Abstinence phenomena of chronic cannabis-addicts prospectively monitored during controlled inpatient detoxification: cannabis withdrawal syndrome and its correlation with delta-9-tetrahydrocannabinol and -metabolites in serum

Cannabis Use Cessation and the Risk of Psychotic Disorders: A Case-Control Analysis from the First Episode Case-Control EU-GEI WP2 Study: L'arrêt de l'utilisation du cannabis et le risque de troubles psychotiques: Une analyse cas-témoins tirée de l'étude cas-témoins EU-GEI WP2 centrée sur les premiers épisodes psychotiques

OBJECTIVES

To establish whether the risk of psychotic disorders in cannabis users changes with time following cannabis cessation using data from the European Network of National Networks studying Gene-Environment Interactions in Schizophrenia (EU-GEI) case-control study.

METHODS

The EU-GEI case-control study collected data from first episode psychosis patients and population controls across sites in Europe and Brazil between May 2010 and April 2015. Adjusted logistic regressions were applied to examine whether the odd of psychosis case status changed: (1) with time following cannabis cessation and (2) across different cannabis use groups.

RESULTS

Psychosis risk declined following cessation of cannabis use (β = -0.002; 95% CI -0.004 to 0.000; P = 0.067). When accounting for duration of use, this effect remained (β = -0.003; 95% CI -0.005 to -0.001; P = 0.013). However, in models adjusting for frequency and potency of use the result was not significant. Analysis of different cannabis use groups indicated that ex-users who stopped 1 to 4 weeks previously had the highest risk for psychotic disorder compared to never users (OR = 6.89; 95% CI 3.91-12.14; P < 0.001); risk declined for those who stopped 5 to 12 weeks previously (OR = 2.70; 95% CI 1.73-4.21; P < 0.001) and 13 to 36 weeks previously (OR = 1.53; 95% CI 1.00-2.33; P = 0.050). Ex-users who stopped 37 to 96 weeks (OR = 1.01; 95% CI 0.66-1.57; P = 0.949), 97 to 180 weeks (OR = 0.73; 95% CI 0.45-1.19; P = 0.204), and 181 weeks previously or more (OR = 1.18; 95% CI 0.76-1.83; P = 0.456) had similar psychosis risk to those who had never-used cannabis.

CONCLUSION

Risk of psychotic disorder appears to decline with time following cannabis cessation, receding to that of those who have never used cannabis after 37 weeks or more of abstinence. Although, preliminary results suggest that frequent users of high potency types of cannabis might maintain an elevated risk compared to never users even when abstaining for longer than 181 weeks.

Patterns of Use and Withdrawal Syndrome in Dual Cannabis and Tobacco Users (DuCATA_GAM-CAT): Protocol for a Mixed Methods Study

BACKGROUND

Approximately 1 in 6 cannabis users develop a cannabis use disorder (CUD) and the odds increase to 1 in 2 for daily users.

OBJECTIVE

The Dual use of Cannabis and Tobacco Monitoreing through a Gamified Web app (DuCATA_GAM-CaT) project aims to identify cannabis-tobacco patterns of use and withdrawal symptoms among individuals with CUD who are attending substance abuse programs.

METHODS

The project uses a mixed methods approach consisting of 3 studies. First, a participatory qualitative study involves focus groups comprising individuals with CUD, clinicians, project researchers, and an expert gamification company to co-design a gamified web app. Second, a longitudinal prospective study to follow up individuals over 6 weeks with CUD attending substance abuse programs . Participants report their cannabis-tobacco usage patterns, type and frequency of tobacco use, nicotine dependence, withdrawal symptoms, psychoemotional factors, and motivation to quit both substances. Predictive analysis techniques are used to analyze clinical, demographic, psychological, and environmental data to predict the probability of achieving abstinence. Third, homogeneous focus groups to explore participants' experiences during their CUD treatment.

RESULTS

By June 2024, the project had completed the first study, defining eligible cannabis user profiles, developed the initial web app prototype, and initiated recruitment across 10 centers, with 74 participants enrolled, aiming to reach 150 participants in total.

