Carlos Ibáñez

Changes in Regional Cerebral Blood Flow Are Associated With Endothelial Dysfunction Markers in Cocaine-dependent Patients Under Recent Abstinence

Objectives:Cocaine is a known risk factor for several vascular ischemic events. The underlying mechanisms leading to the complications are not fully understood, although thrombus formation and accelerated atherosclerosis are prominent findings. Evidence of endothelial dysfunction (ED), a key phenomenon in the pathogenesis of atherogenesis, has been demonstrated in cocaine-dependent individuals. Abnormal regional cerebral blood flow (rCBF) is a common finding among chronic cocaine users. The aim of this study was to evaluate whether brain perfusion changes were associated with ED markers in cocaine-dependent individuals. Methods:Circulating endothelial cells (CECs), soluble intercellular cell adhesion molecule, and the chemokine regulated on activation normal T cells expressed and secreted were measured in 27 DSM-IV (Diagnostic and Statistical Manual of Mental Disorders–Fourth Edition) cocaine-dependents patients. Regional cerebral blood flow was assessed using single-photon emission computed tomography at baseline (after recent cocaine consumption) and after 4 weeks of strict abstinence under standard benzodiazepine or antipsychotic therapy. We used statistical parametric mapping analysis to evaluate the covariates. Results:Endothelial cell damage/activation markers were significantly higher in cocaine-dependent individuals after recent consumption and were reduced after 1-month abstinence (P < 0.05). Global rCBF exhibited no significant difference between baseline and after abstinence. When regional perfusion was analyzed in association with ED covariates, significant differences were observed in bilateral cortical areas, including the limbic lobes. Conclusions:We demonstrated an association between systemic ED markers and rCBF in cocaine-dependent patients. These findings suggest that vascular injury may play a role in the pathogenesis of abnormal rCBF.

The relative prevalence of schizophrenia among cannabis and cocaine users attending addiction services

BACKGROUND Cannabis and cocaine are the most common illicit drugs for which people are treated in addiction services in Latin America. Much research has suggested that the use of cannabis increases the risk of schizophrenia; there is less evidence concerning cocaine. The aim of the present study was to establish the relative prevalence of schizophrenia in people treated for cannabis use and cocaine use disorders in Chile. METHODS A sample of 22,615 people treated for illicit drug use disorders was obtained from a national registry of addiction service users in Chile. Clinical diagnoses were established at admission to substance use treatment programs or at any point during the period of treatment. Prevalence rates of schizophrenia and related disorders, and affective disorders were calculated for the groups of people with cocaine use disorders, and cannabis use disorders. Odds ratios (OR) for schizophrenia and for affective disorders were calculated for cannabis users using the group of people treated for cocaine use disorders as reference category. RESULTS The prevalence of schizophrenia and related disorders was 1.1% in those with cocaine use disorders, but 5.2% in those with cannabis use disorders (OR 4.9; p<0.01). The prevalence of affective disorders was 9.3% in cocaine use disorders, and 13.2% in cannabis use disorders (OR 1.5; p<0.01). CONCLUSIONS The prevalence of schizophrenia and to a lesser extent affective disorders is higher among people with cannabis use disorder than cocaine use disorder among those attending addiction services.

Descripción de los hallazgos en el perfil lipídico y proteico de pacientes dependientes a cocaína, en abstinencia reciente

BACKGROUND Chronic cocaine users develop multiple potentially lethal ischemic vascular complications associated with accelerated atherosclerosis. AIM To assess biochemical and lipid profiles among cocaine dependent subjects in recent abstinence. MATERIAL AND METHODS A blood sample to measure blood count, biochemical and lipid profiles was obtained from 78 patients aged 19 to 53 years (78% males) who complied with DSM-IV criteria for cocaine dependency. Laboratory results were compared with a group of normal subjects. RESULTS All cases had positive urinary cocaine, with a mean consumption lapse of 7.6 years. The frequency of smoking was higher in cases. Dependent males had higher body mass index than controls. Compared to controls, dependent females had significantly higher triglyceride (TG) levels and lower HDL cholesterol. Therefore the relation total/HDL cholesterol was higher (p = 0.0365). Dependent males had higher TG levels than their normal counterparts. Dependent subjects consuming cocaine base-paste had higher TG levels. Total proteins, albumin, urea and blood urea nitrogen were lower in dependent subjects. Among males, serum creatinine was lower and blood urea was positively correlated with the daily amount of cocaine use (p = 0.03). After a month of strict abstinence, lipid profile was repeated in 27 patients and remained unchanged. CONCLUSIONS Chronic cocaine use was associated with higher TG in both genders and lower HDL cholesterol in women when compared with a group of healthy counterparts.Background: Chronic cocaine users develop multiple potentially lethal ischemic vascular complications associated with accelerated atherosclerosis. Aim: To assess biochemical and lipid profiles among cocaine dependent subjects in recent abstinence. Material and methods: A blood sample to measure blood count, biochemical and lipid profiles was obtained from 78 patients aged 19 to 53 years (78% males) who complied with DSM –IV criteria for cocaine dependency. Laboratory results were compared with a group of normal subjects. Results: All cases had positive urinary cocaine, with a mean consumption lapse of 7.6 years. The frequency of smoking was higher in cases. Dependent males had higher body mass index than controls. Compared to controls, dependent females had significantly higher triglyceride (TG) levels and lower HDL cholesterol. Therefore the relation total/HDL cholesterol was higher (p=0.0365). Dependent males had higher TG levels than their normal counterparts. Dependent subjects consuming cocaine base-paste had higher TG levels. Total proteins, albumin, urea and blood urea nitrogen were lower in dependent subjects. Among males, serum creatinine was lower and blood urea was positively correlated with the daily amount of cocaine use (p=0.03). After a month of strict abstinence, lipid profile was repeated in 27 patients and remained unchanged. Conclusions: Chronic cocaine use was associated with higher TG in both genders and lower HDL cholesterol in women when compared which a group of healthy counterparts.

Twitter for marijuana infodemiology

Today online social networks seem to be good tools to quickly monitor what is going on with the population, since they provide environments where users can freely share large amounts of information related to their own lives. Due to well known limitations of surveys, this novel kind of data can be used to get additional real time insights from people to understand their actual behavior related to drug use. The aim of this work is to make use of text messages (tweets) and relationships between Chilean Twitter users to predict marijuana use among them. To do this we collected Twitter accounts using a location-based criteria, and built a set of features based on tweets they made and ego centric network metrics. To get tweet-based features, tweets were filtered using marijuana-related keywords and a set of 1000 tweets were manually labeled to train algorithms capable of predicting marijuana use in tweets. In addition, a sentiment classifier of tweets was developed using the TASS corpus. Then, we made a survey to get real marijuana use labels related to accounts and these labels were used to train supervised machine learning algorithms. The marijuana use per user classifier had precision, recall and F-measure results close to 0.7, implying significant predictive power of the selected variables. We obtained a model capable of predicting marijuana use of Twitter users and estimating their opinion about marijuana. This information can be used as an efficient (fast and low cost) tool for marijuana surveillance, and support decision making about drug policies.