Quality of life depends on the drinking pattern in alcohol-dependent patients.

AIMS: In patients with alcohol dependence, health-related quality of life (QOL) is reduced compared with that of a normal healthy population. The objective of the current analysis was to describe the evolution of health-related QOL in adults with alcohol dependence during a 24-month period after initial assessment for alcohol-related treatment in a routine practice setting, and its relation to drinking pattern which was evaluated across clusters based on the predominant pattern of alcohol use, set against the influence of baseline variables METHODS: The Medical Outcomes Study 36-Item Short-Form Survey (MOS-SF-36) was used to measure QOL at baseline and quarterly for 2 years among participants in CONTROL, a prospective observational study of patients initiating treatment for alcohol dependence. The sample consisted of 160 adults with alcohol dependence (65.6% males) with a mean (SD) age of 45.6 (12.0) years. Alcohol use data were collected using TimeLine Follow-Back. Based on the participant's reported alcohol use, three clusters were identified: 52 (32.5%) mostly abstainers, 64 (40.0%) mostly moderate drinkers and 44 (27.5%) mostly heavy drinkers. Mixed-effect linear regression analysis was used to identify factors that were potentially associated with the mental and physical summary MOS-SF-36 scores at each time point. RESULTS: The mean (SD) MOS-SF-36 mental component summary score (range 0-100, norm 50) was 35.7 (13.6) at baseline [mostly abstainers: 40.4 (14.6); mostly moderate drinkers 35.6 (12.4); mostly heavy drinkers 30.1 (12.1)]. The score improved to 43.1 (13.4) at 3 months [mostly abstainers: 47.4 (12.3); mostly moderate drinkers 44.2 (12.7); mostly heavy drinkers 35.1 (12.9)], to 47.3 (11.4) at 12 months [mostly abstainers: 51.7 (9.7); mostly moderate drinkers 44.8 (11.9); mostly heavy drinkers 44.1 (11.3)], and to 46.6 (11.1) at 24 months [mostly abstainers: 49.2 (11.6); mostly moderate drinkers 45.7 (11.9); mostly heavy drinkers 43.7 (8.8)]. Mixed-effect linear regression multivariate analyses indicated that there was a significant association between a lower 2-year follow-up MOS-SF-36 mental score and being a mostly heavy drinker (-6.97, P < 0.001) or mostly moderate drinker (-3.34 points, P = 0.018) [compared to mostly abstainers], being female (-3.73, P = 0.004), and having a Beck Inventory scale score ≥8 (-6.54, P < 0.001), at baseline. The mean (SD) MOS-SF-36 physical component summary score was 48.8 (10.6) at baseline, remained stable over the follow-up and did not differ across the three clusters. Mixed-effect linear regression univariate analyses found that the average 2-year follow-up MOS-SF-36 physical score was increased (compared with mostly abstainers) in mostly heavy drinkers (+4.44, P = 0.007); no other variables tested influenced the MOS-SF-36 physical score. CONCLUSION: Among individuals with alcohol dependence, a rapid improvement was seen in the mental dimension of QOL following treatment initiation, which was maintained during 24 months. Improvement was associated with the pattern of alcohol use, becoming close to the general population norm in patients classified as mostly abstainers, improving substantially in mostly moderate drinkers and improving only slightly in mostly heavy drinkers. The physical dimension of QOL was generally in the normal range but was not associated with drinking patterns.

Substitution of (R,S)-methadone by (R)-methadone: Impact on QTc interval.

Methadone is administered as a chiral mixture of (R,S)-methadone. The opioid effect is mainly mediated by (R)-methadone, whereas (S)-methadone blocks the human ether-à-go-go-related gene (hERG) voltage-gated potassium channel more potently, which can cause drug-induced long QT syndrome, leading to potentially lethal ventricular tachyarrhythmias. To investigate whether substitution of (R,S)-methadone by (R)-methadone could reduce the corrected QT (QTc) interval, (R,S)-methadone was replaced by (R)-methadone (half-dose) in 39 opioid-dependent patients receiving maintenance treatment for 14 days. (R)-methadone was then replaced by the initial dose of (R,S)-methadone for 14 days (n = 29). Trough (R)-methadone and (S)-methadone plasma levels and electrocardiogram measurements were taken. The Fridericia-corrected QT (QTcF) interval decreased when (R,S)-methadone was replaced by a half-dose of (R)-methadone; the median (interquartile range [IQR]) values were 423 (398-440) milliseconds (ms) and 412 (395-431) ms (P = .06) at days 0 and 14, respectively. Using a univariate mixed-effect linear model, the QTcF value decreased by a mean of -3.9 ms (95% confidence interval [CI], -7.7 to -0.2) per week (P = .04). The QTcF value increased when (R)-methadone was replaced by the initial dose of (R,S)-methadone for 14 days; median (IQR) values were 424 (398-436) ms and 424 (412-443) ms (P = .01) at days 14 and 28, respectively. The univariate model showed that the QTcF value increased by a mean of 4.7 ms (95% CI, 1.3-8.1) per week (P = .006). Substitution of (R,S)-methadone by (R)-methadone reduces the QTc interval value. A safer cardiac profile of (R)-methadone is in agreement with previous in vitro and pharmacogenetic studies. If the present results are confirmed by larger studies, (R)-methadone should be prescribed instead of (R,S)-methadone to reduce the risk of cardiac toxic effects and sudden death.

