Cannabis Use and Inhalational Anesthesia Administration in Older Adults: A Propensity Matched Retrospective Cohort Study.

BACKGROUND: Cannabis use is associated with higher intravenous anesthetic administration. Similar data regarding inhalational anesthetics are limited. With rising cannabis use prevalence, understanding any potential relationship with inhalational anesthetic dosing is crucial. We compared average intraoperative isoflurane/sevoflurane minimum alveolar concentration equivalents between older adults with and without cannabis use. METHODS: The electronic health records of 22,476 surgical patients ≥65 years old at the University of Florida Health System between 2018-2020 were reviewed. The primary exposure was cannabis use within 60 days of surgery, determined via i) a previously published natural language processing algorithm applied to unstructured notes and ii) structured data, including International Classification of Disease codes for cannabis use disorders and poisoning by cannabis, laboratory cannabinoids screening results, and RxNorm codes. The primary outcome was the intraoperative time-weighted average of isoflurane/sevoflurane minimum alveolar concentration equivalents at one-minute resolution. No a priori minimally clinically important difference was established. Patients demonstrating cannabis use were matched 4:1 to non-cannabis use controls using a propensity score. RESULTS: Among 5,118 meeting inclusion criteria, 1,340 patients (268 cannabis users and 1,072 nonusers) remained after propensity score matching. The median and interquartile range (IQR) age was 69 (67, 73) years; 872 (65.0%) were male, and 1,143 (85.3%) were non-Hispanic White. The median (IQR) anesthesia duration was 175 (118, 268) minutes. After matching, all baseline characteristics were well-balanced by exposure. Cannabis users had statistically significantly higher average minimum alveolar concentrations than nonusers [mean±SD: 0.58±0.23 versus 0.54±0.22, respectively; mean difference=0.04; 95% confidence limits, 0.01 to 0.06; p=0.020]. CONCLUSION: Cannabis use was associated with administering statistically significantly higher inhalational anesthetic minimum alveolar concentration equivalents in older adults, but the clinical significance of this difference is unclear. These data do not support the hypothesis that cannabis users require clinically meaningfully higher inhalational anesthetics doses.

Prenatal Exposure to Valproic Acid Across Various Indications for Use.

Importance: Teratogenic outcomes associated with valproic acid use represent a substantial concern for persons of childbearing age. Regulatory agencies worldwide have enhanced warnings or implemented risk minimization programs to reduce exposure during pregnancy. Objectives: To determine pregnancy rates during valproic acid use and concomitant contraception use across indications. Design, Setting, and Participants: This retrospective cohort study used data from the Merative MarketScan commercial claims databases from January 1, 2005, to December 31, 2020, to identify female patients aged 12 to 44 years who initiated valproic acid treatment and had continuous insurance enrollment 6 months before initiation and 9 months after treatment end. A treatment episode included consecutive prescription fills that occurred within 7 days from the end of the days' supply of the previous dispensing. Data were analyzed from March 1 to September 10, 2023. Main Outcomes and Measures: Treatment episodes were categorized by inferred indication using diagnoses preceding treatment initiation, including epilepsy, migraine or headache, mood disorders, and unknown or off-label uses. Pregnancy incidence rate ratios (IRRs) were calculated and were adjusted for age and calendar year. Contraceptive use (prescription contraceptives, intrauterine devices, and implants) during treatment was examined. Results: The cohort included 165 772 valproic acid treatment episodes among 69 390 women (mean [SD] age, 29.8 [10.0] years). Mood disorders (42.5%) were the most common indication, followed by migraine or headache (20.1%), with epilepsy playing a minor role (14.9%). Pregnancy incidence rates during valproic acid use remained unchanged, with a rate of 1.74 (95% CI, 1.14-2.53) per 100 person-years in 2005 and a rate of 1.90 (95% CI, 1.16-3.12) per 100 person-years in 2019. Compared with epilepsy, pregnancy rates were more than double for mood disorder (IRR, 2.16 [95% CI, 1.93-2.42]) and migraine or headache (IRR, 2.01 [95% CI, 1.92-2.09]). Few treatment episodes coincided with contraceptive use (37 012 [22.3%]), and oral dosage forms were the most common (27 069 [73.1%]). Conclusions and Relevance: In this cohort study of patients of childbearing age who used valproic acid, pregnancy rates during valproic acid use did not decrease despite enhanced US Food and Drug Administration safety communications, and contraception use remained low. Patients with migraine and mood disorders accounted for the largest proportion of valproic acid use and had the highest pregnancy rates, while patients with epilepsy had the lowest. These findings suggest a need to enhance efforts to mitigate prenatal exposure to valproic acid, especially for indications where the risk of use during pregnancy outweighs the benefit.

