Higher First 30-Day Dose of Buprenorphine for Opioid Use Disorder Treatment Is Associated With Decreased Mortality.

OBJECTIVE: Buprenorphine is a medication for opioid use disorder that reduces mortality. This study aims to investigate the less well-understood relationship between the dose in the early stages of treatment and the subsequent risk of death. METHODS: We used Kentucky prescription monitoring data to identify adult Kentucky residents initiating transmucosal buprenorphine medication for opioid use disorder (January 2017 to November 2019). Average daily buprenorphine dose for days covered in the first 30 days of treatment was categorized as ≤8 mg, >8 to ≤16 mg, and >16 mg. Patients were followed for 365 days after the first 30 days of buprenorphine treatment. Endpoints were opioid-involved overdose death and death from other causes. Causes and dates of death were obtained using Kentucky death certificate records. Associations were evaluated using multivariable Fine and Gray models adjusting for patient baseline characteristics. RESULTS: In the cohort of 49,857 patients, there were 227 opioid-involved overdose deaths and 459 deaths from other causes. Compared with ≤8 mg, the adjusted subdistribution hazard ratio (aSHR) of opioid-involved overdose death decreased by 55% (aSHR, 0.45; 95% confidence interval [CI], 0.34-0.60) and 64% (aSHR, 0.36; 95% CI, 0.25-0.52) for patients receiving doses of >8 to ≤16 mg and >16 mg, respectively. The incidence of death from other causes was lower in patients receiving >8 to ≤16 mg (aSHR, 0.78; 95% CI, 0.62-0.98) and >16 mg (aSHR, 0.62; 95% CI, 0.47-0.80) versus ≤8 mg dose. CONCLUSIONS: Higher first 30-day buprenorphine doses were associated with reduced opioid-involved overdose death and death from other causes, supporting benefit of higher dosing in reducing mortality.

A multi-ancestry genetic study of pain intensity in 598,339 veterans.

Chronic pain is a common problem, with more than one-fifth of adult Americans reporting pain daily or on most days. It adversely affects the quality of life and imposes substantial personal and economic costs. Efforts to treat chronic pain using opioids had a central role in precipitating the opioid crisis. Despite an estimated heritability of 25-50%, the genetic architecture of chronic pain is not well-characterized, in part because studies have largely been limited to samples of European ancestry. To help address this knowledge gap, we conducted a cross-ancestry meta-analysis of pain intensity in 598,339 participants in the Million Veteran Program, which identified 126 independent genetic loci, 69 of which are new. Pain intensity was genetically correlated with other pain phenotypes, level of substance use and substance use disorders, other psychiatric traits, education level and cognitive traits. Integration of the genome-wide association studies findings with functional genomics data shows enrichment for putatively causal genes (n = 142) and proteins (n = 14) expressed in brain tissues, specifically in GABAergic neurons. Drug repurposing analysis identified anticonvulsants, ß-blockers and calcium-channel blockers, among other drug groups, as having potential analgesic effects. Our results provide insights into key molecular contributors to the experience of pain and highlight attractive drug targets.

Development and validation of a community-level social determinants of health index for drug overdose deaths in the HEALing Communities Study.

INTRODUCTION: Social determinants of health (SDoH), such as socioeconomic status, education level, and food insecurity, are believed to influence the opioid crisis. While global SDoH indices such as the CDC's Social Vulnerability Index (SVI) and Area Deprivation Index (ADI) combine the explanatory power of multiple social factors for understanding health outcomes, they may be less applicable to the specific challenges of opioid misuse and associated outcomes. This study develops a novel index tailored to opioid misuse outcomes, tests the efficacy of this index in predicting drug overdose deaths across contexts, and compares the explanatory power of this index to other SDoH indices. METHODS: Focusing on four HEALing Communities Study (HCS) states (Kentucky, Massachusetts, New York and Ohio; encompassing 4269 ZIP codes), we identified multilevel SDoH potentially associated with opioid misuse and aggregated publicly available data for each measure. We then leveraged a random forest model to develop a composite measure that predicts age-adjusted drug overdose mortality rates based on SDoH. We used this composite measure to understand HCS and non-HCS communities in terms of overdose risk across areas of varying racial composition. Finally, we compared variance in drug overdose deaths explained by this index to variance explained by the SVI and ADI. RESULTS: Our composite measure included 28 SDoH measures and explained approximately 89 % percent of variance in age-adjusted drug overdose mortality across HCS states. Health care measures, including emergency department visits and primary care provider availability, were top predictors within the index. Index accuracy was robust within and outside of HCS communities and states. This measure identified high levels of overdose mortality risk in segregated communities. CONCLUSIONS: Existing SDoH indices fail to explain much variation in area-level overdose mortality rates. Having tailored composite indices can help us to identify places in which residents are at highest risk based on their composite contexts. A comprehensive index can also help to develop effective community interventions for programs such as HCS by considering the context in which people live.

