977 resultados para Drug Consumption Facilities


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Opposing effects of ondansetron and tramadol on the serotonin pathway have been suggested which possibly increase tramadol consumption and emesis when co-administered. In a randomized, double-blinded study, 179 patients received intravenous ondansetron, metoclopramide, or placebo for emesis prophylaxis. Analgesic regimen consisted of tramadol intraoperative loading and subsequent patient-controlled analgesia. Tramadol consumption and response to antiemetic treatment were compared. Additionally, plasma concentrations of ondansetron and (+)O-demethyltramadol and CYP2D6 genetic variants were analyzed as possible confounders influencing analgesic and antiemetic efficacy. Tramadol consumption did not differ between the groups. Response rate to antiemetic prophylaxis was superior in patients receiving ondansetron (85.0%) compared with placebo (66.7%, P = .046), with no difference to metoclopramide (69.5%). Less vomiting was reported in the immediate postoperative hours in the verum groups (ondansetron 5.0%, metoclopramide 5.1%) compared with placebo (18.6%; P = .01). Whereas plasma concentrations of (+)O-demethyltramadol were significantly correlated to CYP2D6 genotype, no influence was detected for ondansetron. Co-administration of ondansetron neither increased tramadol consumption nor frequency of PONV in this postoperative setting. PERSPECTIVE: Controversial findings were reported for efficacy of tramadol and ondansetron when co-administered due to their opposing serotonergic effects. Co-medication of these drugs neither increased postoperative analgesic consumption nor frequency of emesis in this study enrolling patients recovering from major surgery.

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Differentiation between external contamination and incorporation of drugs or their metabolites from inside the body via blood, sweat or sebum is a general issue in hair analysis and of high concern when interpreting analytical results. In hair analysis for cannabinoids the most common target is Delta9-tetrahydrocannabinol (THC), sometimes cannabidiol (CBD) and cannabinol (CBN) are determined additionally. After repeated external contamination by cannabis smoke these analytes are known to be found in hair even after performing multiple washing steps. A widely accepted strategy to unequivocally prove active cannabis consumption is the analysis of hair extracts for the oxidative metabolite 11-nor-9-carboxy-THC (THC-COOH). Although the acidic nature of this metabolite suggests a lower rate of incorporation into the hair matrix compared to THC, it is not fully understood up to now why hair concentrations of THC-COOH are generally found to be much lower (mostly <10 pg/mg) than the corresponding THC concentrations. Delta9-Tetrahydrocannabinolic acid A (THCA A) is the preliminary end product of the THC biosynthesis in the cannabis plant. Unlike THC it is non-psychoactive and can be regarded as a 'precursor' of THC being largely decarboxylated when heated or smoked. The presented work shows for the first time that THCA A is not only detectable in blood and urine of cannabis consumers but also in THC positive hair samples. A pilot experiment performed within this study showed that after oral intake of THCA A on a regular basis no relevant incorporation into hair occurred. It can be concluded that THCA A in hair almost exclusively derives from external contamination e.g. by side stream smoke. Elevated temperatures during the analytical procedure, particularly under alkaline conditions, can lead to decarboxylation of THCA A and accordingly increase THC concentrations in hair. Additionally, it has to be kept in mind that in hair samples tested positive for THCA A at least a part of the 'non-artefact' THC probably derives from external contamination as well, because in condensate of cannabis smoke both THC and THCA A are present in relevant amounts. External contamination by side stream smoke could therefore explain the great differences in THC and THC-COOH hair concentrations commonly found in cannabis users.

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The consumption of antibiotics in the inpatient setting of Switzerland was assessed to determine possible differences between linguistic regions, and to compare these results with European results. Data on antibiotic consumption were obtained from a sentinel network representing 54% of the national acute care hospitals, and from a private drug market monitoring company. Aggregated data were converted into defined daily doses (DDD). The total consumption density in Switzerland was close to the median consumption reported in European surveys. Between 2004 and 2008, the total consumption of systemic antibiotics rose from 46.1 to 54.0 DDD per 100 occupied bed-days in the entire hospitals, and from 101.6 to 114.3 DDD per 100 occupied bed-days in the intensive care units. Regional differences were observed for total consumption and among antibiotic classes. Hospitals in the Italian-speaking region showed a significantly higher consumption density, followed by the French- and German-speaking regions. Hospitals in the Italian-speaking region also had a higher consumption of fluoroquinolones, in line with the reported differences between Italy, Germany and France. Antibiotic consumption in acute care hospitals in Switzerland is close to the European median with a relatively low consumption in intensive care units. Some of the patterns of variation in consumption levels noticed among European countries are also observed among the cultural regions of Switzerland.