Cannabis use and acute postoperative pain outcomes in older adults: a propensity matched retrospective cohort study.

INTRODUCTION: Cannabis use is increasing among older adults, but its impact on postoperative pain outcomes remains unclear in this population. We examined the association between cannabis use and postoperative pain levels and opioid doses within 24 hours of surgery. METHODS: We conducted a propensity score-matched retrospective cohort study using electronic health records data of 22 476 older surgical patients with at least 24-hour hospital stays at University of Florida Health between 2018 and 2020. Of the original cohort, 2577 patients were eligible for propensity-score matching (1:3 cannabis user: non-user). Cannabis use status was determined via natural language processing of clinical notes within 60 days of surgery and structured data. The primary outcomes were average Defense and Veterans Pain Rating Scale (DVPRS) score and total oral morphine equivalents (OME) within 24 hours of surgery. RESULTS: 504 patients were included (126 cannabis users and 378 non-users). The median (IQR) age was 69 (65-72) years; 295 (58.53%) were male, and 442 (87.70%) were non-Hispanic white. Baseline characteristics were well balanced. Cannabis users had significantly higher average DVPRS scores (median (IQR): 4.68 (2.71-5.96) vs 3.88 (2.33, 5.17); difference=0.80; 95% confidence limit (CL), 0.19 to 1.36; p=0.01) and total OME (median (IQR): 42.50 (15.00-60.00) mg vs 30.00 (7.50-60.00) mg; difference=12.5 mg; 95% CL, 3.80 mg to 21.20 mg; p=0.02) than non-users within 24 hours of surgery. DISCUSSION: This study showed that cannabis use in older adults was associated with increased postoperative pain levels and opioid doses.

Protocol of a Combined Cohort and Cross-Sectional Study of Persons Receiving Medical Cannabis in Florida, USA: The Medical Marijuana and Me (M3) Study.

Significant knowledge gaps regarding the effectiveness and safety of medical cannabis (MC) create clinical challenges for MC physicians, making treatment recommendations and patients choosing treatment among the growing number of options offered in dispensaries. Additionally, data describing the characteristics of people who use MC and the products and doses they receive are lacking. The Medical Marijuana and Me (M3) Study was designed to collect patient-centered data from MC users. We aim to describe preferred MC use patterns that patients report as "most effective" for specific health conditions and symptoms, identify user characteristics associated with such use patterns, characterize adverse effects, including cannabis use disorder, identify products and patient characteristics associated with adverse effects, describe concurrent prescription medication use, and identify concomitant medication use with potential drug-MC interaction risk. Among MC initiators, we also aim to quantify MC use persistence and identify reasons for discontinuation, assess MC utilization pattern trajectories over time, describe outcome trajectories of primary reasons for MC use and determine factors associated with different trajectories, track changes in concomitant substance and medication use after MC initiation, and identify factors associated with such changes. M3 is a combined study comprised of: (1) a prospective cohort of MC initiators completing surveys at enrollment, 3 months, and 9 months after MC initiation and (2) a cross-sectional study of current MC users. A multidisciplinary committee including researchers, physicians, pharmacists, patients, and dispensary personnel designed and planned study protocols, established study measures, and created survey questionnaires. M3 will recruit 1,000-1,200 participants aged ≥18 years, with ∼50% new and ∼50% current MC patients from MC clinics across Florida, USA. Study enrollment started in May 2022 and will continue until the target number of patients is achieved. Survey domains include sociodemographic characteristics, physical and mental health, cannabis use history, reasons for MC use and discontinuation, MC products and use patterns, concurrent use of prescription medications and other substances, and side effects. Data collected in the M3 Study will be available for interested researchers affiliated with the Consortium for Medical Marijuana Clinical Outcomes Research. The M3 Study and Databank will be the largest cohort of current and new MC users in Florida, USA, which will provide data to support MC-related health research necessary to inform policy and clinical practice and ultimately improve patient outcomes.