CONCLUSIONS

All participants are required to provide informed consent, and their information is kept confidential and anonymized following confidentiality rules. The research team is committed to disseminating the results obtained to professional and patient groups, as well as informing public health agents, to positively influence political and social decision makers and design programmers. Additionally, we aim to prioritize the publication of the results in high-impact journals specialized in drug abuse, public health, and health care services research.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05512091; https://clinicaltrials.gov/study/NCT05512091.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/58335.

Exploratory Growth Mixture Modeling of Cannabis-Withdrawal Syndrome Trajectories of Adult Pure Cannabis Dependents During Detoxification: Two Subtypes?

As clinical studies about subtypes of the cannabis withdrawal syndrome (CWS) are scant, we performed a re-analysis of longitudinal data with German adult cannabis-users seeking inpatient cannabis detoxification-treatment. Sixty-seven cannabis-dependents without active comorbidity were included for growth-mixture-analysis (GMM) of their CWS-severity-trajectories during a scheduled 24-day detox-treatment. As of treatment-day 12, thirty-six (53.7%) of 67 patients were discharged after successful detoxification. This led to artificial imputations for I-GMM. Therefore, we preferred the results of the GMM including raw data-only (R-GMM). By both, I-GMM and R-GMM, we found two classes of CWS severity time-courses. Class one (n = 44, R-GMM) showed a continuously decreasing CWS-severity; class two (n = 23, R-GMM) exhibited a sharp peak (generally between days 2-6 post-cessation). A short inpatient treatment-period and low urinary 11-nor-9-carboxy-Δ9 -tetrahydrocannabinol-level upon admission predicted the peaking trajectory of R-GMM-class-two-CWS. Withdrawal syndrome medication (PRN), comorbidity, cannabis-history data and gender balance were not significantly different between the CWS-classes. Although possibly confounded by PRN-medication, this exploratory study supports the presence of two CWS-variants in adult cannabis-dependents, characterized by a slowly decreasing ("protracted") slope (class one) or a clear crescendo-decrescendo trajectory (class two). The latter was associated with a significantly shorter inpatient detoxification period and lower urinary THC-COOH-levels at admission.

A narrative review of outcome measures used in drug and alcohol inpatient withdrawal treatment research

ISSUES

Assessing drug and alcohol inpatient withdrawal treatment programs is important, as these represent a first step of treatment among people with alcohol and drug problems. However, there are many ways of measuring outcomes making it difficult for service providers to decide which domains and methods to use. This narrative review aims to clarify frequencies of the domains and methods used to assess withdrawal treatment outcomes.

APPROACH

We reviewed published studies that examined outcomes of inpatient drug and alcohol withdrawal treatment. The types of outcome measures used and the frequency of use were summarised.

KEY FINDINGS

The review showed that assessment of withdrawal treatment outcomes goes beyond traditional abstinence measures. Outcomes mainly focus on biological and psychological outcomes, with social outcomes rarely measured. Even within outcome domains (e.g., cravings), there were many assessment methods.

IMPLICATIONS

The review provides service providers with an outline of common outcome domains and measures. Given the importance of social functioning to recovery from alcohol and drug problems, greater emphasis on such measures is desirable. Future research could develop greater consensus on outcome measures for use in withdrawal management services to facilitate clarity around factors associated with treatment success.

CONCLUSION

Outcome assessment in withdrawal treatment goes beyond abstinence to include holistic measurement of biological, psychological and some social outcomes; but more work needs to be done to cohere the different assessment methods and broaden the scope to include social functioning.