Perceptions of community risk assessment and challenges to implementation.

Quick, easy access to data-driven community risk assessment principles and to related community risk reduction activities can encourage fire departments to learn about, conduct, and complete district risk reduction practices. With the ultimate goal of creating web-based community risk assessment and community risk reduction resources, we first evaluated fire department needs. Over an eight-month period, a quantitative online survey was administered to officers from 45 unique fire departments in 44 Kentucky counties, with follow-up qualitative telephone interviews administered to 11 fire officials. Mixed-methods, sequential analysis of the data clarified the "what," "who," and "how" of risk analysis/reduction activities, noted what specific reduction activities departments used to prepare for and mitigate risk, and named specific facilitators and barriers to risk assessment and reduction. Respondents described data use for community risk assessment and for planning community risk reduction activities; how a lack of time, personnel, and funding impacts community risk assessment and community risk reduction activities; and how to involve both firefighters and the community in the process. Innovative solutions such as a website containing resources on how to assess community risk information along with resources such as community risk assessment/ reduction education, program planning, and tools, can assist departments to use community risk assessment data in the development of community risk reduction activities.

Is There a Risk for Semaglutide Misuse? Focus on the Food and Drug Administration's FDA Adverse Events Reporting System (FAERS) Pharmacovigilance Dataset.

Recent media reports commented about a possible issue of the misuse of antidiabetics related to molecules promoted as a weight-loss treatment in non-obese people. We evaluated here available pharmacovigilance misuse/abuse signals related to semaglutide, a glucagon-like peptide-1 (GLP-1) analogue, in comparison to other GLP-1 receptor agonists (albiglutide, dulaglutide, exenatide, liraglutide, lixisenatide, and tirzepatide) and the phentermine-topiramate combination. To acheieve that aim, we analyzed the Food and Drug Administration's FDA Adverse Events Reporting System (FAERS) dataset, performing a descriptive analysis of adverse event reports (AERs) and calculating related pharmacovigilance measures, including the reporting odds ratio (ROR) and the proportional reporting ratio (PRR). During January 2018-December 2022, a total of 31,542 AERs involving the selected molecules were submitted to FAERS; most involved dulaglutide (n = 11,858; 37.6%) and semaglutide (n = 8249; 26.1%). In comparing semaglutide vs. the remaining molecules, the respective PRR values of the AERs 'drug abuse', 'drug withdrawal syndrome', 'prescription drug used without a prescription', and 'intentional product use issue' were 4.05, 4.05, 3.60, and 1.80 (all < 0.01). The same comparisons of semaglutide vs. the phentermine-topiramate combination were not associated with any significant differences. To the best of our knowledge, this is the first study documenting the misuse/abuse potential of semaglutide in comparison with other GLP1 analogues and the phentermine-topiramate combination. The current findings will need to be confirmed by further empirical investigations to fully understand the safety profile of those molecules.

Genetic Underpinnings of the Transition From Alcohol Consumption to Alcohol Use Disorder: Shared and Unique Genetic Architectures in a Cross-Ancestry Sample.