Developing and validating a natural language processing algorithm to extract preoperative cannabis use status documentation from unstructured narrative clinical notes.

OBJECTIVE: This study aimed to develop a natural language processing algorithm (NLP) using machine learning (ML) techniques to identify and classify documentation of preoperative cannabis use status. MATERIALS AND METHODS: We developed and applied a keyword search strategy to identify documentation of preoperative cannabis use status in clinical documentation within 60 days of surgery. We manually reviewed matching notes to classify each documentation into 8 different categories based on context, time, and certainty of cannabis use documentation. We applied 2 conventional ML and 3 deep learning models against manual annotation. We externally validated our model using the MIMIC-III dataset. RESULTS: The tested classifiers achieved classification results close to human performance with up to 93% and 94% precision and 95% recall of preoperative cannabis use status documentation. External validation showed consistent results with up to 94% precision and recall. DISCUSSION: Our NLP model successfully replicated human annotation of preoperative cannabis use documentation, providing a baseline framework for identifying and classifying documentation of cannabis use. We add to NLP methods applied in healthcare for clinical concept extraction and classification, mainly concerning social determinants of health and substance use. Our systematically developed lexicon provides a comprehensive knowledge-based resource covering a wide range of cannabis-related concepts for future NLP applications. CONCLUSION: We demonstrated that documentation of preoperative cannabis use status could be accurately identified using an NLP algorithm. This approach can be employed to identify comparison groups based on cannabis exposure for growing research efforts aiming to guide cannabis-related clinical practices and policies.

Priorities for Medical Marijuana Research from the Perspective of Physicians, Dispensary Owners/Staff, and Patients: A Survey Study.

OBJECTIVE: More patients are turning to medical marijuana as an alternative treatment, yet there are apparent knowledge gaps on the risk benefit of medical marijuana for a variety of indications. This study aimed to determine the priorities for medical marijuana research from the perspective of multiple stakeholders including patients, clinicians, and industry representatives. METHODS: An anonymous survey was administered to attendees of the 2019 American Medical Marijuana Physicians Association annual meeting in Orlando, Florida. Respondents completed the survey on paper or smartphone via Qualtrics. The survey included questions on demographics and medical marijuana research priorities under the following broad categories: clinical conditions, safety issues, marijuana types, populations, and others. RESULTS: Forty-six participants (56.5% female, mean age = 51.6 ± 14.1) responded to the survey. A majority were medical marijuana qualified physicians in Florida (56.5%), 30.5% other physicians or clinicians, and 21.7% medical marijuana patients (multiple choices allowed). The top conditions prioritized for research by this group were chronic pain, cancer, and anxiety, and the top priority safety issues were dosing/product choice, complications from smoking/vaping, and drug interactions. Regarding marijuana types, the group prioritized research on THC/CBD ratios, different modes of consumption, and terpenes. CONCLUSIONS: Findings from this survey indicate that medical marijuana stakeholders perceived a broad range of research topics as priorities. More research is needed to advance the evidence in these areas and provide guidance to patients, physicians, and the medical marijuana industry.

Practice Patterns and Training Needs Among Physicians Certifying Patients for Medical Marijuana in Florida.

