Plasma and urine profiles of Delta9-tetrahydrocannabinol and its metabolites 11-hydroxy-Delta9-tetrahydrocannabinol and 11-nor-9-carboxy-Delta9-tetrahydrocannabinol after cannabis smoking by male volunteers to estimate recent consumption by athletes.

Since 2004, cannabis has been prohibited by the World Anti-Doping Agency for all sports competitions. In the years since then, about half of all positive doping cases in Switzerland have been related to cannabis consumption. In doping urine analysis, the target analyte is 11-nor-9-carboxy-Delta(9)-tetrahydrocannabinol (THC-COOH), the cutoff being 15 ng/mL. However, the wide urinary detection window of the long-term metabolite of Delta(9)-tetrahydrocannabinol (THC) does not allow a conclusion to be drawn regarding the time of consumption or the impact on the physical performance. The purpose of the present study on light cannabis smokers was to evaluate target analytes with shorter urinary excretion times. Twelve male volunteers smoked a cannabis cigarette standardized to 70 mg THC per cigarette. Plasma and urine were collected up to 8 h and 11 days, respectively. Total THC, 11-hydroxy-Delta(9)-tetrahydrocannabinol (THC-OH), and THC-COOH were determined after hydrolysis followed by solid-phase extraction and gas chromatography/mass spectrometry. The limits of quantitation were 0.1-1.0 ng/mL. Eight puffs delivered a mean THC dose of 45 mg. Plasma levels of total THC, THC-OH, and THC-COOH were measured in the ranges 0.2-59.1, 0.1-3.9, and 0.4-16.4 ng/mL, respectively. Peak concentrations were observed at 5, 5-20, and 20-180 min. Urine levels were measured in the ranges 0.1-1.3, 0.1-14.4, and 0.5-38.2 ng/mL, peaking at 2, 2, and 6-24 h, respectively. The times of the last detectable levels were 2-8, 6-96, and 48-120 h. Besides high to very high THC-COOH levels (245 +/- 1,111 ng/mL), THC (3 +/- 8 ng/mL) and THC-OH (51 +/- 246 ng/mL) were found in 65 and 98% of cannabis-positive athletes' urine samples, respectively. In conclusion, in addition to THC-COOH, the pharmacologically active THC and THC-OH should be used as target analytes for doping urine analysis. In the case of light cannabis use, this may allow the estimation of more recent consumption, probably influencing performance during competitions. However, it is not possible to discriminate the intention of cannabis use, i.e., for recreational or doping purposes. Additionally, pharmacokinetic data of female volunteers are needed to interpret cannabis-positive doping cases of female athletes.

Cannabis et conduite automobile [Cannabis and automobile driving]

Cannabis use has increased considerably during the last 15 years. One of the major problems dealing with cannabis use is driving under the influence of drugs. With the exception of ethyl alcohol, the majority of the epidemiological studies have shown that cannabis is the most frequently detected substance in people suspected of driving under the influence of drugs. Experimental studies are therefore needed to assess cannabis effects on driving capability. Many studies indicate that cannabis impairs psychomotor performance. This impairment becomes obvious when high doses of cannabis are taken, when ethyl alcohol or other drugs are simultaneously ingested, or when sustained attention is needed. Moreover, cannabis effects are qualitatively different from those observed after ethyl alcohol consumption. In forensic practice, cannabis impairment of driving performance must be related to cannabinoids blood concentrations. To facilitate the interpretation of cannabinoids blood levels, several models were set up recently. These models must be further improved in order to fit in with all circumstances of cannabis use.

Inferring about individual drug and schizotypy effects on cognitive functioning in polydrug using mephedrone users before and after clubbing

