Cocaine and Marijuana Polysubstance Use and Cocaine Use Disorder: Investigating Mediated Effects through Patterns of Cocaine Use

Identifying neurofunctional domains across substance use disorders

Background: Substance use disorders (SUDs) are heterogeneous across multiple functional domains. Various frameworks posit that domains (e.g., executive function) contribute to the persistence of SUDs; however, the domains identified in different studies vary.Objectives: We used factor analysis to identify the underlying latent domains present in a large sample (N = 5,244, 55.8% male) with a variety of SUDs to yield findings more generalizable than studies with a narrower focus.Method: Participants (1,384 controls and 3,860 participants with one or more SUDs including alcohol, cocaine, cannabis, and/or opioid use disorders) completed the Semi-Structured Assessment for Drug Dependence and Alcoholism, the NEO Personality Inventory, and the Wisconsin Card Sorting Test. Exploratory factor analysis (EFA) and fit indices (root mean-squared error of approximation (RMSEA), Comparative Fit Index (CFI), and Tucker-Lewis Index (TLI)) were used to examine different latent variable models. A multiple indicators, multiple causes (MIMIC) approach-tested associations of the latent variables with sociodemographics, substance use, and a history of abuse/neglect.Results: A six-factor model (predominant alcohol, predominant cocaine, predominant opioid, externalizing, personality, and executive function) provided the best fit [RMSEA = 0.063 (90% CI 0.060, 0.066), CFI = 0.98, TLI = 0.96]. All factors were moderately correlated (coefficient = 0.25-0.55, p < .05) with the exception of executive function. MIMIC analysis revealed different patterns of associations (all p < .0001) with sociodemographics, substance use, and a history of abuse/neglect among the factors.Conclusions: The domains identified, particularly executive function, were parallel to those observed previously. These factors underscore the heterogeneous nature of SUDs and may be useful in developing more targeted clinical interventions.

Polysubstance addiction patterns among 7,989 individuals with cocaine use disorder

To characterize polysubstance addiction (PSA) patterns of cocaine use disorder (CoUD), we performed a latent class analysis (LCA) in 7,989 participants with a lifetime DSM-5 diagnosis of CoUD. This analysis identified three PSA subgroups among CoUD participants (i.e., low, 17%; intermediate, 38%; high, 45%). While these subgroups varied by age, sex, and racial-ethnic distribution (p < 0.001), there was no difference with respect to education or income (p > 0.05). After accounting for sex, age, and race-ethnicity, the CoUD subgroup with high PSA had higher odds of antisocial personality disorder (OR = 21.96 vs. 6.39, difference-p = 8.08✕10-6), agoraphobia (OR = 4.58 vs. 2.05, difference-p = 7.04✕10-4), mixed bipolar episode (OR = 10.36 vs. 2.61, difference-p = 7.04✕10-4), posttraumatic stress disorder (OR = 11.54 vs. 5.86, difference-p = 2.67✕10-4), antidepressant medication use (OR = 13.49 vs. 8.02, difference-p = 1.42✕10-4), and sexually transmitted diseases (OR = 5.92 vs. 3.38, difference-p = 1.81✕10-5) than the low-PSA CoUD subgroup. These findings underscore the importance of modeling PSA severity and comorbidities when examining the clinical, molecular, and neuroimaging correlates of CoUD.

Substance use and medical outcomes in those age 50 and older involving cocaine and metamfetamine reported to United States poison centers

CONTEXT

Cocaine and metamfetamine use and overdose deaths among United States adults have been increasing in recent years. We examined associations of medical outcomes with co-used opioids and other substances among cocaine, and metamfetamine exposures in people age ≥50 years (N = 9300) reported to the National Poison Data System, 2015-2021.

METHODS

We first described increases in these exposures over time. We fitted generalized linear models for a Poisson distribution with a log link, one for cocaine exposures and the other for metamfetamine exposures, to examine associations of medical outcomes (major effects/death versus all others) with co-used other substances, controlling for exposure year and demographics.

