standard. Studies using optical (n = 12) and electrochemical (n = 13) portable sensors and biosensors were also identified as well as commercially available devices (n = 7).

Discussion: The landscape of THC detection technology is predominantly shaped by immunoassay tests, owing to their established reliability. However, these methods have distinct drawbacks, particularly for quantitative analysis. Electrochemical sensing technology holds great potential to overcome the challenges of quantification and present a multitude of advantages, encompassing the possibility of miniaturization and diverse modifications to amplify sensitivity and selectivity. Nevertheless, these sensors have considerable limitations, including non-specific interactions and the potential interference of compounds and substances existing in biofluids.

Conclusion: The foremost challenge in THC detection involves creating electrochemical sensors that are both stable and long-lasting while exhibiting exceptional selectivity, minimal non-specific interactions, and decreased susceptibility to matrix interferences. These aspects need to be resolved before these sensors can be successfully introduced to the market.

Background: To address the research question of how simultaneous users of alcohol and cannabis differ from concurrent users in risk of cannabis use problems after the recreational marijuana legalization in Washington State.

Methods: We used generalized estimating equations with a Poisson distribution to analyze the association between simultaneous use of alcohol and marijuana (SAM) and cannabis-related problems compared to concurrent use. The data is a longitudinal sample of drinkers and cannabis users (n = 257, 47% female) aged 18 years and older from Washington State in 2014-2016. We adjusted for survey weights to account for differential probability of selection and response rates. The primary outcome is the past-six-month CUDIT problem subscale (ranging from 0 to 28), which is the total score for seven CUDIT problem items, after excluding the three items that covered marijuana use frequency. Covariates include marijuana use frequency (daily/near daily use, regular use, or infrequent use), marijuana daily quantity, alcohol daily volume, panel survey cycle, medical marijuana recommendation, driving time to nearest marijuana outlet, age of marijuana use onset, and other demographics.

Results: After adjusting for covariates, we found that compared to concurrent use, SAM was significantly positively associated with CUDIT problem subscale (IRR = 1.68, 95% CI: 1.25-2.27, p < 0.001); daily/near daily use of marijuana was strongly significantly associated with CUDIT problem subscale compared with infrequent use (IRR = 5.1, 2.71-9.57, p < 0.001) or regular use (IRR = 3.05, 1.91-4.85, p < 0.001). Secondary analyses using CUDIT total score as the outcome also showed a significant positive association with SAM compared to concurrent use (IRR = 1.17, 1.02-1.34, p < 0.05).

Conclusions: This study highlighted the importance of SAM, in addition to cannabis use frequency for predicting cannabis-related problems.

Objective: Marijuana use is increasingly common among patients with chronic non-cancer pain (CNCP) and long-term opioid therapy (LTOT). We determined if lifetime recreational and medical marijuana use were associated with more frequent and higher dose prescription opioid use.

Design: Cross-sectional SUBJECTS: Eligible patients (n=1,037), who had a new period of prescription opioid use lasting 30-90 days, were recruited from two midwestern health care systems to a study of long-term prescription opioid use and mental health outcomes. The present cross-sectional analyses uses baseline data from this on-going cohort study.

Methods: Primary exposures were participant reported lifetime recreational and medical marijuana use versus no lifetime marijuana use. Prescription opioid characteristics included daily versus non-daily opioid use and ≥50 morphine milligram equivalent (MME) dose per day vs. <50 MME. Multivariate, logistic regression models estimated the association between lifetime recreational and medical marijuana use vs. no use and odds of daily and higher dose prescription opioid use, before and after adjusting for confounding.

Results: The sample was an average of 54.9 (SD±11.3) years of age, 57.3% identified as female gender, 75.2% identified as White, and 22.5% identified as Black race. Among all participants, 44.4% were never marijuana users, 21.3% were recreational only, 7.7% medical only and 26.6% were both recreational and medical marijuana users. After controlling for all confounders, lifetime recreational marijuana use, as compared to no use, was significantly associated with increased odds of daily prescription opioid use (OR=1.61; 95%CI:1.02-2.54). There was no association between lifetime recreational or medical marijuana use and daily opioid dose.

Conclusion: Lifetime medical marijuana use is not linked to current opioid dose, but lifetime recreational use is associated with more than a 60% odds of being a daily prescription opioid user. Screening for lifetime recreational marijuana use may identify patients with chronic pain who are vulnerable to daily opioid use which increases risk for adverse opioid outcomes. Prospective data is needed to determine how marijuana use influences the course of LTOT and vice versa.

Objective: Our primary objective was to understand breastfeeding individuals' decisions to use cannabis. Specifically, we investigated reasons for cannabis use, experiences with healthcare providers regarding use, and potential concerns about cannabis use.

Methods: We collected survey data from twenty breastfeeding participants from Washington and Oregon who used cannabis at least once weekly. We documented individuals' cannabis use and analyzed factors associated with their decisions to use cannabis during lactation. Qualitative description was used to assess responses to an open-ended question about potential concerns.