Objective: Mephedrone has been recently made illegal in Europe, but little empirical evidence is available on its impact on human cognitive functions. We investigated acute and chronic effects of mephedrone consumption on drug-sensitive cognitive measures, while also accounting for the influence of associated additional drug use and personality features. Method: Twenty-six volunteers from the general population performed tasks measuring verbal learning, verbal fluency and cognitive flexibility before and after a potential drug-taking situation (pre- and post-clubbing at dance clubs, respectively). Participants also provided information on chronic and recent drug use, schizotypal (O-LIFE) and depressive symptoms (Beck depression inventory), sleep pattern and premorbid IQ. Results: We found that i) mephedrone users performed worse than non-users pre-clubbing, and deteriorated from the pre-clubbing to the post-clubbing assessment, ii) pre-clubbing cannabis and amphetamine (not mephedrone) use predicted relative cognitive attenuations, iii) post-clubbing, depression scores predicted relative cognitive attenuations, and iv) schizotypy was largely unrelated to cognitive functioning, apart from a negative relationship between cognitive disorganisation and verbal fluency. Conclusion: Results suggest that polydrug use and depressive symptoms in the general population negatively affect cognition. For schizotypy, only elevated cognitive disorganisation showed potential links to a pathological cognitive profile previously reported along the psychosis dimension.

Cost-effectiveness analysis of the first-line therapies for nicotine dependence.

BACKGROUND: Nicotine dependence is the major obstacle for smokers who want to quit. Guidelines have identified five effective first-line therapies, four nicotine replacement therapies (NRTs)--gum, patch, nasal spray and inhaler--and bupropion. Studying the extent to which these various treatments are cost-effective requires additional research. OBJECTIVES: To determine cost-effectiveness (CE) ratios of pharmacotherapies for nicotine dependence provided by general practitioners (GPs) during routine visits as an adjunct to cessation counselling. METHODS: We used a Markov model to generate two cohorts of one-pack-a-day smokers: (1) the reference cohort received only cessation counselling from a GP during routine office visits; (2) the second cohort received the same counselling plus an offer to use a pharmacological treatment to help them quit smoking. The effectiveness of adjunctive therapy was expressed in terms of the resultant differential in mortality rate between the two cohorts. Data on the effectiveness of therapies came from meta-analyses, and we used odds ratio for quitting as the measure of effectiveness. The costs of pharmacotherapies were based on the cost of the additional time spent by GPs offering, prescribing and following-up treatment, and on the retail prices of the therapies. We used the third-party-payer perspective. Results are expressed as the incremental cost per life-year saved. RESULTS: The cost per life-year saved for only counselling ranged from Euro 385 to Euro 622 for men and from Euro 468 to Euro 796 for women. The CE ratios for the five pharmacological treatments varied from Euro 1768 to Euro 6879 for men, and from Euro 2146 to Euro 8799 for women. Significant variations in CE ratios among the five treatments were primarily due to differences in retail prices. The most cost-effective treatments were bupropion and the patch, and, then, in descending order, the spray, the inhaler and, lastly, gum. Differences in CE between men and women across treatments were due to the shape of their respective mortality curve. The lowest CE ratio in men was for the 45- to 49-year-old group and for women in the 50- to 54-year-old group. Sensitivity analysis showed that changes in treatment efficacy produced effects only for less-well proven treatments (spray, inhaler, and bupropion) and revealed a strong influence of the discount rate and natural quit rate on the CE of pharmacological treatments. CONCLUSION: The CE of first-line treatments for nicotine dependence varied widely with age and sex and was sensitive to the assumption for the natural quit rate. Bupropion and the nicotine patch were the two most cost-effective treatments.