RESULTS

The number of exposures increased steadily during the seven years, but metamfetamine exposures increased more rapidly starting in 2018. One-fifth of cocaine and one-sixth of metamfetamine exposures suffered major effects/death. Co-use of prescription opioids (incident risk ratio = 2.00, 95% CI = 1.76-2.28 for cocaine; incident risk ratio = 1.62, 95% CI = 1.27-2.07 for metamfetamine), illicit fentanyl (incident risk ratio =1.88, 95% CI = 1.08-3.27 for cocaine; incident risk ratio = 2.05, 95% CI = 1.04-4.06 for metamfetamine), heroin (incident risk ratio =1.62, 95% CI = 1.37-1.90 for cocaine), or amfetamine (incident risk ratio =1.73, 95% CI = 1.28-2.33 for cocaine) was associated with a higher likelihood of major effects/death.

DISCUSSION

Increases in the number of cocaine and metamfetamine exposures among older adults reported to poison centers are of concern, and so is the increased risk of major effects/death from polysubstance use, especially prescription and illicit opioids, among these illicit psychostimulant users.

CONCLUSIONS

Healthcare provider screening of individuals at risk of cocaine and/or metamfetamine use and psychoeducation about the dangers of these substance use are needed.

Polysubstance addiction and psychiatric, somatic comorbidities among 7,989 individuals with cocaine use disorder: a latent class analysis

Aims

We performed a latent class analysis (LCA) in a sample ascertained for addiction phenotypes to investigate cocaine use disorder (CoUD) subgroups related to polysubstance addiction (PSA) patterns and characterized their differences with respect to psychiatric and somatic comorbidities.

Design

Cross-sectional study.

Setting

United States.

Participants

Adult participants aged 18-76, 39% female, 47% African American, 36% European American with a lifetime DSM-5 diagnosis of CoUD (N=7,989) enrolled in the Yale-Penn cohort. The control group included 2,952 Yale-Penn participants who did not meet for alcohol, cannabis, cocaine, opioid, or tobacco use disorders.

Measurements

Psychiatric disorders and related traits were assessed via the Semi-structured Assessment for Drug Dependence and Alcoholism. These features included substance use disorders (SUD), family history of substance use, sociodemographic information, traumatic events, suicidal behaviors, psychopathology, and medical history. LCA was conducted using diagnoses and diagnostic criteria of alcohol, cannabis, opioid, and tobacco use disorders.

Findings

Our LCA identified three subgroups of PSA (i.e., low, 17%; intermediate, 38%; high, 45%) among 7,989 CoUD participants. While these subgroups varied by age, sex, and racial-ethnic distribution (p<0.001), there was no difference on education or income (p>0.05). After accounting for sex, age, and race-ethnicity, the CoUD subgroup with high PSA had higher odds of antisocial personality disorder (OR=21.96 vs. 6.39, difference-p=8.08×10 -6 ), agoraphobia (OR=4.58 vs. 2.05, difference-p=7.04×10 -4 ), mixed bipolar episode (OR=10.36 vs. 2.61, difference-p=7.04×10 -4 ), posttraumatic stress disorder (OR=11.54 vs. 5.86, difference-p=2.67×10 -4 ), antidepressant medication use (OR=13.49 vs. 8.02, difference-p=1.42×10 -4 ), and sexually transmitted diseases (OR=5.92 vs. 3.38, difference-p=1.81×10 -5 ) than the low-PSA CoUD subgroup.

Conclusions

We found different patterns of PSA in association with psychiatric and somatic comorbidities among CoUD cases within the Yale-Penn cohort. These findings underscore the importance of modeling PSA severity and comorbidities when examining the clinical, molecular, and neuroimaging correlates of CoUD.

Smoked cannabis reduces peak cocaine plasma levels and subjective effects in a controlled drug administration study of polysubstance use in men

BACKGROUND

Despite the high prevalence of polysubstance use, outcomes and potential risks associated with common drug combinations are not well characterized. Many individuals who use cocaine also use cannabis, yet little is known about how interactions between the two drugs might contribute to continued co-use.

METHODS

The aim of this double-blind, placebo-controlled study was to determine the physiological and subjective effects of smoked cannabis with smoked cocaine, to identify variables that may contribute to the continued use of this drug combination. Healthy, non-treatment seeking volunteers who reported smoking both cocaine and cannabis (N = 9, all males) completed a 13-day inpatient protocol. On session days, cannabis [0.0 or 5.6 % tetrahydrocannabinol (THC)] was administered 28 min prior to cocaine (0, 12, or 25 mg). Dependent measures included pharmacokinetic assessment of THC and cocaine and their respective metabolites, in addition to subjective and cardiovascular effects.