Results: Fifty-five percent of participants (n = 11) reported using cannabis to treat or manage health conditions, mostly related to mental health. Eighty percent of participants (n = 16) reported very few or no concerns about using cannabis while breastfeeding, although participants who used cannabis for medical purposes had significantly more concerns. Most participants (n = 18, 90%) reported receiving either no or unhelpful advice from healthcare providers. Four themes arose through qualitative analysis, indicating that breastfeeding individuals are: 1) identifying research gaps and collecting evidence; 2) monitoring their child's health and development; 3) monitoring and titrating their cannabis use; and 4) comparing risks between cannabis and other controlled substances.

Conclusions: Breastfeeding individuals reported cannabis for medical and non-medical reasons and few had concerns about cannabis use during breastfeeding. Breastfeeding individuals reported using a variety of strategies and resources in their assessment of risk or lack thereof when deciding to use cannabis. Most participants reported receiving no helpful guidance from healthcare providers.

Objectives: In legal cannabis markets, the distribution of retail stores has the potential to influence transitions from illegal to legal sources as well as consumer patterns of use. The current study examined the distribution of legal cannabis stores in Canada according to level of neighbourhood deprivation.

Methods: Postal code data for all legal cannabis stores in Canada were collected from government websites from October 2018 to September 2021. This data was linked to the Institut National de Santé Publique du Québec measures for material and social neighbourhood deprivation. Descriptive data are reported, including differences across provinces with different retail systems.

Results: At the national level, there were approximately 8.0 retail cannabis stores per 100,000 individuals age 15+ in September 2021. The distribution of stores was closely aligned with the expected distribution across levels of material deprivation: for example, 19.5% of stores were located in neighbourhoods with the lowest level of material deprivation versus 19.1% in the highest level. More cannabis stores were located in the 'most socially deprived' or 'socially deprived' neighbourhoods (37.2% and 22.1%, respectively), characterized by a higher proportion of residents who live alone, are unmarried, or in single-parent families. The distribution of stores in provinces and territories were generally consistent with national patterns with a few exceptions.

Conclusion: In the first 3 years following cannabis legalization in Canada, retail cannabis stores were evenly distributed across materially deprived neighbourhoods but were more common in socially deprived neighbourhoods. Future monitoring of retail store locations is required as the legal retail market evolves in Canada.

Background: With the legalization of cannabis in Canada, consumers are presented with numerous purchase options. Licensed retailers are limited by the Cannabis Act and provincial regulations with respect to offering sales, advertising, location, maximum quantities, and information sharing in an effort to protect public health and safety. The degree these policies influence consumer purchase behavior will help inform regulatory refinement.

Methods: A discrete choice experiment within a cross-sectional online survey was used to explore trade-offs consumers make when deciding where to purchase cannabis. Attributes included availability of sales/discounts, proximity, product information, customer service, product variety, and provincial regulation. Participants ≥ 19 years old who lived in Canada and purchased cannabis in the previous 12 months were recruited through an online market research survey panel. A multinomial logit (MNL) model was used for the base model, and latent class analysis was used to assess preference sub-groups. Key limitations included ordering effect, hypothetical bias, and framing effect.

Results: The survey was completed by 1626 people, and the base model showed that customer service carried the most weight in purchase decisions, followed by proximity and availability of sales and discounts. There was considerable heterogeneity in preference patterns, with a five-group latent class model demonstrating best fit. Only one group (15% of sample) placed a high value on the store being provincially regulated, while three groups were willing to make a trade-off with regulation to access better customer service, product information, or closer proximity. One group preferred non-regulated sources (24% of sample); this group was also primarily driven by the availability of sales and discounts. Three groups (60.5% of sample) preferred online stores.

Conclusion: This study highlighted that there exists significant diversity with respect to the influence of consumer experiences on cannabis purchase behaviors. Modifications to cannabis retail regulations that focus on improving access to product information as well as reviewing limitations on sales and discounts could have the most impact for shifting customers to licensed retailers.

Background: Acute cannabis use has been demonstrated to slow reaction time and affect decision-making and short-term memory. These effects may have utility in identifying impairment associated with recent use. However, these effects have not been widely investigated among individuals with a pattern of daily use, who may have acquired tolerance. The purpose of this study was to examine the impact of tolerance to cannabis on the acute effects as measured by reaction time, decision-making (gap acceptance), and short-term memory.

Methods: Participants (ages 25-45) completed a tablet-based (iPad) test battery before and approximately 60 min after smoking cannabis flower. The change in performance from before to after cannabis use was compared across three groups of cannabis users: (1) occasional use (n = 23); (2) daily use (n = 31); or (3) no current use (n = 32). Participants in the occasional and daily use group self-administered ad libitum, by smoking or vaping, self-supplied cannabis flower with a high concentration of total THC (15-30%).

Results: The occasional use group exhibited decrements in reaction time (slowed) and short-term memory (replicated fewer shapes) from before to after cannabis use, as compared to the no-use group. In the gap acceptance task, daily use participants took more time to complete the task post-smoking cannabis as compared to those with no use or occasional use; however, the level of accuracy did not significantly change.

Conclusions: The findings are consistent with acquired tolerance to certain acute psychomotor effects with daily cannabis use. The finding from the gap acceptance task which showed a decline in speed but not accuracy may indicate a prioritization of accuracy over response time. Cognitive and psychomotor assessments may have utility for identifying impairment associated with recent cannabis use.