OBJECTIVE: Recent genome-wide association studies (GWASs) of alcohol-related phenotypes have uncovered key differences in the underlying genetic architectures of alcohol consumption and alcohol use disorder (AUD), with the two traits having opposite genetic correlations with psychiatric disorders. Understanding the genetic factors that underlie the transition from heavy drinking to AUD has important theoretical and clinical implications. METHODS: The authors used longitudinal data from the cross-ancestry Million Veteran Program sample to identify 1) novel loci associated with AUD and alcohol consumption (measured by the score on the consumption subscale of the Alcohol Use Disorders Identification Test [AUDIT-C]), 2) the impact of phenotypic variation on genetic discovery, and 3) genetic variants with direct effects on AUD that are not mediated through alcohol consumption. RESULTS: The authors identified 26 loci associated with AUD and 22 loci associated with AUDIT-C score, including ancestry-specific and novel loci. In secondary GWASs that excluded individuals who report abstinence, the authors identified seven additional loci for AUD and eight additional loci for AUDIT-C score. Although the heterogeneity of the abstinent group biases the GWAS findings, unique variance between alcohol consumption and disorder remained after the abstinent group was excluded. Finally, using mediation analysis, the authors identified a set of variants with effects on AUD that are not mediated through alcohol consumption. CONCLUSIONS: Differences in genetic architecture between alcohol consumption and AUD are consistent with their having different biological contributions. Genetic variants with direct effects on AUD are potentially relevant to understanding the transition from heavy alcohol consumption to AUD and may be targets for translational prevention and treatment efforts.

Racial and Ethnic Bias in the Diagnosis of Alcohol Use Disorder in Veterans.

OBJECTIVE: Studies show that racially and ethnically minoritized veterans have a higher prevalence of alcohol use disorder (AUD) than White veterans. The investigators examined whether the relationship between self-reported race and ethnicity and AUD diagnosis remains after adjusting for alcohol consumption, and if so, whether it varies by self-reported alcohol consumption. METHODS: The sample included 700,012 Black, White, and Hispanic veterans enrolled in the Million Veteran Program. Alcohol consumption was defined as an individual's maximum score on the consumption subscale of the Alcohol Use Disorders Identification Test (AUDIT-C), a screen for unhealthy alcohol use. A diagnosis of AUD, the primary outcome, was defined by the presence of relevant ICD-9 or ICD-10 codes in electronic health records. Logistic regression with interactions was used to assess the association between race and ethnicity and AUD as a function of maximum AUDIT-C score. RESULTS: Black and Hispanic veterans were more likely than White veterans to have an AUD diagnosis despite similar levels of alcohol consumption. The difference was greatest between Black and White men; at all but the lowest and highest levels of alcohol consumption, Black men had 23%-109% greater odds of an AUD diagnosis. The findings were unchanged after adjustment for alcohol consumption, alcohol-related disorders, and other potential confounders. CONCLUSIONS: The large discrepancy in the prevalence of AUD across groups despite a similar distribution of alcohol consumption levels suggests that there is racial and ethnic bias, with Black and Hispanic veterans more likely than White veterans to receive an AUD diagnosis. Efforts are needed to reduce bias in the diagnostic process to address racialized differences in AUD diagnosis.

The genetic architecture of pain intensity in a sample of 598,339 U.S. veterans.

Chronic pain is a common problem, with more than one-fifth of adult Americans reporting pain daily or on most days. It adversely affects quality of life and imposes substantial personal and economic costs. Efforts to treat chronic pain using opioids played a central role in precipitating the opioid crisis. Despite an estimated heritability of 25-50%, the genetic architecture of chronic pain is not well characterized, in part because studies have largely been limited to samples of European ancestry. To help address this knowledge gap, we conducted a cross-ancestry meta-analysis of pain intensity in 598,339 participants in the Million Veteran Program, which identified 125 independent genetic loci, 82 of which are novel. Pain intensity was genetically correlated with other pain phenotypes, level of substance use and substance use disorders, other psychiatric traits, education level, and cognitive traits. Integration of the GWAS findings with functional genomics data shows enrichment for putatively causal genes (n = 142) and proteins (n = 14) expressed in brain tissues, specifically in GABAergic neurons. Drug repurposing analysis identified anticonvulsants, beta-blockers, and calcium-channel blockers, among other drug groups, as having potential analgesic effects. Our results provide insights into key molecular contributors to the experience of pain and highlight attractive drug targets.