Acute Effects of Cannabis Smoking on Skills Related to Driving : an fMRI Study

Introduction : Driving is a complex everyday task requiring mechanisms of perception, attention, learning, memory, decision making and action control, thus indicating that involves numerous and varied brain networks. If many data have been accumulated over time about the effects of alcohol consumption on driving capability, much less is known about the role of other psychoactive substances, such as cannabis (Chang et al.2007, Ramaekers et al, 2006). Indeed, the solicited brain areas during safe driving which could be affected by cannabis exposure have not yet been clearly identified. Our aim is to study these brain regions during a tracking task related to driving skills and to evaluate the modulation due to the tolerance of cannabis effects. Methods : Eight non-smoker control subjects participated to an fMRI experiment based on a visuo-motor tracking task, alternating active tracking blocks with passive tracking viewing and rest condition. Half of the active tracking conditions included randomly presented traffic lights as distractors. Subjects were asked to track with a joystick with their right hand and to press a button with their left index at each appearance of a distractor. Four smoking subjects participated to the same fMRI sessions once before and once after smoking cannabis and a placebo in two independent cross-over experiments. We quantified the performance of the subjects by measuring the precision of the behavioural responses (i.e. percentage of time of correct tracking and reaction times to distractors). Functional MRI data were acquired using on a 3.0T Siemens Trio system equipped with a 32-channel head coil. BOLD signals will be obtained with a gradient-echo EPI sequence (TR=2s, TE=30ms, FoV=216mm, FA=90°, matrix size 72×72, 32 slices, thickness 3mm). Preprocessing, single subject analysis and group statistics were conducted on SPM8b. Results were thresholded at p<0.05 (FWE corrected) and at k>30 for spatial extent. Results : Behavioural results showed a significant impairment in task and cognitive test performance of the subjects after cannabis inhalation when comparing their tracking accuracy either to the controls subjects or to their performances before the inhalation or after the placebo inhalation (p<0.001 corrected). In controls, fMRI BOLD analysis of the active tracking condition compared to the passive one revealed networks of polymodal areas in superior frontal and parietal cortex dealing with attention and visuo-spatial coordination. In accordance to what is known of the visual and sensory motor networks we found activations in V4, frontal eye-field, right middle frontal gyrus, intra-parietal sulcus, temporo-parietal junction, premotor and sensory-motor cortex. The presence of distractors added a significant activation in the precuneus. Preliminary results on cannabis smokers in the acute phase, compared either to themselves before the cannabis inhalation or to control subjects, showed a decreased activation in large portions of the frontal and parietal attention network during the simple tracking task, but greater involvement of precuneus, of the superior part of intraparietal sulcus and middle frontal gyrus bilaterally when distractors were present in the task. Conclusions : Our preliminary results suggest that acute cannabis smoking alters performances and brain activity during active tracking tasks, partly reorganizing the recruitment of brain areas of the attention network.

A comparison of the spatial dependence of body mass index among adults and children in a Swiss general population.

BACKGROUND: Body mass index (BMI) may cluster in space among adults and be spatially dependent. Whether BMI clusters among children and how age-specific BMI clusters are related remains unknown. We aimed to identify and compare the spatial dependence of BMI in adults and children in a Swiss general population, taking into account the area's income level. METHODS: Geo-referenced data from the Bus Santé study (adults, n=6663) and Geneva School Health Service (children, n=3601) were used. We implemented global (Moran's I) and local (local indicators of spatial association (LISA)) indices of spatial autocorrelation to investigate the spatial dependence of BMI in adults (35-74 years) and children (6-7 years). Weight and height were measured using standardized procedures. Five spatial autocorrelation classes (LISA clusters) were defined including the high-high BMI class (high BMI participant's BMI value correlated with high BMI-neighbors' mean BMI values). The spatial distributions of clusters were compared between adults and children with and without adjustment for area's income level. RESULTS: In both adults and children, BMI was clearly not distributed at random across the State of Geneva. Both adults' and children's BMIs were associated with the mean BMI of their neighborhood. We found that the clusters of higher BMI in adults and children are located in close, yet different, areas of the state. Significant clusters of high versus low BMIs were clearly identified in both adults and children. Area's income level was associated with children's BMI clusters. CONCLUSIONS: BMI clusters show a specific spatial dependence in adults and children from the general population. Using a fine-scale spatial analytic approach, we identified life course-specific clusters that could guide tailored interventions.

Two cases of "cannabis acute psychosis" following the administration of oral cannabis.

BACKGROUND: Cannabis is the most commonly used illegal drug and its therapeutic aspects have a growing interest. Short-term psychotic reactions have been described but not clearly with synthetic oral THC, especially in occasional users. CASE PRESENTATIONS: We report two cases of healthy subjects who were occasional but regular cannabis users without psychiatric history who developed transient psychotic symptoms (depersonalization, paranoid feelings and derealisation) following oral administration of cannabis. In contrast to most other case reports where circumstances and blood concentrations are unknown, the two cases reported here happened under experimental conditions with all subjects negative for cannabis, opiates, amphetamines, cocaine, benzodiazepines and alcohol, and therefore the ingested dose, the time-events of effects on behavior and performance as well as the cannabinoid blood levels were documented. CONCLUSION: While the oral route of administration achieves only limited blood concentrations, significant psychotic reactions may occur.