BACKGROUND: Little is known about the clinical training or practice experiences among physicians who certify patients for medical marijuana. The objective of this study was to determine information sources, factors influencing recommendations, clinical practices in patient assessment, communications, and recommendations, and priority areas for additional training among physicians who certify patients for medical marijuana. METHODS: A cross-sectional state-wide anonymous survey of registered medical marijuana physicians in Florida between June and October 2020 was administered. Numerical responses were quantified using counts and percentages. The frequencies for "often" and "always" responses were aggregated when appropriate. RESULTS: Among 116 respondents, the mean (standard deviation) age was 57 (12) years old, and 70% were male. The most frequently used information sources were research articles (n = 102, 95%), followed by online sources (n = 99, 93%), and discussions with other providers and dispensary staff (n = 84, 90%). Safety concerns were most influential in patient recommendations (n = 39, 39%), followed by specific conditions (n = 30, 30%) and patient preferences (n = 26, 30%). Ninety-three physicians (92%) reported they "often" or "always" perform a patient physical exam. Eighty-four (77%) physicians provided specific administration route recommendations. Half (n = 56) "often" or "always" provided specific recommendations for Δ-9-tetrahydrocannabinol: cannabidiol ratios, while 69 (62%) "often" or "always" provided specific dose recommendations. Online learning/training modules were the most preferred future training mode, with 88 (84%) physicians "likely" or "very likely" to participate. The top 3 desired topics for future training were marijuana-drug interactions (n = 84, 72%), management of specific medical conditions or symptoms (n = 83, 72%), and strategies to reduce opioids or other drugs use (n = 78, 67%). CONCLUSIONS: This survey of over 100 medical marijuana physicians indicates that their clinical practices rely on a blend of research and anecdotal information sources. While physicians report clinical factors as influential during patient recommendation, patient assessment practices and treatment regimen recommendations vary substantially and rely on experimental approaches. More research is needed to inform evidence-based practice and training, especially considering details on drug interactions, risk-benefit of treatment for specific clinical conditions, and strategies to reduce opioid use.

A Mapping Literature Review of Medical Cannabis Clinical Outcomes and Quality of Evidence in Approved Conditions in the USA from 2016 to 2019.

In 2017, a National Academies of Sciences, Engineering, and Medicine (NASEM) report comprehensively evaluated the body of evidence regarding cannabis health effects through the year 2016. The objectives of this study are to identify and map the most recently (2016-2019) published literature across approved conditions for medical cannabis and to evaluate the quality of identified recent systematic reviews, published following the NASEM report. Following the literature search from 5 databases and consultation with experts, 11 conditions were identified for evidence compilation and evaluation: amyotrophic lateral sclerosis, autism, cancer, chronic noncancer pain, Crohn's disease, epilepsy, glaucoma, human immunodeficiency virus/AIDS, multiple sclerosis (MS), Parkinson's disease, and posttraumatic stress disorder. A total of 198 studies were included after screening for condition-specific relevance and after imposing the following exclusion criteria: preclinical focus, non-English language, abstracts only, editorials/commentary, case studies/series, and non-U.S. study setting. Data extracted from studies included: study design type, outcome definition, intervention definition, sample size, study setting, and reported effect size. Few completed randomized controlled trials (RCTs) were identified. Studies classified as systematic reviews were graded using the Assessing the Methodological Quality of Systematic Reviews-2 tool to evaluate the quality of evidence. Few high-quality systematic reviews were available for most conditions, with the exceptions of MS (9 of 9 graded moderate/high quality; evidence for 2/9 indicating cannabis improved outcomes; evidence for 7/9 indicating cannabis inconclusive), epilepsy (3 of 4 graded moderate/high quality; 3 indicating cannabis improved outcomes; 1 indicating cannabis inconclusive), and chronic noncancer pain (12 of 13 graded moderate/high quality; evidence for 7/13 indicating cannabis improved outcomes; evidence from 6/7 indicating cannabis inconclusive). Among RCTs, we identified few studies of substantial rigor and quality to contribute to the evidence base. However, there are some conditions for which significant evidence suggests that select dosage forms and routes of administration likely have favorable risk-benefit ratios (i.e., epilepsy and chronic noncancer pain). The body of evidence for medical cannabis requires more rigorous evaluation before consideration as a treatment option for many conditions, and evidence necessary to inform policy and treatment guidelines is currently insufficient for many conditions.