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Drug-use among teenagers in two ex-communist countries, Romania and the Republic of Moldova, was studied both in isolation and on a comparative basis. The group carried out a psycho-social study, gaining data from two representative samples of teenagers (N=713 in Romania and N=760 in Moldova). Teachers, parents and experts were also interviewed, using focus groups, questionnaires and 3 individual interviews. Aspects of the phenomenon investigated were the extent of drug use (frequency of consumption, kinds of drugs used, and categories of teenage consumers, by age, gender, residential areas, occupational status, marketplaces and traffickers); internal and external stimulating and inhibiting factors, the attitude of all four categories of subjects to drug abuse in teenagers, and strategies for combating this and other such problems.

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BACKGROUND: Alcohol consumption leading to morbidity and mortality affects HIV-infected individuals. Here, we aimed to study self-reported alcohol consumption and to determine its association with adherence to antiretroviral therapy (ART) and HIV surrogate markers. METHODS: Cross-sectional data on daily alcohol consumption from August 2005 to August 2007 were analysed and categorized according to the World Health Organization definition (light, moderate or severe health risk). Multivariate logistic regression models and Pearson's chi(2) statistics were used to test the influence of alcohol use on endpoints. RESULTS: Of 6,323 individuals, 52.3% consumed alcohol less than once a week in the past 6 months. Alcohol intake was deemed light in 39.9%, moderate in 5.0% and severe in 2.8%. Higher alcohol consumption was significantly associated with older age, less education, injection drug use, being in a drug maintenance programme, psychiatric treatment, hepatitis C virus coinfection and with a longer time since diagnosis of HIV. Lower alcohol consumption was found in males, non-Caucasians, individuals currently on ART and those with more ART experience. In patients on ART (n=4,519), missed doses and alcohol consumption were positively correlated (P<0.001). Severe alcohol consumers, who were pretreated with ART, were more often off treatment despite having CD4+ T-cell count <200 cells/microl; however, severe alcohol consumption per se did not delay starting ART. In treated individuals, alcohol consumption was not associated with worse HIV surrogate markers. CONCLUSIONS: Higher alcohol consumption in HIV-infected individuals was associated with several psychosocial and demographic factors, non-adherence to ART and, in pretreated individuals, being off treatment despite low CD4+ T-cell counts.

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Objective. Predictors of non-adherence to antiretroviral medications in a population of low-income, multiethnic, HIV-positive smokers were investigated. ^ Methods. A secondary analysis was conducted using baseline data collected from 326 patients currently prescribed antiretrovirals enrolled in a randomized clinical trial assessing smoking outcomes. Variables evaluated included demographics, stress, depression, nicotine dependence, illicit drug use and alcohol use. ^ Results. The average age of participants was 45.9 years (SD=7.6). The majority of participants were male (72.1%), Black (76.7%), reported sexual contact as the method of HIV exposure (heterosexual (43%) and MSM (27%)) and were antiretroviral adherent (60.4%). Results from unadjusted analyses indicated depression (OR=1.02; 95% CI=1.00-1.04), illicit drug use (OR=2.39; 95% CI=1.51-3.79) and alcohol consumption (OR=2.86; 95% CI=1.79-4.57) were associated with non-adherence. Multivariate analyses indicated nicotine dependence (OR=1.13; 95% CI=1.02-1.25), illicit drug use (OR=2.10; 95% CI=1.27-3.49) and alcohol use (OR=2.50; 95% CI=1.52-4.12) were associated with nonadherence. ^ Conclusions. Illicit drug use, alcohol use and nicotine dependence are formidable barriers to antiretroviral adherence in this population. Future research is needed to assess how to address these variables in the context of improving antiretroviral adherence for individuals living with HIV/AIDS.^

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Many efforts have been made in order to adequate the production of a solar thermal collector field to the consumption of domestic hot water of the inhabitants of a building. In that sense, much has been achieved in different domains: research agencies, government policies and manufacturers. However, most of the design rules of the solar plants are based on steady state models, whereas solar irradiance, consumption and thermal accumulation are inherently transient processes. As a result of this lack of physical accuracy, thermal storage tanks are sometimes left to be as large as the designer decides without any aforementioned precise recommendation. This can be a problem if solar thermal systems are meant to be implemented in nowadays buildings, where there is a shortage of space. In addition to that, an excessive storage volume could not result more efficient in many residential applications, but costly, extreme in space consumption and in some cases too heavy. A proprietary transient simulation program has been developed and validated with a detailed measurement campaign in an experimental facility. In situ environmental data have been obtained through a whole year of operation. They have been gathered at intervals of 10 min for a solar plant of 50 m2 with a storage tank of 3 m3, including the equipment for domestic hot water production of a typical apartment building. This program has been used to obtain the design and dimensioning criteria of DHW solar plants under daily transient conditions throughout a year and more specifically the size of the storage tank for a multi storey apartment building. Comparison of the simulation results with the current Spanish regulation applicable, “Código Técnico de la Edificación” (CTE 2006), offers fruitful details and establishes solar facilities dimensioning criteria.