Detecting Tweets Containing Cannabidiol-Related COVID-19 Misinformation Using Transformer Language Models and Warning Letters From Food and Drug Administration: Content Analysis and Identification.

Background: COVID-19 has introduced yet another opportunity to web-based sellers of loosely regulated substances, such as cannabidiol (CBD), to promote sales under false pretenses of curing the disease. Therefore, it has become necessary to innovate ways to identify such instances of misinformation. Objective: We sought to identify COVID-19 misinformation as it relates to the sales or promotion of CBD and used transformer-based language models to identify tweets semantically similar to quotes taken from known instances of misinformation. In this case, the known misinformation was the publicly available Warning Letters from Food and Drug Administration (FDA). Methods: We collected tweets using CBD- and COVID-19-related terms. Using a previously trained model, we extracted the tweets indicating commercialization and sales of CBD and annotated those containing COVID-19 misinformation according to the FDA definitions. We encoded the collection of tweets and misinformation quotes into sentence vectors and then calculated the cosine similarity between each quote and each tweet. This allowed us to establish a threshold to identify tweets that were making false claims regarding CBD and COVID-19 while minimizing the instances of false positives. Results: We demonstrated that by using quotes taken from Warning Letters issued by FDA to perpetrators of similar misinformation, we can identify semantically similar tweets that also contain misinformation. This was accomplished by identifying a cosine distance threshold between the sentence vectors of the Warning Letters and tweets. Conclusions: This research shows that commercial CBD or COVID-19 misinformation can potentially be identified and curbed using transformer-based language models and known prior instances of misinformation. Our approach functions without the need for labeled data, potentially reducing the time at which misinformation can be identified. Our approach shows promise in that it is easily adapted to identify other forms of misinformation related to loosely regulated substances.

Changes in transmucosal buprenorphine utilization for opioid use disorder treatment during the COVID-19 pandemic in Kentucky.

PURPOSE: With surging opioid-involved overdoses, maintaining access to opioid use disorder (OUD) treatment is critical during the COVID-19 pandemic. We examined changes in transmucosal buprenorphine prescribing for OUD treatment in Kentucky after the national COVID-19 emergency declaration, with a focus on rural-urban differences. METHODS: Using 2019-2020 prescription monitoring data, we performed segmented regression analysis for an interrupted time series design to evaluate changes in weekly rates (per 100,000 residents) of dispensed prescriptions, unique individuals with dispensed prescriptions, and average days' supply for dispensed prescriptions of transmucosal buprenorphine. FINDINGS: The weekly rates of dispensed prescriptions and unique individuals with dispensed prescriptions were higher for rural residents than urban residents. After the national COVID-19 emergency declaration, rural and urban residents experienced similar immediate drops in the rate of dispensed prescriptions (rural -33.4; urban -24.3) and unique patients with dispensed prescriptions (rural -25.0; urban -17.1), followed by similar sustained increases. Both measures surpassed the prepandemic levels in mid-June 2020. Patients residing in urban areas received averagely longer prescriptions at baseline (urban: 11.0 days; rural: 10.5 days). The average weekly days' supply increased in the week after the national emergency declaration, but the estimated increase was higher (P = .004) for urban (0.8 days) versus rural (0.5 days) residents. CONCLUSIONS: Transmucosal buprenorphine utilization increased during the COVID-19 pandemic after experiencing interruption during the initial weeks of the pandemic. Future studies should evaluate the contribution of the relaxed telemedicine buprenorphine prescribing regulations during the COVID-19 national emergency on initiation and maintenance of buprenorphine treatment.

Cannabinoid Poisoning-Related Emergency Department Visits and Inpatient Hospitalizations in Kentucky, 2017 to 2019.

