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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. Keywords: Medical marijuana, Cannabis, Cannabinoids, Cannabidiol, Marijuana efficacy, Commonly recommended conditions for marijuana treatment, Marijuana clinical outcomes, Author(s): Sebastian Jugl [a,b]; Aimalohi Okpeku [a,b]; Brianna Costales [a,b]; Earl J. Morris [a,b]; Golnoosh Alipour-Haris [a,b]; Juan M. Hincapie-Castillo [a,b]; Nichole E. Stetten [c]; Ruba Sajdeya [d]; Shailina Keshwani [...]

Background: Chronic cough (CC), characterized as a cough lasting >8 weeks, is a common multi-factorial syndrome in the community, especially in older adults. Methods: Using a pre-existing algorithm to identify patients with CC within the 2011–2018 Medicare beneficiaries, we examined trends in gabapentinoid use through repeated cross-sectional analyses and identified distinct utilization trajectories using group-based trajectory modeling (GBTM) in a retrospective cohort study. Individuals without CC but with any respiratory conditions related to cough served as a comparator group. Results: Among patients with CC, gabapentinoid use increased from 18.6% in 2011 to 24.1% in 2018 (p = 0.002), with a similar upward trend observed in the non-CC cohort but with overall lower usage (14.7% to 18.4%; p < 0.001). Patients with CC had significantly higher burdens of respiratory and non-respiratory comorbidities, as well as greater healthcare service and medication use compared to the non-CC cohort. The GBTM analyses identified three distinct gabapentinoid utilization trajectories for CC and non-CC patients: no use (77.3% vs. 84.5%), low use (13.9% vs. 10.3%), and high use (8.8% vs. 5.2%). Conclusions: Future studies are needed to evaluate the safety and effectiveness of gabapentinoid use in patients with refractory or unexplained CC in real-world settings. [ABSTRACT FROM AUTHOR]

Background/Objectives: Concurrent opioid (OPI) and benzodiazepine (BZD) use may exacerbate injurious fall risk (e.g., falls and fractures) compared to no use or use alone. Yet, patients may need concurrent OPI-BZD use for co-occurring conditions (e.g., pain and anxiety). Therefore, we examined the association between longitudinal OPI-BZD dosing patterns and subsequent injurious fall risk. Methods: We conducted a retrospective cohort study including non-cancer fee-for-service Medicare beneficiaries initiating OPI and/or BZD in 2016–2018. We identified OPI-BZD use patterns during the 3 months following OPI and/or BZD initiation (i.e., trajectory period) using group-based multi-trajectory models. We estimated the time to first injurious falls within the 3-month post-trajectory period using inverse-probability-of-treatment-weighted Cox proportional hazards models. Results: Among 622,588 beneficiaries (age ≥ 65 = 84.6%, female = 58.1%, White = 82.7%; having injurious falls = 0.45%), we identified 13 distinct OPI-BZD trajectories: Group (A): Very-low OPI-only (early discontinuation) (44.9% of the cohort); (B): Low OPI-only (rapid decline) (15.1%); (C): Very-low OPI-only (late discontinuation) (7.7%); (D): Low OPI-only (gradual decline) (4.0%); (E): Moderate OPI-only (rapid decline) (2.3%); (F): Very-low BZD-only (late discontinuation) (11.5%); (G): Low BZD-only (rapid decline) (4.5%); (H): Low BZD-only (stable) (3.1%); (I): Moderate BZD-only (gradual decline) (2.1%); (J): Very-low OPI (rapid decline)/Very-low BZD (late discontinuation) (2.9%); (K): Very-low OPI (rapid decline)/Very-low BZD (increasing) (0.9%); (L): Very-low OPI (stable)/Low BZD (stable) (0.6%); and (M): Low OPI (gradual decline)/Low BZD (gradual decline) (0.6%). Compared with Group (A), six trajectories had an increased 3-month injurious falls risk: (C): HR = 1.78, 95% CI = 1.58–2.01; (D): HR = 2.24, 95% CI = 1.93–2.59; (E): HR = 2.60, 95% CI = 2.18–3.09; (H): HR = 2.02, 95% CI = 1.70–2.40; (L): HR = 2.73, 95% CI = 1.98–3.76; and (M): HR = 1.96, 95% CI = 1.32–2.91. Conclusions: Our findings suggest that 3-month injurious fall risk varied across OPI-BZD trajectories, highlighting the importance of considering both dose and duration when assessing injurious fall risk of OPI-BZD use among older adults. [ABSTRACT FROM AUTHOR]