Long-Term Frequent Cannabis Use and Related Serum Cannabinoid Levels Are Not Associated with Kidney Dysfunction

Introduction: Human studies about the impact of cannabis use on both healthy kidneys as well as kidney function in patients with kidney disease are lacking. To shed more light on this understudied topic, we reevaluated a previous clinical study. The sample of this study was exclusively suited for investigating effects of recreational long-term cannabis use on humans under real-life conditions. Methods: This special sample had sought and was undergoing inpatient detox-treatment. It was characterized by a lone and considerable cannabis-dependence without any other relevant active comorbidity (except of a concurrent nicotine-dependence). In the present post hoc analysis, we are focused on this sample's routine laboratory tests at admission, including the glomerular filtration rate (GFR), which is the key routine parameter for kidney function assessment. Next, we investigated the association between participants' GFR and their cannabis-related data, including serum cannabinoid levels (Δ-9-tetrahydrocannabinol and main metabolites 11-Hydroxy-Δ-9-tetrahydrocannabinol and 11-Nor-9-carboxy-Δ-9-tetrahydrocannabinol). Results: In the whole sample (N=42; 9 females; mean 28.7 years old), we found five persons (12%; 95% confidence interval [2.1-21.7%]) with a mild kidney dysfunction (GFR; 86-75 mL/min). These persons (two females), however, had reported a stronger nicotine misuse. Furthermore, we found no significant association between the study-populations' GFR and reported cannabis burden (median daily use 2.5 g for 36 months, moderate general symptom-load). Most remarkably, the GFR was also not significantly correlated with the serum cannabinoid-levels. Conclusion: Chronic recreational cannabis-use (including its related discomfort) did not affect the kidney function of our almost selectively "cannabis-burdened" population in a relevant manner.

Is the Urine Cannabinoid Level Measured via a Commercial Point-of-Care Semiquantitative Immunoassay a Cannabis Withdrawal Syndrome Severity Predictor?

Background: For cannabis-dependent subjects, the relationship between cannabis withdrawal syndrome (CWS) severity and the urine cannabinoid concentrations are unclear; we investigated this using a commercial point-of-care (POC) enzyme immunoassay detecting 11-nor-9-carboxy-Delta-9-tetrahydrocannabinol (THC-COOH). Methods: Observational study of 78 adult chronic cannabis-dependent subjects assessed over a 24-day inpatient detoxification treatment, with 13 serial measurement days. Repeated Measures Correlation and Multilevel Linear Models were employed. Results: Absolute urinary THC-COOH levels significantly correlated with Marijuana Withdrawal Checklist (MWC) scores across the entire study duration (r = 0.248; p < 0.001). Correlation between serial creatinine-adjusted THC-COOH ratios and serial MWC scores emerged as significant only in the sample with higher MWC scores (>11 points) at admission (n = 21; r = 0.247; p = 0.002). The aforementioned significant relationships have persisted when replacing the absolute THC-COOH-levels with the (relative) day-to-day change in urinary THC-COOH levels. MWC scores were significantly correlated with the Clinical Global Impression-Severity (CGI-S; r = 0.812; p < 0.001). Females showed a significantly slower decline in urine THC-COOH levels and prolonged CWS course characterized by substantial illness severity (per CGI-S), occurring in nearly 30% of cases. Conclusion: Urine cannabinoid levels (THC-COOH) determined by POC assay significantly predicted CWS severity (moderate correlation), guiding detoxification treatment duration. In patients with MWC > 11 points upon admission, creatinine-adjusted THC-COOH ratios also significantly predicted CWS severity-again with moderate effect size. Females showed prolonged urinary THC-COOH elimination and cannabis withdrawal.

Prevalence of Cannabis Withdrawal Symptoms Among People With Regular or Dependent Use of Cannabinoids: A Systematic Review and Meta-analysis

IMPORTANCE

Cannabis withdrawal syndrome (CWS)-a diagnostic indicator of cannabis use disorder-commonly occurs on cessation of heavy and prolonged cannabis use. To date, the prevalence of CWS syndrome has not been well described, nor have the factors potentially associated with CWS.

OBJECTIVES

To estimate the prevalence of CWS among individuals with regular or dependent use of cannabinoids and identify factors associated with CWS.