Background and objectives: Cannabis is the most used federally illicit substance. Due to widespread medicinal use and state-level legalization, public perceptions of cannabis have shifted toward the assumption that cannabis is safe. However, cannabinoids can cause adverse medical complications that may lead people to seek treatment. This study characterized cannabinoid poisoning-related medical encounters, poisoning involving cannabinoids and other psychoactive substances, and cannabinoid poisoning-related cardiac complications. Methods: Administrative billing data for emergency department visits and inpatient hospitalizations in acute care facilities with a discharge date from January 1, 2017 to December 31, 2019 were used to characterize cannabinoid poisoning events in Kentucky, identified by ICD-10-CM diagnosis code T40.7X. Results: There were 1,490 encounters of cannabinoid poisoning; patients were primarily non-Hispanic White males, ages 15-44, who had Medicaid and lived in a metropolitan area. Of those, 31.21% involved poisoning with a second psychoactive substance, primarily stimulants and/or opioids, and 17.72% experienced a cardiac complication. Cannabinoid-polydrug poisoning was associated with inpatient treatment (χ2=199.18, p < 0.001) and cardiac complications (χ2=4.58, p < 0.001). Discussion and Conclusions: These results are consistent with other state-level data. Patients who were diagnosed with cannabis-polydrug poisoning, compared to cannabis alone poisoning, had greater odds of hospital admission and cardiac complications, and longer length of hospital stays. Scientific Significance: The health risks of cannabinoid use must be more broadly recognized, while timely and accurate data need to be shared to guide policies on cannabis access. Future research on cannabinoid poisoning should consider the involvement of other psychoactive drugs.

Cross-ancestry meta-analysis of opioid use disorder uncovers novel loci with predominant effects in brain regions associated with addiction.

Despite an estimated heritability of ~50%, genome-wide association studies of opioid use disorder (OUD) have revealed few genome-wide significant loci. We conducted a cross-ancestry meta-analysis of OUD in the Million Veteran Program (N = 425,944). In addition to known exonic variants in OPRM1 and FURIN, we identified intronic variants in RABEPK, FBXW4, NCAM1 and KCNN1. A meta-analysis including other datasets identified a locus in TSNARE1. In total, we identified 14 loci for OUD, 12 of which are novel. Significant genetic correlations were identified for 127 traits, including psychiatric disorders and other substance use-related traits. The only significantly enriched cell-type group was CNS, with gene expression enrichment in brain regions previously associated with substance use disorders. These findings increase our understanding of the biological basis of OUD and provide further evidence that it is a brain disease, which may help to reduce stigma and inform efforts to address the opioid epidemic.

Pharmacovigilance Signals of the Opioid Epidemic over 10 Years: Data Mining Methods in the Analysis of Pharmacovigilance Datasets Collecting Adverse Drug Reactions (ADRs) Reported to EudraVigilance (EV) and the FDA Adverse Event Reporting System (FAERS).

In the past twenty years, the consumption of opioid medications has reached significant proportions, leading to a rise in drug misuse and abuse and increased opioid dependence and related fatalities. Thus, the purpose of this study was to determine whether there are pharmacovigilance signals of abuse, misuse, and dependence and their nature for the following prescription opioids: codeine, dihydrocodeine, fentanyl, oxycodone, pentazocine, and tramadol. Both the pharmacovigilance datasets EudraVigilance (EV) and the FDA Adverse Events Reporting System (FAERS) were analyzed to identify and describe possible misuse-/abuse-/dependence-related issues. A descriptive analysis of the selected Adverse Drug Reactions (ADRs) was performed, and pharmacovigilance signal measures (i.e., reporting odds ratio, proportional reporting ratio, information component, and empirical Bayesian geometric mean) were computed for preferred terms (PTs) of abuse, misuse, dependence, and withdrawal, as well as PTs eventually related to them (e.g., aggression). From 2003 to 2018, there was an increase in ADR reports for the selected opioids in both datasets. Overall, 16,506 and 130,293 individual ADRs for the selected opioids were submitted to EV and FAERS, respectively. Compared with other opioids, abuse concerns were mostly recorded in relation to fentanyl and oxycodone, while tramadol and oxycodone were more strongly associated with drug dependence and withdrawal. Benzodiazepines, antidepressants, other opioids, antihistamines, recreational drugs (e.g., cocaine and alcohol), and several new psychoactive substances, including mitragynine and cathinones, were the most commonly reported concomitant drugs. ADRs reports in pharmacovigilance databases confirmed the availability of data on the abuse and dependence of prescription opioids and should be considered a resource for monitoring and preventing such issues. Psychiatrists and clinicians prescribing opioids should be aware of their misuse and dependence liability and effects that may accompany their use, especially together with concomitant drugs.

