Care Gaps in Sodium-Glucose Cotransporter-2 Inhibitor and Renin Angiotensin System Inhibitor Prescriptions for Patients with Diabetic Kidney Disease.

BACKGROUND: Renin and angiotensin system inhibitors (RAASi) and sodium-glucose cotransporter-2 inhibitors (SGLT2i) are recommended for patients with diabetic kidney disease (DKD) to reduce the progression to end-stage kidney disease; however, they are under-prescribed. OBJECTIVE: To evaluate the frequency of care gaps in RAASi and SGLT2i prescription by patient demographic, health system, and clinical factors in patients with DKD. DESIGN: Retrospective cohort study. PARTICIPANTS: Adult primary care patients with DKD at an integrated health system in Bronx, NY, with 23 primary care sites in 2021. MAIN MEASURES: The odds of having a care gap for (1) SGLT2i or (2) RAASi prescription. Multivariate logistic regression models were performed for each outcome measure to evaluate associations with patient demographic, health system, and clinical factors. KEY RESULTS: Of 7199 patients with DKD, 80.3% had a care gap in SGLT2i prescription and 42.0% had a care gap in RAASi prescription. For SGLT2i, patients with A1C at goal (aOR 2.32, 95% CI 1.96-2.73), Black non-Hispanic race/ethnicity (aOR 1.46, 95% CI 1.15-1.87), and Hispanic race/ethnicity (aOR 1.46, 95% CI 1.11-1.92) were more likely to experience a care gap. For RAASi, patients with blood pressure at goal (aOR 1.34, 95% CI 1.21-1.49) were more likely to experience a care gap. CONCLUSIONS: The care gaps for SGLT2i and RAASi for patients with DKD with well-controlled diabetes and blood pressure suggest failure to recognize DKD as an independent indication for these medications. Racial/ethnic disparities for SGLT2i, but not for RAASi, suggest systemic racism exacerbates care gaps for novel medications. These factors can be targets for interventions to improve patient care.

First-Year Trajectories of Medical Cannabis Use Among Adults Taking Opioids for Chronic Pain: An Observational Cohort Study.

OBJECTIVE: To describe first-year trajectories of medical cannabis use and identify characteristics associated with patterns of use in a cohort of adults using opioids for chronic pain. DESIGN: Latent class trajectory analysis of a prospective cohort study using data on the 14-day frequency of medical cannabis use. SETTING: A large academic medical center and four medical cannabis dispensaries in the New York City metropolitan area. SUBJECTS: Adults with chronic pain using opioids and newly certified for medical cannabis in New York between 2018 and 2020. METHODS: Using latent class trajectory analysis, we identified clusters of participants based on the 14-day frequency of medical cannabis use. We used logistic regression to determine factors associated with cluster membership, including sociodemographic characteristics, pain, substance use, and mental health symptoms. RESULTS: Among 99 participants, the mean age was 53 years; 62% were women, and 52% were White. We identified three clusters of medical cannabis use: infrequent use (n = 30, mean use = 1.5 days/14-day period), occasional use (n = 28, mean = 5.7 days/14-day period), and frequent use (n = 41, mean = 12.1 days/14-day period). Within clusters, use patterns did not vary significantly over 52 weeks. Differences were observed in two sociodemographic variables: Frequent (vs infrequent) use was associated with non-Hispanic White race/ethnicity (adjusted odds ratio 4.54, 95% confidence interval 1.49-14.29), while occasional (vs infrequent) use was associated with employment (adjusted odds ratio 13.84, 95% confidence interval 1.21-158.74). CONCLUSIONS: Three clusters of medical cannabis use patterns emerged and were stable over time. Results suggest that structural factors related to race/ethnicity and employment may be major drivers of medical cannabis use, even among adults certified for its use.

Medical Marijuana and Opioids (MEMO) Study: protocol of a longitudinal cohort study to examine if medical cannabis reduces opioid use among adults with chronic pain.

INTRODUCTION: In the USA, opioid analgesic use and overdoses have increased dramatically. One rapidly expanding strategy to manage chronic pain in the context of this epidemic is medical cannabis. Cannabis has analgesic effects, but it also has potential adverse effects. Further, its impact on opioid analgesic use is not well studied. Managing pain in people living with HIV is particularly challenging, given the high prevalence of opioid analgesic and cannabis use. This study's overarching goal is to understand how medical cannabis use affects opioid analgesic use, with attention to Δ9-tetrahydrocannabinol and cannabidiol content, HIV outcomes and adverse events. METHODS AND ANALYSES: We are conducting a cohort study of 250 adults with and without HIV infection with (a) severe or chronic pain, (b) current opioid use and (c) who are newly certified for medical cannabis in New York. Over 18 months, we collect data via in-person visits every 3 months and web-based questionnaires every 2 weeks. Data sources include: questionnaires; medical, pharmacy and Prescription Monitoring Program records; urine and blood samples; and physical function tests. Using marginal structural models and comparisons within participants' 2-week time periods (unit of analysis), we will examine how medical cannabis use (primary exposure) affects (1) opioid analgesic use (primary outcome), (2) HIV outcomes (HIV viral load, CD4 count, antiretroviral adherence, HIV risk behaviours) and (3) adverse events (cannabis use disorder, illicit drug use, diversion, overdose/deaths, accidents/injuries, acute care utilisation). ETHICS AND DISSEMINATION: This study is approved by the Montefiore Medical Center/Albert Einstein College of Medicine institutional review board. Findings will be disseminated through conferences, peer-reviewed publications and meetings with medical cannabis stakeholders. TRIAL REGISTRATION NUMBER: ClinicalTrials.gov Registry (NCT03268551); Pre-results.