Investigating the association between asthma and opioid use disorder with interactions of anxiety and depression among a national sample of the US population.

INTRODUCTION: Previous studies have not examined the association between asthma and opioid use disorder (OUD) in a comprehensive national sample of the U.S. population. This study aims to investigate such an association. METHODS: This is a matched retrospective cohort study, with a follow-up period of two years, utilizing longitudinal electronic medical records of a comprehensive national healthcare database in the U.S.-Cerner-Real World DataTM. Patients selected for analysis were ≥12 years old with a hospital encounter between January 2000 and June 2020. Adjusted risk ratios (aRRs) of incident OUD for those with asthma compared to those without asthma were calculated using a modified Poisson regressions with robust standard errors via the Huber-White sandwich estimator, and results were stratified by comorbid mental illnesses. RESULTS: Individuals with asthma had a greater risk of OUD compared to those without asthma (aRR = 2.12; 95% CI 2.03-2.23). When stratified by anxiety and depression status, individuals with asthma and no anxiety or depression had a greater risk of incident OUD compared to individuals with asthma and either anxiety, depression, or both. Additionally, individuals with asthma medication had 1.29 (95% CI: 1.24, 1.35) greater overall risk for incident OUD compared to those without medication. Independent of comorbid mental illnesses, individuals with asthma medication had greater risk for incident OUD compared to those without medication among individuals without severe/obstructive asthma. CONCLUSIONS: Individuals with asthma face a higher OUD risk compared to those without asthma. Comorbid mental illnesses modulate this risk. Caution is advised in opioid prescribing for asthma patients.

The association between glucose-dependent insulinotropic polypeptide and/or glucagon-like peptide-1 receptor agonist prescriptions and substance-related outcomes in patients with opioid and alcohol use disorders: A real-world data analysis.

AIMS: This study aimed to estimate the strength of association between prescriptions of glucose-dependent insulinotropic polypeptide (GIP) and/or glucagon-like peptide-1 receptor agonists (GLP-1 RA) and the incidence of opioid overdose and alcohol intoxication in patients with opioid use disorder (OUD) and alcohol use disorder (AUD), respectively. This study also aimed to compare the strength of the GIP/GLP-1 RA and substance use-outcome association among patients with comorbid type 2 diabetes and obesity. DESIGN: A retrospective cohort study analyzing de-identified electronic health record data from the Oracle Cerner Real-World Data. SETTING: About 136 United States of America health systems, covering over 100 million patients, spanning January 2014 to September 2022. PARTICIPANTS: The study included 503 747 patients with a history of OUD and 817 309 patients with a history of AUD, aged 18 years or older. MEASUREMENTS: The exposure indicated the presence (one or more) or absence of GIP/GLP-1 RA prescriptions. The outcomes were the incidence rates of opioid overdose in the OUD cohort and alcohol intoxication in the AUD cohort. Potential confounders included comorbidities and demographic factors. FINDINGS: Patients with GIP/GLP-1 RA prescriptions demonstrated statistically significantly lower rates of opioid overdose [adjusted incidence rate ratio (aIRR) in OUD patients: 0.60; 95% confidence interval (CI) = 0.43-0.83] and alcohol intoxication (aIRR in AUD patients: 0.50; 95% CI = 0.40-0.63) compared to those without such prescriptions. When stratified by comorbid conditions, the rate of incident opioid overdose and alcohol intoxication remained similarly protective for those prescribed GIP/GLP-1 RA among patients with OUD and AUD. CONCLUSIONS: Prescriptions of glucose-dependent insulinotropic polypeptide and/or glucagon-like peptide-1 receptor agonists appear to be associated with lower rates of opioid overdose and alcohol intoxication in patients with opioid use disorder and alcohol use disorder. The protective effects are consistent across various subgroups, including patients with comorbid type 2 diabetes and obesity.

Exploring the Association Between Opioid Use Disorder and Alzheimer's Disease and Dementia Among a National Sample of the U.S. Population.

BACKGROUND: Past research suggests associations between heavy alcohol use and later life dementia. However, little is known about whether opioid use disorder (OUD) and dementia share this association, especially among age groups younger than 65 years old. OBJECTIVE: Examine the association between OUD and Alzheimer's disease (AD) and dementia. METHODS: Electronic health records between 2000 and 2021 for patients age 12 or older were identified in the Cerner Real-World database™. Patients with a prior diagnosis of dementia were excluded. Patients were followed for 1-10 years (grouped by one, three, five, and ten-year follow-up periods) in a matched retrospective cohort study. Cox proportional hazards regressions were used to estimate adjusted hazard ratios (aHRs) of incident AD/dementia stratified by age and follow-up group. RESULTS: A sample of 627,810 individuals with OUD were compared to 646,340 without OUD. Individuals with OUD exhibited 88% higher risk for developing AD/dementia compared to those without OUD (aHR = 1.88, 95% CI 1.74, 2.03) within 1 year follow-up and 211% (aHR = 3.11, 95% CI 2.63, 3.69) within 10 years follow-up. When stratifying by age, younger patients (age 12-44) had a greater disparity in odds of AD/dementia between OUD and non-OUD groups compared with patients older than 65 years. CONCLUSIONS: Additional research is needed to understand why an association exists between OUD and AD/dementia, especially among younger populations. The results suggest that cognitive functioning screening programs for younger people diagnosed with OUD may be useful for targeting early identification and intervention for AD/dementia in particularly high risk and marginalized populations.