Interindividual variability of the clinical pharmacokinetics of methadone: implications for the treatment of opioid dependence

Methadone is widely used for the treatment of opioid dependence. Although in most countries the drug is administered as a racemic mixture of (R)- and (S)- methadone, (R)-methadone accounts for most, if not all, of the opioid effects. Methadone can be detected in the blood 15-45 minutes after oral administration, with peak plasma concentration at 2.5-4 hours. Methadone has a mean bioavailability of around 75% (range 36-100%). Methadone is highly bound to plasma proteins, in particular to alpha(1)-acid glycoprotein. Its mean free fraction is around 13%, with a 4-fold interindividual variation. Its volume of distribution is about 4 L/kg (range 2-13 L/kg). The elimination of methadone is mediated by biotransformation, followed by renal and faecal excretion. Total body clearance is about 0.095 L/min, with wide interindividual variation (range 0.02-2 L/min). Plasma concentrations of methadone decrease in a biexponential manner, with a mean value of around 22 hours (range 5-130 hours) for elimination half-life. For the active (R)-enantiomer, mean values of around 40 hours have been determined. Cytochrome P450 (CYP) 3A4 and to a lesser extent 2D6 are probably the main isoforms involved in methadone metabolism. Rifampicin (rifampin), phenobarbital, phenytoin, carbamazepine, nevirapine, and efavirenz decrease methadone blood concentrations, probably by induction of CYP3A4 activity, which can result in severe withdrawal symptoms. Inhibitors of CYP3A4, such as fluconazole, and of CYP2D6, such as paroxetine, increase methadone blood concentrations. There is an up to 17-fold interindividual variation of methadone blood concentration for a given dosage, and interindividual variability of CYP enzymes accounts for a large part of this variation. Since methadone probably also displays large interindividual variability in its pharmacodynamics, methadone treatment must be individually adapted to each patient. Because of the high morbidity and mortality associated with opioid dependence, it is of major importance that methadone is used at an effective dosage in maintenance treatment: at least 60 mg/day, but typically 80-100 mg/day. Recent studies also show that a subset of patients might benefit from methadone dosages larger than 100 mg/day, many of them because of high clearance. In clinical management, medical evaluation of objective signs and subjective symptoms is sufficient for dosage titration in most patients. However, therapeutic drug monitoring can be useful in particular situations. In the case of non-response trough plasma concentrations of 400 microg/L for (R,S)-methadone or 250 microg/L for (R)-methadone might be used as target values.

Association of smoking and nicotine dependence with pre-diabetes in young and healthy adults.

INTRODUCTION: Several studies have shown an increased risk of type 2 diabetes among smokers. Therefore, the aim of this analysis was to assess the relationship between smoking, cumulative smoking exposure and nicotine dependence with pre-diabetes. METHODS: We performed a cross-sectional analysis of healthy adults aged 25-41 in the Principality of Liechtenstein. Individuals with known diabetes, Body Mass Index (BMI) >35 kg/m² and prevalent cardiovascular disease were excluded. Smoking behaviour was assessed by self-report. Pre-diabetes was defined as glycosylated haemoglobin between 5.7% and 6.4%. Multivariable logistic regression models were done. RESULTS: Of the 2142 participants (median age 37 years), 499 (23.3%) had pre-diabetes. There were 1,168 (55%) never smokers, 503 (23%) past smokers and 471 (22%) current smokers, with a prevalence of pre-diabetes of 21.2%, 20.9% and 31.2%, respectively (p <0.0001). In multivariable regression models, current smokers had an odds ratio (OR) of pre-diabetes of 1.82 (95% confidential interval (CI) 1.39; 2.38, p <0.0001). Individuals with a smoking exposure of <5, 5-10 and >10 pack-years had an OR (95% CI) for pre-diabetes of 1.34 (0.90; 2.00), 1.80 (1.07; 3.01) and 2.51 (1.80; 3.59) (p linear trend <0.0001) compared with never smokers. A Fagerström score of 2, 3-5 and >5 among current smokers was associated with an OR (95% CI) for pre-diabetes of 1.27 (0.89; 1.82), 2.15 (1.48; 3.13) and 3.35 (1.73; 6.48) (p linear trend <0.0001). DISCUSSION: Smoking is strongly associated with pre-diabetes in young adults with a low burden of smoking exposure. Nicotine dependence could be a potential mechanism of this relationship.