DATA SOURCES

A search of literature from database inception to June 19, 2019, was performed using MEDLINE, Embase, PsycINFO, Web of Science, the Cumulative Index to Nursing and Allied Health Literature, ProQuest, Allied and Complementary Medicine, and Psychiatry online, supplemented by manual searches of reference lists of included articles.

STUDY SELECTION

Articles were included if they (1) were published in English, (2) reported on individuals with regular use of cannabinoids or cannabis use disorder as a primary study group, (3) reported on the prevalence of CWS or CWS symptoms using a validated instrument, (4) reported the prevalence of CWS, and (5) used an observational study design (eg, cohort or cross-sectional).

DATA EXTRACTION AND SYNTHESIS

All abstracts, full-text articles, and other sources were reviewed, with data extracted in duplicate. Cannabis withdrawal syndrome prevalence was estimated using a random-effects meta-analysis model, alongside stratification and meta-regression to characterize heterogeneity.

MAIN OUTCOMES AND MEASURES

Cannabis withdrawal syndrome prevalence was reported as a percentage with 95% CIs.

RESULTS

Of 3848 unique abstracts, 86 were selected for full-text review, and 47 studies, representing 23 518 participants, met all inclusion criteria. Of 23 518 participants included in the analysis, 16 839 were white (72%) and 14 387 were men (69%); median (SD) age was 29.9 (9.0) years. The overall pooled prevalence of CWS was 47% (6469 of 23 518) (95% CI, 41%-52%), with significant heterogeneity between estimates (I2 = 99.2%). When stratified by source, the prevalence of CWS was 17% (95% CI, 13%-21%) in population-based samples, 54% in outpatient samples (95% CI, 48%-59%), and 87% in inpatient samples (95% CI, 79%-94%), which were significantly different (P < .001). Concurrent cannabis (β = 0.005, P < .001), tobacco (β = 0.002, P = .02), and other substance use disorders (β = 0.003, P = .05) were associated with a higher CWS prevalence, as was daily cannabis use (β = 0.004, P < .001).

CONCLUSIONS AND RELEVANCE

These findings suggest that cannabis withdrawal syndrome appears to be prevalent among regular users of cannabis. Clinicians should be aware of the prevalence of CWS in order to counsel patients and support individuals who are reducing their use of cannabis.

Bidirectional Longitudinal Associations Between Cannabis Use and Body Mass Index Among Adolescents

Introduction: Literature on the association between cannabis use and body mass index (BMI) among adults suggests that greater cannabis use is associated with a lower BMI. However, results are mixed among adolescents, with both cross-sectional and longitudinal studies finding positive, negative, and nonsignificant associations between cannabis use and BMI. This longitudinal study aims to shed light on these associations by prospectively examining the associations between cannabis use and BMI across a 2-year window in a large sample of adolescent cannabis users. Methods: Participants were 401 adolescents ages 14-17 at baseline who were at risk for escalation in their use of cannabis. We conducted a parallel process latent growth curve model to examine associations between the cannabis use intercept, BMI intercept, cannabis use slope, and BMI slope. Results: Results showed that baseline BMI predicted a positive and significant association with cannabis use slope. In addition, there was a significant and negative correlation between the cannabis use slope and the BMI slope. These significant associations remained after controlling for relevant covariates. Conclusions: Results are consistent with the adult literature that reports a negative association between cannabis use and BMI. Future research should focus on uncovering the mechanisms that may drive the association between cannabis use and BMI.

Prospects for the Use of Cannabinoids in Oncology and Palliative Care Practice: A Review of the Evidence

There is an increased interest in the use of cannabinoids in the treatment of symptoms in cancer and palliative care patients. Their multimodal action, in spite of limited efficacy, may make them an attractive alternative, particularly in patients with multiple concomitant symptoms of mild and moderate intensity. There is evidence to indicate cannabis in the treatment of pain, spasticity, seizures, sleep disorders, nausea and vomiting, and Tourette syndrome. Although the effectiveness of cannabinoids is limited, it was confirmed in neuropathic pain management and combination with opioids. A relatively favorable adverse effects profile, including no depressive effect on the respiratory system, may make cannabis complement a rather narrow armamentarium that is in the disposition of a palliative care professional.

