Longitudinal latent polysubstance use patterns among a cohort of people who use opioids in Vancouver, Canada

Initiation and/or re-initiation of drug use among people who use drugs in Vancouver, Canada from 2021 to 2022: a prospective cohort study

OBJECTIVES

Widespread health service disruptions resulting from the COVID-19 pandemic coincided with a dramatic increase in overdose deaths among people who use drugs (PWUD) in Vancouver, Canada. Those with a history of injection drug use are known to be at heightened risk of substance-associated harms. Drug use patterns and associated sociodemographic and health care utilization trends have been understudied in this population since the pandemic onset. We sought to understand patterns of drug use initiation and/or re-initiation among people with a history of injection drug use (IVDU).

METHODS

Data were obtained from three harmonized prospective cohort studies of PWUD in Vancouver. Participants with a lifetime history of IVDU who responded to a survey between June 2021 and May 2022 were included. The primary outcome variable was a composite of substance use initiation and re-initiation over the study period, labelled as drug (re)-initiation. A multivariable generalized linear mixed-effects model was used to examine factors associated with self-reported (re)-initiation of substance use over the past six months.

RESULTS

Among 1061 participants, the median age was 47 years at baseline and 589 (55.5%) identified as men. In total, 183 (17.2%) participants reported initiating and/or re-initiating a drug, with 44 (4.1%) reporting new drug initiation and 148 (14.0%) reporting drug re-initiation (9 participants responded 'yes' to both). Overall, unregulated stimulants (e.g., crystal methamphetamine and cocaine) were the most common drug class (re-)initiated (n = 101; 55.2%), followed by opioids (n = 74; 40.4%) and psychedelics (n = 36; 19.7%). In the multivariable analysis, (re-)initiation of drug use was independently associated with recent IVDU (adjusted odds ratio [AOR] 2.62, 95% confidence interval [CI] 1.02, 6.76), incarceration (AOR 3.36, CI 1.12, 10.14) and inability to access addiction treatment (AOR 4.91, 95% CI 1.22, 19.75).

CONCLUSIONS

In an era impacted by the intersecting effects of the COVID-19 pandemic and the overdose crisis, nearly one in five PWUD with a history of IVDU began using a new drug and/or re-started use of a previous drug. Those who reported drug (re-)initiation exhibited riskier substance use behaviours and reported difficulty accessing treatment services. Our findings underscore the need to provide additional resources to support this high-risk population.

A Comparison of Veterans with Problematic Opioid Use Identified through Natural Language Processing of Clinical Notes versus Using Diagnostic Codes

Opioid use disorder is known to be under-coded as a diagnosis, yet problematic opioid use can be documented in clinical notes, which are included in electronic health records. We sought to identify problematic opioid use from a full range of clinical notes and compare the demographic and clinical characteristics of patients identified as having problematic opioid use exclusively in clinical notes to patients documented through ICD opioid use disorder diagnostic codes. We developed and applied a natural language processing (NLP) tool that combines rule-based pattern analysis and a trained support vector machine to the clinical notes of a patient cohort (n = 222,371) from two Veteran Affairs service regions to identify patients with problematic opioid use. We also used a set of ICD diagnostic codes to identify patients with opioid use disorder from the same cohort. The NLP tool achieved 96.6% specificity, 90.4% precision/PPV, 88.4% sensitivity/recall, and 94.4% accuracy on unseen test data. NLP exclusively identified 57,331 patients; 6997 patients had positive ICD code identifications. Patients exclusively identified through NLP were more likely to be women. Those identified through ICD codes were more likely to be male, younger, have concurrent benzodiazepine prescriptions, more comorbidities, and more care encounters, and were less likely to be married. Patients in both these groups had substantially elevated comorbidity levels compared with patients not documented through either method as experiencing problematic opioid use. Clinicians may be reluctant to code for opioid use disorder. It is therefore incumbent on the healthcare team to search for documentation of opioid concerns within clinical notes.