RESULTS

Active cannabis (5.6 % THC) increased plasma levels of THC and the metabolite 11-nor-9-carboxy-Δ9-THC (THCCOOH), as well as subjective ratings of cannabis effects and heart rate relative to inactive cannabis. Cocaine dose-dependently increased plasma cocaine and metabolites and subjective ratings of cocaine effects. Active cannabis pre-treatment decreased plasma levels of cocaine and metabolites. Furthermore, active cannabis attenuated cocaine-related reductions in 'Hunger' and 'Calm.'

CONCLUSIONS

Cannabis pre-treatment altered the subjective experience of smoked cocaine and reduced peak plasma levels of cocaine. Future studies should explore additional doses of each drug and whether these changes also impact cocaine's reinforcing effects.

Co-exposure of cocaine and cannabinoids and its association with select biological, behavioural and health outcomes: A systematic scoping review of multi-disciplinary studies

Cocaine use entails severe health- and social-related harms globally. Treatment options for cocaine dependence are highly limited. Benefits of cannabinoids for addiction have been documented, making it opportune to examine existing data on the possible outcomes associated with cannabinoids and cocaine co-use. We conducted a systematic scoping review following the PRISMA guidelines of peer-reviewed, English-language studies published from 2000 to 2021 in four databases (Medline, Web-of-Science, CINAHL Plus, and PsycInfo), assessing the co-exposure of cannabis/cannabinoids with cocaine on behavioural, biological or health outcomes. Both quantitative and qualitative, as well as humans and pre-clinical animals' studies (n=46) were included. Pre-clinical studies (n=19) showed mostly protective effects of cannabidiol (CBD) administration on animal models of addiction (e.g., cocaine-craving, -relapse, and -withdrawal) and cocaine-toxicity. Tetrahydrocannabinol (THC) had more inconsistent results, with both protective and counter-protective effects. Human studies (n=27) were more heterogeneous and assessed natural ongoing cannabis and cocaine use or dependence. Quantitative-based studies showed mostly enhanced harms in several outcomes (e.g., cocaine use, mental health); two available clinical trials found no effect upon CBD administration on cocaine-related treatment outcomes. Qualitative data-based studies reported cannabis use as a substitute for or to alleviate harms of crack-cocaine use. While pre-clinical studies suggest a potential of cannabinoids, especially CBD, to treat cocaine addiction, the few trials conducted in humans found no benefits. Cannabis co-use by cocaine users commonly presents a risk factor, entailing enhanced harms for users. More rigorous, controlled trials are still necessary to investigate cannabinoids' potential considering pre-clinical findings and reported benefits from specific drug users.

In-Treatment Changes in Quality of Life-Related Variables in Therapeutic Communities for Cocaine Abusers: Are These Changes Associated with Clinical Outcomes?

BACKGROUND

Few studies have explored changes in quality of life during the first three months of admission to a therapeutic community for addictions. The objective of this study was to determine the relationship between these changes and treatment outcomes at discharge.

METHODS

We undertook a prospective longitudinal study of 142 cocaine-dependent patients treated at a therapeutics community. All of these patients reached the 3-month evaluation and were subsequently followed until discharge. All participants completed the following measures: Health-Related Quality of Life for Drug Abusers Test; Beck Depression Inventory; State-Trait Anxiety Inventory; Opiate Treatment Index; Dual Diagnosis and Discharge Checklist.

RESULTS

At the 3-month assessment, scores on the Health-Related Quality of Life for Drug Abusers Test had increased significantly (Cohen's d: 0.92), while scores on the Opiate Treatment Index (Cohen's d: 0.86) and Beck Depression Inventory (Cohen's d: 0.20) scales both decreased significantly. A higher proportion of the patients considered to have achieved "clinically relevant" treatment outcomes at discharge versus those without clinically relevant outcomes were considered "recovered" according to the Reliable Change Index.

CONCLUSIONS

An improvement in quality of life-related variables from baseline to the 3-month assessment was associated with better outcomes at discharge from the therapeutic community. The findings of this study may help us to optimise therapeutic interventions.