A Focus on Abuse/Misuse and Withdrawal Issues with Selective Serotonin Reuptake Inhibitors (SSRIs): Analysis of Both the European EMA and the US FAERS Pharmacovigilance Databases.

Despite increasing reports, antidepressant (AD) misuse and dependence remain underestimated issues, possibly due to limited epidemiological and pharmacovigilance evidence. Thus, here we aimed to determine available pharmacovigilance misuse/abuse/dependence/withdrawal signals relating to the Selective Serotonin Reuptake Inhibitors (SSRI) citalopram, escitalopram, paroxetine, fluoxetine, and sertraline. Both EudraVigilance (EV) and Food and Drug Administration-FDA Adverse Events Reporting System (FAERS) datasets were analysed to identify AD misuse/abuse/dependence/withdrawal issues. A descriptive analysis was performed; moreover, pharmacovigilance measures, including the reporting odds ratio (ROR), the proportional reporting ratio (PRR), the information component (IC), and the empirical Bayesian geometric mean (EBGM) were calculated. Both datasets showed increasing trends of yearly reporting and similar signals regarding abuse and dependence. From the EV, a total of 5335 individual ADR reports were analysed, of which 30% corresponded to paroxetine (n = 1592), 27% citalopram (n = 1419), 22% sertraline (n = 1149), 14% fluoxetine (n = 771), and 8% escitalopram (n = 404). From FAERS, a total of 144,395 individual ADR reports were analysed, of which 27% were related to paroxetine, 27% sertraline, 18% citalopram, 16% fluoxetine, and 13% escitalopram. Comparing SSRIs, the EV misuse/abuse-related ADRs were mostly recorded for citalopram, fluoxetine, and sertraline; conversely, dependence was mostly associated with paroxetine, and withdrawal to escitalopram. Similarly, in the FAERS dataset, dependence/withdrawal-related signals were more frequently reported for paroxetine. Although SSRIs are considered non-addictive pharmacological agents, a range of proper withdrawal symptoms can occur well after discontinuation, especially with paroxetine. Prescribers should be aware of the potential for dependence and withdrawal associated with SSRIs.

Self-Reported Cannabis Use and HIV Viral Control among Patients with HIV Engaged in Care: Results from a National Cohort Study.

Background: The association between cannabis use and HIV-1 RNA (viral load) among people with HIV (PWH) engaged in care is unclear. Methods: We used data collected from 2002 to 2018 on PWH receiving antiretroviral therapy (ART) enrolled in the Veterans Aging Cohort Study. Generalized estimating equations were used to estimate associations between self-reported past-year cannabis use and detectable viral load (≥500 copies/mL), with and without adjustment for demographics, other substance use, and adherence. Results: Among 2515 participants, 97% were male, 66% were Black, the mean age was 50 years, and 33% had detectable HIV viral load at the first study visit. In unadjusted analyses, PWH with any past-year cannabis use had 21% higher odds of a detectable viral load than those with no past-year use (OR = 1.21; 95% CI, 1.07-1.37). However, there was no significant association between cannabis use and viral load after adjustment. Conclusions: Among PWH engaged in care and receiving ART, cannabis use is associated with decreased adherence in unadjusted analyses but does not appear to directly impact viral control. Future studies are needed to understand other potential risks and benefits of cannabis use among PWH.

Longitudinal analysis of the prevalence and correlates of heavy episodic drinking and self-reported opioid use among a national cohort of patients with HIV.