Preparation with fasting and acipimox increases myocardial glucose uptake in mice during cardiac 18F-FDG microPET

Purpose: Cardiac 18F-FDG PET is considered as the gold standard to assess myocardial metabolism and infarct size. The myocardial demand for glucose can be influenced by fasting and/or following pharmacological preparation. In the rat, it has been previously shown that fasting combined with preconditioning with acipimox, a nicotinic acid derivate and lipidlowering agent, increased dramatically 18F-FDG uptake in the myocardium. Strategies aimed at reducing infarct scar are evaluated in a variety of mouse models. PET would particularly useful for assessing cardiac viability in the mouse. However, prior knowledge of the best preparation protocol is a prerequisite for accurate measurement of glucose uptake in mice. Therefore, we studied the effect of different protocols on 18F-FDG uptake in the mouse heart.Methods: Mice (n = 15) were separated into three treatment groups according to preconditioning and underwent a 18FDG PET scan. Group 1: No preconditioning (n = 3); Group 2: Overnight fasting (n = 8); and Group 3: Overnight fasting and acipimox (25mg/kg SC) (n = 4). MicroPET images were processed with PMOD to determine 18F-FDG mean standard uptake value (SUV) at 30 min for the whole left ventricle (LV) and for each region of the 17-segments AHA model. For comparisons, we used Mann-Whitney test and multilevel mixed-effects linear regression (Stata 11.0).Results: In total, 27 microPET were performed successfully in 15 animals. Overnight fasting led to a dramatic increase in LV-SUV compared to mice without preconditioning (8.6±0.7g/mL vs. 3.7±1.1g/mL, P<0.001). In addition, LV-SUV was slightly but not significantly higher in animals treated with acipimox compared to animals with overnight fasting alone (10.2±0.5 g/mL, P = 0.06). Fastening increased segmental SUV by 5.1±0.5g/mL as compared to free-feeding mice (from 3.7±0.8g/mL to 8.8±0.4g/mL, P<0.001); segmental-SUV also significantly increased after administration of acipimox (from 8.8±0.4g/mL to 10.1±0.4g/mL, P<0.001).Conclusion: Overnight fasting led to myocardial glucose deprivation and increases 18F-FDG myocardial uptake. Additional administration of acipimox enhances myocardial 18F-FDG uptake, at least at the segmental level. Thus, preconditioning with acipimox may provide better image quality that may help for assessing segmental myocardial metabolism.

Looking for orders of magnitude : five essays in trade and the environment and economic geography