What do we know about the pharmacotheraputic management of insomnia in cannabis withdrawal: A systematic review

BACKGROUND AND OBJECTIVES

Sleep disturbance is one of the hallmarks of cannabis withdrawal. Studies have indicated that treatment of this key symptom may facilitate abstinence. In the present paper we aim to provide a systematic review of the extant literature on pharmacological management of sleep disturbance associated with cannabis withdrawal.

METHOD

We conducted a systematic literature search across five electronic databases including PubMed, Psycinfo, MEDLINE, Cochrane review and Embase. Human studies using a pharmacological treatment for sleep disturbances associated with cannabis withdrawal were included. Review articles, case-series, open trials, posters, and editorials were excluded.

RESULTS

Seventeen publications, involving 562 participants, were included in this review. Major limitations involved small sample size, high dropout rate, methodological limitations, and heterogeneity of participants. Most of the studies were at high risk of bias, further downgrading the level of evidence. A meta-analysis was not performed due to lack of quantitative data, marked heterogeneity and low quality of the included studies.

CONCLUSION

There is not sufficient evidence for any of the reviewed treatment options. Methodological limitations in a majority of the studies rendered their findings preliminary. Of the twelve investigated pharmacological agents, Gabapentin, Lofexidine, Mirtazapine, Quetiapine, and Zolpidem showed some primary benefits for treatment of sleep difficulties associated with cannabis withdrawal; however, future prospective studies are required to confirm such results.

SCIENTIFIC SIGNIFICANCE

This review examines the current evidence for potential pharmacological options for treatment of cannabis withdrawal and associated sleep disturbance. It furthers our knowledge and provides groundwork for future research. (Am J Addict 2018;27:453-464).

Long-Term Heavy Recreational Cannabis Use and Serum Delta-9-Tetrahydrocannabinol Levels are not Associated with an Impaired Liver Function in Cannabis Dependents

To shed more light on the influence of chronic cannabis use on liver function, we performed a post-hoc analysis of routine lab data of 42 inpatient treatment-seeking (9 female, median: 27 years old) pure cannabis dependents. Serum liver function tests (LFT: transaminases, bilirubin), C-reactive protein (CRP), carbohydrate-deficient transferrin (CDT), and body mass index (BMI) were considered. The LFT were correlated with CDT, BMI, and cannabis-related clinical data (CR); i.e., the serum levels of delta-9-tetrahydrocannabinol (THC) and its major metabolites 11-hydroxy-delta-9-tetrahydrocannabinol (THC-OH) and 11-nor-delta-9-tetrahydrocannabinol-9-carboxylic acid (THC-COOH), plus the cannabis-history data. The LFT was normal in 32 (76.2%) patients. There was no significant association of LFT with BMI, CRP, CDT, and CR. No significant differences were found between the group with elevated LFT (N = 10) and the group without elevated LFT (N = 32) regarding BMI, CRP, CDT, and CR, except for THC-OH, which was even lower in the elevated-LFT group. These results argue against a relevant harmful impact of chronic cannabis inhalation on the liver function of relatively healthy humans (apart from nicotine dependence). Specifically, the liver function tests were not significantly influenced by THC and THC-COOH levels, both objective markers for the amount and duration of prior cannabis use.