Purpose: With the expansion of research utilizing electronic healthcare data to identify transgender (TG) population health trends, the validity of computational phenotype (CP) algorithms to identify TG patients is not well understood. We aim to identify the current state of the literature that has utilized CPs to identify TG people within electronic healthcare data and their validity, potential gaps, and a synthesis of future recommendations based on past studies. Methods: Authors searched the National Library of Medicine's PubMed, Scopus, and the American Psychological Association PsycInfo's databases to identify studies published in the United States that applied CPs to identify TG people within electronic healthcare data. Results: Twelve studies were able to validate or enhance the positive predictive value (PPV) of their CP through manual chart reviews (n = 5), hierarchy of code mechanisms (n = 4), key text‐strings (n = 2), or self‐surveys (n = 1). CPs with the highest PPV to identify TG patients within their study population contained diagnosis codes and other components such as key text‐strings. However, if key text‐strings were not available, researchers have been able to find most TG patients within their electronic healthcare databases through diagnosis codes alone. Conclusion: CPs with the highest accuracy to identify TG patients contained diagnosis codes along with components such as procedural codes or key text‐strings. CPs with high validity are essential to identifying TG patients when self‐reported gender identity is not available. Still, self‐reported gender identity information should be collected within electronic healthcare data as it is the gold standard method to better understand TG population health patterns. [ABSTRACT FROM AUTHOR]

Background: Severe skin and soft tissue infections related to injection drug use have increased in concordance with a shift to heroin and illicitly manufactured fentanyl. Opioid agonist therapy medications (methadone and buprenorphine) may improve long-term outcomes by reducing injection drug use. We aimed to examine the association of medication use with mortality among people with opioid use-related skin or soft tissue infections. Methods: An observational cohort study of Medicaid enrollees aged 18 years or older following their first documented medical encounters for opioid use-related skin or soft tissue infections during 2007–2018 in North Carolina. The exposure was documented medication use (methadone or buprenorphine claim) in the first 30 days following initial infection compared with no medication claim. Using Kaplan–Meier estimators, we examined the difference in 3-year incidence of mortality by medication use, weighted for year, age, comorbidities, and length of hospital stay. Results: In this sample, there were 13,286 people with opioid use-related skin or soft tissue infections. The median age was 37 years, 68% were women, and 78% were white. In Kaplan–Meier curves for the total study population, 12 of every 100 patients died during the first 3 years. In weighted models, for every 100 people who used medications, there were four fewer deaths over 3 years (95% confidence interval = 2, 6). Conclusion: In this study, people with opioid use-related skin and soft tissue infections had a high risk of mortality following their initial healthcare visit for infections. Methadone or buprenorphine use was associated with reductions in mortality. [ABSTRACT FROM AUTHOR]

Conserved in female reproduction across all mammalian species is the estrous cycle and its regulation by the hypothalamic-pituitary-gonadal (HPG) axis, a collective of intersected hormonal events that are crucial for ensuring uterine fertility. Nonetheless, knowledge of the direct mediators that synchronously shape the uterine microenvironment for successive yet distinct events, such as the transit of sperm and support for progressive stages of preimplantation embryo development, remain principally deficient. Toward understanding the timed endometrial outputs that permit luminal events as directed by the estrous cycle, we used Bovidae as a model system to uniquely surface sample and study temporal shifts to in vivo endometrial transcripts that encode for proteins destined to be secreted. The results revealed the full quantitative profile of endometrial components that shape the uterine luminal microenvironment at distinct phases of the estrous cycle (estrus, metestrus, diestrus, and proestrus). In interpreting this comprehensive log of stage-specific endometrial secretions, we define the "uterine secretory cycle" and extract a predictive understanding of recurring physiological actions regulated within the uterine lumen in anticipation of sperm and preimplantation embryonic stages. This repetitive microenvironmental preparedness to sequentially provide operative support was a stable intrinsic framework, with only limited responses to sperm or embryos if encountered in the lumen within the cyclic time period. In uncovering the secretory cycle and unraveling realistic biological processes, we present novel foundational knowledge of terminal effectors controlled by the HPG axis to direct a recurring sequence of vital functions within the uterine lumen. NEW & NOTEWORTHY This study unravels the recurring sequence of changes within the uterus that supports vital functions (sperm transit and development of preimplantation embryonic stages) during the reproductive cycle in female Ruminantia. These data present new systems knowledge in uterine reproductive physiology crucial for setting up in vitro biomimicry and artificial environments for assisted reproduction technologies for a range of mammalian species. [ABSTRACT FROM AUTHOR]