General Summary Although the chapters of this thesis address a variety of issues, the principal aim is common: test economic ideas in an international economic context. The intention has been to supply empirical findings using the largest suitable data sets and making use of the most appropriate empirical techniques. This thesis can roughly be divided into two parts: the first one, corresponding to the first two chapters, investigates the link between trade and the environment, the second one, the last three chapters, is related to economic geography issues. Environmental problems are omnipresent in the daily press nowadays and one of the arguments put forward is that globalisation causes severe environmental problems through the reallocation of investments and production to countries with less stringent environmental regulations. A measure of the amplitude of this undesirable effect is provided in the first part. The third and the fourth chapters explore the productivity effects of agglomeration. The computed spillover effects between different sectors indicate how cluster-formation might be productivity enhancing. The last chapter is not about how to better understand the world but how to measure it and it was just a great pleasure to work on it. "The Economist" writes every week about the impressive population and economic growth observed in China and India, and everybody agrees that the world's center of gravity has shifted. But by how much and how fast did it shift? An answer is given in the last part, which proposes a global measure for the location of world production and allows to visualize our results in Google Earth. A short summary of each of the five chapters is provided below. The first chapter, entitled "Unraveling the World-Wide Pollution-Haven Effect" investigates the relative strength of the pollution haven effect (PH, comparative advantage in dirty products due to differences in environmental regulation) and the factor endowment effect (FE, comparative advantage in dirty, capital intensive products due to differences in endowments). We compute the pollution content of imports using the IPPS coefficients (for three pollutants, namely biological oxygen demand, sulphur dioxide and toxic pollution intensity for all manufacturing sectors) provided by the World Bank and use a gravity-type framework to isolate the two above mentioned effects. Our study covers 48 countries that can be classified into 29 Southern and 19 Northern countries and uses the lead content of gasoline as proxy for environmental stringency. For North-South trade we find significant PH and FE effects going in the expected, opposite directions and being of similar magnitude. However, when looking at world trade, the effects become very small because of the high North-North trade share, where we have no a priori expectations about the signs of these effects. Therefore popular fears about the trade effects of differences in environmental regulations might by exaggerated. The second chapter is entitled "Is trade bad for the Environment? Decomposing worldwide SO2 emissions, 1990-2000". First we construct a novel and large database containing reasonable estimates of SO2 emission intensities per unit labor that vary across countries, periods and manufacturing sectors. Then we use these original data (covering 31 developed and 31 developing countries) to decompose the worldwide SO2 emissions into the three well known dynamic effects (scale, technique and composition effect). We find that the positive scale (+9,5%) and the negative technique (-12.5%) effect are the main driving forces of emission changes. Composition effects between countries and sectors are smaller, both negative and of similar magnitude (-3.5% each). Given that trade matters via the composition effects this means that trade reduces total emissions. We next construct, in a first experiment, a hypothetical world where no trade happens, i.e. each country produces its imports at home and does no longer produce its exports. The difference between the actual and this no-trade world allows us (under the omission of price effects) to compute a static first-order trade effect. The latter now increases total world emissions because it allows, on average, dirty countries to specialize in dirty products. However, this effect is smaller (3.5%) in 2000 than in 1990 (10%), in line with the negative dynamic composition effect identified in the previous exercise. We then propose a second experiment, comparing effective emissions with the maximum or minimum possible level of SO2 emissions. These hypothetical levels of emissions are obtained by reallocating labour accordingly across sectors within each country (under the country-employment and the world industry-production constraints). Using linear programming techniques, we show that emissions are reduced by 90% with respect to the worst case, but that they could still be reduced further by another 80% if emissions were to be minimized. The findings from this chapter go together with those from chapter one in the sense that trade-induced composition effect do not seem to be the main source of pollution, at least in the recent past. Going now to the economic geography part of this thesis, the third chapter, entitled "A Dynamic Model with Sectoral Agglomeration Effects" consists of a short note that derives the theoretical model estimated in the fourth chapter. The derivation is directly based on the multi-regional framework by Ciccone (2002) but extends it in order to include sectoral disaggregation and a temporal dimension. This allows us formally to write present productivity as a function of past productivity and other contemporaneous and past control variables. The fourth chapter entitled "Sectoral Agglomeration Effects in a Panel of European Regions" takes the final equation derived in chapter three to the data. We investigate the empirical link between density and labour productivity based on regional data (245 NUTS-2 regions over the period 1980-2003). Using dynamic panel techniques allows us to control for the possible endogeneity of density and for region specific effects. We find a positive long run elasticity of density with respect to labour productivity of about 13%. When using data at the sectoral level it seems that positive cross-sector and negative own-sector externalities are present in manufacturing while financial services display strong positive own-sector effects. The fifth and last chapter entitled "Is the World's Economic Center of Gravity Already in Asia?" computes the world economic, demographic and geographic center of gravity for 1975-2004 and compares them. Based on data for the largest cities in the world and using the physical concept of center of mass, we find that the world's economic center of gravity is still located in Europe, even though there is a clear shift towards Asia. To sum up, this thesis makes three main contributions. First, it provides new estimates of orders of magnitudes for the role of trade in the globalisation and environment debate. Second, it computes reliable and disaggregated elasticities for the effect of density on labour productivity in European regions. Third, it allows us, in a geometrically rigorous way, to track the path of the world's economic center of gravity.

Quality of life depends on the drinking pattern in alcohol-dependent patients.