The cannabis withdrawal syndrome: current insights

The cannabis withdrawal syndrome (CWS) is a criterion of cannabis use disorders (CUDs) (Diagnostic and Statistical Manual of Mental Disorders - Fifth Edition) and cannabis dependence (International Classification of Diseases [ICD]-10). Several lines of evidence from animal and human studies indicate that cessation from long-term and regular cannabis use precipitates a specific withdrawal syndrome with mainly mood and behavioral symptoms of light to moderate intensity, which can usually be treated in an outpatient setting. Regular cannabis intake is related to a desensitization and downregulation of human brain cannabinoid 1 (CB1) receptors. This starts to reverse within the first 2 days of abstinence and the receptors return to normal functioning within 4 weeks of abstinence, which could constitute a neurobiological time frame for the duration of CWS, not taking into account cellular and synaptic long-term neuroplasticity elicited by long-term cannabis use before cessation, for example, being possibly responsible for cannabis craving. The CWS severity is dependent on the amount of cannabis used pre-cessation, gender, and heritable and several environmental factors. Therefore, naturalistic severity of CWS highly varies. Women reported a stronger CWS than men including physical symptoms, such as nausea and stomach pain. Comorbidity with mental or somatic disorders, severe CUD, and low social functioning may require an inpatient treatment (preferably qualified detox) and post-acute rehabilitation. There are promising results with gabapentin and delta-9-tetrahydrocannabinol analogs in the treatment of CWS. Mirtazapine can be beneficial to treat CWS insomnia. According to small studies, venlafaxine can worsen the CWS, whereas other antidepressants, atomoxetine, lithium, buspirone, and divalproex had no relevant effect. Certainly, further research is required with respect to the impact of the CWS treatment setting on long-term CUD prognosis and with respect to psychopharmacological or behavioral approaches, such as aerobic exercise therapy or psychoeducation, in the treatment of CWS. The up-to-date ICD-11 Beta Draft is recommended to be expanded by physical CWS symptoms, the specification of CWS intensity and duration as well as gender effects.

Using Bayes factors for testing hypotheses about intervention effectiveness in addictions research

BACKGROUND AND AIMS

It has been proposed that more use should be made of Bayes factors in hypothesis testing in addiction research. Bayes factors are the ratios of the likelihood of a specified hypothesis (e.g. an intervention effect within a given range) to another hypothesis (e.g. no effect). They are particularly important for differentiating lack of strong evidence for an effect and evidence for lack of an effect. This paper reviewed randomized trials reported in Addiction between January and June 2013 to assess how far Bayes factors might improve the interpretation of the data.

METHODS

Seventy-five effect sizes and their standard errors were extracted from 12 trials. Seventy-three per cent (n = 55) of these were non-significant (i.e. P > 0.05). For each non-significant finding a Bayes factor was calculated using a population effect derived from previous research. In sensitivity analyses, a further two Bayes factors were calculated assuming clinically meaningful and plausible ranges around this population effect.

RESULTS

Twenty per cent (n = 11) of the non-significant Bayes factors were < ⅓ and 3.6% (n = 2) were > 3. The other 76.4% (n = 42) of Bayes factors were between ⅓ and 3. Of these, 26 were in the direction of there being an effect (Bayes factor > 1 and < 3); 12 tended to favour the hypothesis of no effect (Bayes factor < 1 and > ⅓); and for four there was no evidence either way (Bayes factor = 1). In sensitivity analyses, 13.3% of Bayes Factors were < ⅓ (n = 20), 62.7% (n = 94) were between ⅓ and 3 and 24.0% (n = 36) were > 3, showing good concordance with the main results.

CONCLUSIONS

Use of Bayes factors when analysing data from randomized trials of interventions in addiction research can provide important information that would lead to more precise conclusions than are obtained typically using currently prevailing methods.

Risks associated with the non-medicinal use of cannabis

BACKGROUND

Cannabis is the most commonly consumed illicit drug around the world; in Germany, about 4.5% of all adults use it each year. Intense cannabis use is associated with health risks. Evidence-based treatments are available for health problems caused by cannabis use.

METHODS

Selective literature review based on a search of the PubMed database, with special emphasis on systematic reviews, meta-analyses, cohort studies, randomized controlled trials (RCTs), case-control studies, and treatment guidelines.