Longitudinal patterns of use of stimulants and opioids in the AIDS linked to the IntraVenous experience cohort, 2005-2019

BACKGROUND

Overdoses involving opioids and stimulants are on the rise, yet few studies have examined longitudinal trends in use of both substances. We sought to describe use and co-use of opioids and stimulants, 2005-2019, in the AIDS Linked to the Intravenous Experience (ALIVE) cohort - a community-based cohort of people with a history of injection drug use living in or near Baltimore, MD.

METHODS

We included 2083 ALIVE participants, who had at least two visits during the study period. Our outcome was based on self-reported use of opioids and stimulants in the prior 6 months. We estimated prevalence of 4 categories of use (neither stimulants nor opioids, only stimulants, only opioids, stimulants and opioids), using a non-parametric multi-state model, accounting for the competing event of death and weighting for informative loss to follow-up. All analyses were stratified by enrollment cohort, with the main analysis including participants who enrolled prior to 2015 and a sub-analysis including participants who enrolled 2015-2018.

RESULTS

In the main analysis, prevalence of using stimulants and opioids decreased from 38 % in 2005 to 12 % 2013 but stabilized from 2014 onwards (13-19 %). The prevalence of using only stimulants (7-11 %) and only opioids (5-10 %) was stable across time. Participants who reported using both were more likely to report homelessness, depression, and other substance use (e.g., marijuana and heavy alcohol use) than participants in the other use categories. On average, 65 % of visits with use of both were followed by a subsequent visit with use of both; of participants transitioning out of using both, 13% transitioned to using neither.

CONCLUSIONS

While use of stimulants and opioids declined in the cohort through 2013, a meaningful proportion of participants persistently used both. More research is needed to understand and develop strategies to mitigate harms associated with persistent use of both stimulants and opioids.

Longitudinal polysubstance use patterns and non-fatal overdose: A repeated measures latent class analysis

BACKGROUND

Polysubstance use (PSU) is common among people who use opioids (PWUO) and has been associated with drug-related harms. We aimed to identify latent longitudinal PSU classes among a cohort of PWUO and characterize non-fatal overdose risks among different sub-classes over time.

METHODS

We used longitudinal data (2005-2018) from three ongoing prospective cohorts of people who use drugs in Vancouver, Canada. The primary outcome of interest was self-reported non-fatal overdose during the past six months. The primary exposure of interest was longitudinal PSU patterns among PWUO, obtained from repeated measures latent class analysis (RMLCA) of weekly substance use-related outcome indicators. Multivariable generalized estimating equations models were built to assess the association between latent PSU class membership and non-fatal overdose, adjusting for potential sociodemographic, behavioural, and structural confounders.

RESULTS

2627 PWUO were included in the analysis, and 1094 (41.6 %) had experienced at least one non-fatal overdose during the study period. RMLCA revealed five distinct latent longitudinal PSU classes, including low/infrequent use (Class 1; 30 %), primarily opioid and methamphetamine use (Class 2; 22 %), primarily cannabis use (Class 3; 15 %), primarily opioid and crack use (Class 4; 29 %), and frequent PSU (Class 5; 4 %). In comparison with Class 1 (low), membership in all latent PSU classes except Class 3 (cannabis) was associated with increased odds of non-fatal overdose: Class 2 (opioids + meth) vs. Class 1 (Adjusted odds ratios [aOR] = 2.20, 95 % confidence intervals [CI]: 1.51-3.22), Class 4 (opioids + crack) vs. Class 1 (aOR = 1.06, 95 % CI: 0.85-1.33), and Class 5 (frequent) vs. Class 1 (aOR = 2.39, 95 % CI: 1.92-2.97).

CONCLUSION

Our findings highlighted the heterogeneous characteristics of PWUO in terms of patterns of PSU and non-fatal overdose risk. The diverse nature of PWUO and the potential additive or multiplicative impact of using several substances on overdoses should be reflected across the substance use treatment continuum and care provision.