AIMS: In patients with alcohol dependence, health-related quality of life (QOL) is reduced compared with that of a normal healthy population. The objective of the current analysis was to describe the evolution of health-related QOL in adults with alcohol dependence during a 24-month period after initial assessment for alcohol-related treatment in a routine practice setting, and its relation to drinking pattern which was evaluated across clusters based on the predominant pattern of alcohol use, set against the influence of baseline variables METHODS: The Medical Outcomes Study 36-Item Short-Form Survey (MOS-SF-36) was used to measure QOL at baseline and quarterly for 2 years among participants in CONTROL, a prospective observational study of patients initiating treatment for alcohol dependence. The sample consisted of 160 adults with alcohol dependence (65.6% males) with a mean (SD) age of 45.6 (12.0) years. Alcohol use data were collected using TimeLine Follow-Back. Based on the participant's reported alcohol use, three clusters were identified: 52 (32.5%) mostly abstainers, 64 (40.0%) mostly moderate drinkers and 44 (27.5%) mostly heavy drinkers. Mixed-effect linear regression analysis was used to identify factors that were potentially associated with the mental and physical summary MOS-SF-36 scores at each time point. RESULTS: The mean (SD) MOS-SF-36 mental component summary score (range 0-100, norm 50) was 35.7 (13.6) at baseline [mostly abstainers: 40.4 (14.6); mostly moderate drinkers 35.6 (12.4); mostly heavy drinkers 30.1 (12.1)]. The score improved to 43.1 (13.4) at 3 months [mostly abstainers: 47.4 (12.3); mostly moderate drinkers 44.2 (12.7); mostly heavy drinkers 35.1 (12.9)], to 47.3 (11.4) at 12 months [mostly abstainers: 51.7 (9.7); mostly moderate drinkers 44.8 (11.9); mostly heavy drinkers 44.1 (11.3)], and to 46.6 (11.1) at 24 months [mostly abstainers: 49.2 (11.6); mostly moderate drinkers 45.7 (11.9); mostly heavy drinkers 43.7 (8.8)]. Mixed-effect linear regression multivariate analyses indicated that there was a significant association between a lower 2-year follow-up MOS-SF-36 mental score and being a mostly heavy drinker (-6.97, P < 0.001) or mostly moderate drinker (-3.34 points, P = 0.018) [compared to mostly abstainers], being female (-3.73, P = 0.004), and having a Beck Inventory scale score ≥8 (-6.54, P < 0.001), at baseline. The mean (SD) MOS-SF-36 physical component summary score was 48.8 (10.6) at baseline, remained stable over the follow-up and did not differ across the three clusters. Mixed-effect linear regression univariate analyses found that the average 2-year follow-up MOS-SF-36 physical score was increased (compared with mostly abstainers) in mostly heavy drinkers (+4.44, P = 0.007); no other variables tested influenced the MOS-SF-36 physical score. CONCLUSION: Among individuals with alcohol dependence, a rapid improvement was seen in the mental dimension of QOL following treatment initiation, which was maintained during 24 months. Improvement was associated with the pattern of alcohol use, becoming close to the general population norm in patients classified as mostly abstainers, improving substantially in mostly moderate drinkers and improving only slightly in mostly heavy drinkers. The physical dimension of QOL was generally in the normal range but was not associated with drinking patterns.

4B.05: Plasma Lasma copeptin is associated with insulin resistance in a Swiss population-based study

OBJECTIVE: Previous studies suggest that arginine vasopressin may have a role in metabolic syndrome (MetS) and diabetes by altering liver glycogenolysis, insulin, and glucagon secretion and pituitary ACTH release. We tested whether plasma copeptin, the stable C-terminal fragment of arginine vasopressin prohormone, was associated with insulin resistance and MetS in a Swiss population-based study. DESIGN AND METHOD: We analyzed data from the population-based Swiss Kidney Project on Genes in Hypertension. Copeptin was assessed by an immunoluminometric assay. Insulin resistance was derived from the HOMA model and calculated as follows: (FPI x FPG)/22.5, where FPI is fasting plasma insulin concentration (mU/L) and FPG fasting plasma glucose (mmol/L). Subjects were classified as having the MetS according to the National Cholesterol Education Program Adult Treatment Panel III criteria. Mixed multivariate linear regression models were built to explore the association of insulin resistance with copeptin. In addition, multivariate logistic regression models were built to explore the association between MetS and copeptin. In the two analyses, adjustment was done for age, gender, center, tobacco and alcohol consumption, socioeconomic status, physical activity, intake of fruits and vegetables and 24 h urine flow rate. Copeptin was log-transformed for the analyses. RESULTS: Among the 1,089 subjects included in this analysis, 47% were male. Mean (SD) age and body mass index were 47.4 (17.6) years 25.0 (4.5) kg/m2. The prevalence of MetS was 10.5%. HOMA-IR was higher in men (median 1.3, IQR 0.7-2.1) than in women (median 1.0, IQR 0.5-1.6,P < 0.0001). Plasma copeptin was higher in men (median 5.2, IQR 3.7-7.8 pmol/L) than in women (median 3.0, IQR 2.2-4.3 pmol/L), P < 0.0001. HOMA-IR was positively associated with log-copeptin after full adjustment (β (95% CI) 0.19 (0.09-0.29), P < 0.001). MetS was not associated with copeptin after full adjustment (P = 0.92). CONCLUSIONS: Insulin resistance, but not MetS, was associated with higher copeptin levels. Further studies should examine whether modifying pharmacologically the arginine vasopressin system might improve insulin resistance, thereby providing insight into the causal nature of this association.