RESULTS

The delta-9-tetrahydrocannabinol content of cannabis products is rising around the world as a result of plant breeding, while cannabidiol, in contrast, is often no longer detectable. Various medical conditions can arise acutely after cannabis use, depending on the user's age, dose, frequency, mode and situation of use, and individual disposition; these include panic attacks, psychotic symptoms, deficient attention, impaired concentration, motor incoordination, and nausea. In particular, intense use of high doses of cannabis over many years, and the initiation of cannabis use in adolescence, can be associated with substance dependence (DSM-5; ICD-10), specific withdrawal symptoms, cognitive impairment, affective disorders, psychosis, anxiety disorders, and physical disease outside the brain (mainly respiratory and cardiovascular conditions). At present, the most effective way to treat cannabis dependence involves a combination of motivational encouragement, cognitive behavioral therapy, and contingency management (level 1a evidence). For adolescents, family therapy is also recommended (level 1a evidence). No pharmacological treatments can be recommended to date, as evidence for their efficacy is lacking.

CONCLUSION

Further research is needed to elucidate the causal relationships between intense cannabis use and potential damage to physical and mental health. Health problems due to cannabis use can be effectively treated.

Dose-dependent effects of cannabis on the neural correlates of error monitoring in frequent cannabis users

Cannabis has been suggested to impair the capacity to recognize discrepancies between expected and executed actions. However, there is a lack of conclusive evidence regarding the acute impact of cannabis on the neural correlates of error monitoring. In order to contribute to the available knowledge, we used a randomized, double-blind, between-groups design to investigate the impact of administration of a low (5.5 mg THC) or high (22 mg THC) dose of vaporized cannabis vs. placebo on the amplitudes of the error-related negativity (ERN) and error positivity (Pe) in the context of the Flanker task, in a group of frequent cannabis users (required to use cannabis minimally 4 times a week, for at least 2 years). Subjects in the high dose group (n=18) demonstrated a significantly diminished ERN in comparison to the placebo condition (n=19), whereas a reduced Pe amplitude was observed in both the high and low dose (n=18) conditions, as compared to placebo. The results suggest that a high dose of cannabis may affect the neural correlates of both the conscious (late), as well as the initial automatic processes involved in error monitoring, while a low dose of cannabis might impact only the conscious (late) processing of errors.

Abstinence phenomena of chronic cannabis-addicts prospectively monitored during controlled inpatient detoxification (Part II): Psychiatric complaints and their relation to delta-9-tetrahydrocannabinol and its metabolites in serum

OBJECTIVE

To investigate the impact of inpatient detoxification treatment on psychiatric symptoms of chronic cannabis addicts and to analyze the influence of serum cannabinoid levels on the severity of these symptoms.

METHODS

Thirty five treatment-seeking, not active co-morbid chronic cannabis dependents (ICD-10) were studied on admission and on abstinence days 8 and 16, using several observational and self-report scales, such as Hamilton Depression Rating Scale (HAMD), Hamilton Anxiety Rating Scale (HAMA), Young Mania Rating Scale (YMRS) and Brief Psychiatric Rating Scale (BPRS), and the Symptom Checklist-90-Revised (SCL-90-R). Simultaneously obtained serum was analyzed with regard to levels of delta-9-tetrahydrocannabinol (THC) and its main metabolites 11-hydroxy-delta-9-tetrahydrocannabinol (THC-OH) and 11-nor-delta-9-tetrahydrocannabinol-9-carboxylic acid (THC-COOH).

RESULTS

At admission, nearly 90% of the patients were not, or only mildly, affected by depression, anxiety or manic symptoms. In contrast, patients' self-description indicated a strong psychiatric burden in approximately 60% of the cases. All patients improved significantly within 16 days of the treatment. Effect sizes ranged from 0.7 to 1.4. (Cohen's d) for the respective scales. Serum THC-levels were positively associated with impairment of cognition in HAMA and motor retardation in BPRS. All other test results were not significantly related to the serum levels of the measured cannabinoids.

DISCUSSION

Effects of the cannabis withdrawal syndrome and executive dysfunctions might explain the discrepancy between the observer ratings and self-reported psychiatric burden.

CONCLUSION

Inpatient cannabis detoxification treatment significantly improved psychiatric symptoms. Serum THC-levels were not associated with affective symptoms and anxiety but predicted cognitive impairment and motor retardation.