BACKGROUND: Heavy episodic drinking (HED) is a risk factor for opioid-related overdose and negatively impacts HIV disease progression. Among a national cohort of patients with HIV (PWH), we examined sociodemographic and clinical correlates of concomitant HED and self-reported opioid use. METHODS: We used data collected from 2002 through 2018 from the Veterans Aging Cohort Study, a prospective cohort including PWH in care at eight US Veterans Health Administration sites. HED was defined as consuming six or more drinks at least once in the year prior to survey collection. We examined the relationship between HED and self-reported opioid use and created a 4-level composite variable of HED and opioid use. We used multinomial logistic regression to estimate odds of reporting concomitant HED and self-reported opioid use. RESULTS: Among 3702 PWH, 1458 (39.4%) reported HED during the study period and 350 (9.5%) reported opioid use. In the multinomial model, compared to reporting neither HED nor opioid use, lifetime housing instability (adjusted odds ratio [aOR] 1.54, 95% confidence interval [CI] 1.01 to 2.35), Veterans Aging Cohort Study Index 2.0 (a measure of disease severity; aOR 1.14, 95% CI 1.02 to 1.28), depressive symptoms (aOR 2.27, 95% CI 1.42 to 3.62), past-year cigarette smoking (aOR 3.06, 95% CI 1.53 to 6.14), cannabis use (aOR 1.69, 95% CI 1.09 to 2.62), and cocaine/stimulant use (aOR 11.54, 95% CI 7.40 to 17.99) were independently associated with greater odds of concomitant HED and self-reported opioid use. Compared to having attended no college, having some college or more (aOR 0.39, 95% CI 0.26 to 0.59) was associated with lower odds of concomitant HED and self-reported opioid use. CONCLUSIONS: Among PWH, concomitant HED and self-reported opioid use are more common among individuals with depressive symptoms and substance use, structural vulnerabilities, and greater illness severity. Efforts to minimize opioid-related risk should address high-risk drinking as a modifiable risk factor for harm among these groups.

Sociodemographic and clinical correlates of gabapentin receipt with and without opioids among a national cohort of patients with HIV.

Gabapentin is commonly prescribed for chronic pain, including to patients with HIV (PWH). There is growing concern regarding gabapentin's potential for harm, particularly in combination with opioids. Among PWH, we examined factors associated with higher doses of gabapentin receipt and determined if receipt varied by opioid use. We examined data from the Veterans Aging Cohort Study, a national prospective cohort including PWH, from 2002 through 2017. Covariates included prescribed opioid dose, self-reported past year opioid use, and other sociodemographic and clinical variables. We used multinomial logistic regression to determine independent predictors of gabapentin receipt. Among 3,702 PWH, 902 (24%) received any gabapentin during the study period at a mean daily dose of 1,469 mg. In the multinomial model, high-dose gabapentin receipt was associated with high-dose benzodiazepine receipt (adjusted odds ratio [aOR], 95% confidence interval [CI]= 1.53, [1.03-2.27]), pain interference (1.65 [1.39-1.95]), and hand or foot pain (1.81, [1.45-2.26]). High-dose gabapentin receipt was associated with prescribed high-dose opioids receipt (2.66 [1.95-3.62]) but not self-reported opioid use (1.03 [0.89-1.21]). PWH prescribed gabapentin at higher doses are more likely to receive high-dose opioids and high-dose benzodiazepines, raising safety concerns.

Cannabis use, pain interference, and prescription opioid receipt among persons with HIV: a target trial emulation study.

Concomitant with expanded legalization, cannabis is increasingly used to treat chronic pain among persons with HIV (PWH), despite equivocal benefit in research limited by small sample sizes and short duration of follow-up. To address these limitations, among a sample of PWH with pain interference enrolled in the Veterans Aging Cohort Study, we performed a target trial emulation study to compare the impact of four cannabis use strategies on pain interference. Among those receiving long-term opioid therapy (LTOT), we also explored impact of these strategies on ≥ 25% LTOT dose reduction. Among the analytic sample (N = 1284), the majority were men with a mean age of 50. Approximately 31% used cannabis and 12% received LTOT at baseline. Adjusting for demographic and clinical factors, cannabis use in any of 4 longitudinal patterns was not associated with resolved pain interference over 12- to 24-month follow-up. Among 153 participants receiving LTOT at baseline, cannabis use at both baseline and follow-up was negatively associated with LTOT dose reduction compared to no use at both baseline and follow-up. These findings support other observational studies finding no association between cannabis use and improved chronic pain or LTOT reduction among PWH.