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As advanced Cloud services are becoming mainstream, the contribution of data centers in the overall power consumption of modern cities is growing dramatically. The average consumption of a single data center is equivalent to the energy consumption of 25.000 households. Modeling the power consumption for these infrastructures is crucial to anticipate the effects of aggressive optimization policies, but accurate and fast power modeling is a complex challenge for high-end servers not yet satisfied by analytical approaches. This work proposes an automatic method, based on Multi-Objective Particle Swarm Optimization, for the identification of power models of enterprise servers in Cloud data centers. Our approach, as opposed to previous procedures, does not only consider the workload consolidation for deriving the power model, but also incorporates other non traditional factors like the static power consumption and its dependence with temperature. Our experimental results shows that we reach slightly better models than classical approaches, but simul- taneously simplifying the power model structure and thus the numbers of sensors needed, which is very promising for a short-term energy prediction. This work, validated with real Cloud applications, broadens the possibilities to derive efficient energy saving techniques for Cloud facilities.

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Methyl mercury levels in fish tissues have recently become a health issue. Does this toxin adversely affect humans to the point that fish consumption should be severely limited? Health effects of high levels of mercury exposure to human adults are fairly well known, however the effects of lower levels of exposure on human fetal development are less understood. Recent guidelines issued by the United States Food and Drug Agency and the Environmental Protection Agency recommended that pregnant women should refrain from consuming some types of fish, and limit consumption to certain levels, but results of health studies used to develop recommendations were inconclusive when low levels of in-utero methyl mercury exposure were compared. Other studies demonstrated health benefits of fish consumption to developing fetuses. These health benefits may be an over-riding factor, and my interpretation of various studies concludes that restricted consumption of some fish species may be premature at this time due to a need to balance potential health benefits against mercury toxicity hazard.

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Mode of access: Internet.

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Mode of access: Internet.

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On cover: An investigation conducted by Newcomb & Boyd, consulting engineers; sponsored by Naval Facilities Engineering Command.

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Mode of access: Internet.

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Background Non-random mating affects population variation for substance use and dependence. Developmentally, mate selection leading to positive spousal correlations for genetic similarity may result in increased risk for substance use and misuse in offspring. Mate selection varies by cohort and thus, assortative mating in one generation may produce marked changes in rates of substance use in the next. We aim to clarify the mechanisms contributing to spousal similarity for cigarette smoking and alcohol consumption. Methods Using data from female twins and their male spouses, we fit univariate and bivariate twin models to examine the contribution of primary assortative mating and reciprocal marital interaction to spousal resemblance for regular cigarette smoking and nicotine dependence, and for regular alcohol use and alcohol dependence. Results We found that assortative mating significantly influenced regular smoking, regular alcohol use, nicotine dependence and alcohol dependence. The bivariate models for cigarette smoking and alcohol consumption also highlighted the importance of primary assortative mating on all stages of cigarette smoking and alcohol consumption, with additional evidence for assortative mating across the two stages of alcohol consumption. Conclusions Women who regularly used, and subsequently were dependent on cigarettes or alcohol were more likely to marry men with similar behaviors. After mate selection had occurred, one partner's cigarette or alcohol involvement did not significantly modify the other partner's involvement with these psychoactive substances.

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Multidimensional compound optimization is a new paradigm in the drug discovery process, yielding efficiencies during early stages and reducing attrition in the later stages of drug development. The success of this strategy relies heavily on understanding this multidimensional data and extracting useful information from it. This paper demonstrates how principled visualization algorithms can be used to understand and explore a large data set created in the early stages of drug discovery. The experiments presented are performed on a real-world data set comprising biological activity data and some whole-molecular physicochemical properties. Data visualization is a popular way of presenting complex data in a simpler form. We have applied powerful principled visualization methods, such as generative topographic mapping (GTM) and hierarchical GTM (HGTM), to help the domain experts (screening scientists, chemists, biologists, etc.) understand and draw meaningful decisions. We also benchmark these principled methods against relatively better known visualization approaches, principal component analysis (PCA), Sammon's mapping, and self-organizing maps (SOMs), to demonstrate their enhanced power to help the user visualize the large multidimensional data sets one has to deal with during the early stages of the drug discovery process. The results reported clearly show that the GTM and HGTM algorithms allow the user to cluster active compounds for different targets and understand them better than the benchmarks. An interactive software tool supporting these visualization algorithms was provided to the domain experts. The tool facilitates the domain experts by exploration of the projection obtained from the visualization algorithms providing facilities such as parallel coordinate plots, magnification factors, directional curvatures, and integration with industry standard software. © 2006 American Chemical Society.