Association between Angiotensin-Converting Enzyme Inhibitors and Troponin in Acute Coronary Syndrome

Background:Cardiovascular disease is the leading cause of mortality in the western world and its treatment should be optimized to decrease severe adverse events.Objective:To determine the effect of previous use of angiotensin-converting enzyme inhibitors on cardiac troponin I measurement in patients with acute coronary syndrome without ST-segment elevation and evaluate clinical outcomes at 180 days.Methods:Prospective, observational study, carried out in a tertiary center, in patients with acute coronary syndrome without ST-segment elevation. Clinical, electrocardiographic and laboratory variables were analyzed, with emphasis on previous use of angiotensin-converting enzyme inhibitors and cardiac troponin I. The Pearson chi-square tests (Pereira) or Fisher's exact test (Armitage) were used, as well as the non-parametric Mann-Whitney's test. Variables with significance levels of <10% were submitted to multiple logistic regression model.Results:A total of 457 patients with a mean age of 62.1 years, of whom 63.7% were males, were included. Risk factors such as hypertension (85.3%) and dyslipidemia (75.9%) were the most prevalent, with 35% of diabetics. In the evaluation of events at 180 days, there were 28 deaths (6.2%). The statistical analysis showed that the variables that interfered with troponin elevation (> 0.5 ng / mL) were high blood glucose at admission (p = 0.0034) and ST-segment depression ≥ 0.5 mm in one or more leads (p = 0.0016). The use of angiotensin-converting inhibitors prior to hospitalization was associated with troponin ≤ 0.5 ng / mL (p = 0.0482). The C-statistics for this model was 0.77.Conclusion:This study showed a correlation between prior use of angiotensin-converting enzyme inhibitors and reduction in the myocardial necrosis marker troponin I in patients admitted for acute coronary syndrome without ST-segment elevation. However, there are no data available yet to state that this reduction could lead to fewer severe clinical events such as death and re-infarction at 180 days.

Experimental design for mixed models with application to population pharmacokinetic studies

experimental design, mixed model, random coefficient regression model, population pharmacokinetics, approximate design

Left Atrial Volume Determinants in Patients with Non-Ischemic Dilated Cardiomyopathy

Background:Left atrial volume (LAV) is a predictor of prognosis in patients with heart failure.Objective:We aimed to evaluate the determinants of LAV in patients with dilated cardiomyopathy (DCM).Methods:Ninety patients with DCM and left ventricular (LV) ejection fraction ≤ 0.50 were included. LAV was measured with real-time three-dimensional echocardiography (eco3D). The variables evaluated were heart rate, systolic blood pressure, LV end-diastolic volume and end-systolic volume and ejection fraction (eco3D), mitral inflow E wave, tissue Doppler e´ wave, E/e´ ratio, intraventricular dyssynchrony, 3D dyssynchrony index and mitral regurgitation vena contracta. Pearson´s coefficient was used to identify the correlation of the LAV with the assessed variables. A multiple linear regression model was developed that included LAV as the dependent variable and the variables correlated with it as the predictive variables.Results:Mean age was 52 ± 11 years-old, LV ejection fraction: 31.5 ± 8.0% (16-50%) and LAV: 39.2±15.7 ml/m2. The variables that correlated with the LAV were LV end-diastolic volume (r = 0.38; p < 0.01), LV end-systolic volume (r = 0.43; p < 0.001), LV ejection fraction (r = -0.36; p < 0.01), E wave (r = 0.50; p < 0.01), E/e´ ratio (r = 0.51; p < 0.01) and mitral regurgitation (r = 0.53; p < 0.01). A multivariate analysis identified the E/e´ ratio (p = 0.02) and mitral regurgitation (p = 0.02) as the only independent variables associated with LAV increase.Conclusion:The LAV is independently determined by LV filling pressures (E/e´ ratio) and mitral regurgitation in DCM.

Sex Differences in High Sensitivity C-Reactive Protein in Subjects with Risk Factors of Metabolic Syndrome

Abstract Background: Metabolic syndrome (MetS) is associated with a higher risk of all-cause mortality. High-sensitivity C-reactive protein (hsCRP) is a prototypic marker of inflammation usually increased in MetS. Women with MetS-related diseases present higher hsCRP levels than men with MetS-related diseases, suggesting sex differences in inflammatory markers. However, it is unclear whether serum hsCRP levels are already increased in men and/or women with MetS risk factors and without overt diseases or under pharmacological treatment. Objective: To determine the impact of the number of MetS risk factors on serum hsCRP levels in women and men. Methods One hundred and eighteen subjects (70 men and 48 women; 36 ± 1 years) were divided into four groups according to the number of MetS risk factors: healthy group (CT; no risk factors), MetS ≤ 2, MetS = 3, and MetS ≥ 4. Blood was drawn after 12 hours of fasting for measurement of biochemical variables and hsCRP levels, which were determined by immunoturbidimetric assay. Results: The groups with MetS risk factors presented higher serum hsCRP levels when compared with the CT group (p < 0.02). There were no differences in hsCRP levels among groups with MetS risk factors (p > 0.05). The best linear regression model to explain the association between MetS risk factors and hsCRP levels included waist circumference and HDL cholesterol (r = 0.40, p < 0.01). Women with MetS risk factors presented higher hsCRP levels when compared with men (psex < 0.01). Conclusions: Despite the absence of overt diseases and pharmacological treatment, subjects with MetS risk factors already presented increased hsCRP levels, which were significantly higher in women than men at similar conditions.

Human capital spillovers, productivity and regional convergence in Spain

This paper analyses the differential impact of human capital, in terms of different levels of schooling, on regional productivity and convergence. The potential existence of geographical spillovers of human capital is also considered by applying spatial panel data techniques. The empirical analysis of Spanish provinces between 1980 and 2007 confirms the positive impact of human capital on regional productivity and convergence, but reveals no evidence of any positive geographical spillovers of human capital. In fact, in some specifications the spatial lag presented by tertiary studies has a negative effect on the variables under consideration.

General Practitioners' willingness to pay for continuing medical education in a fee-for-service universal coverage health care system

Background: Sponsoring of physicians meetings by life science companies has led to reduced participation fees but might influence physician's prescription practices. A ban on such sponsoring may increase participation fees. We aimed to evaluate factors associated with physicians' willingness to pay for medical meetings, their position on the sponsoring of medical meetings and their opinion on alternative financing options. Methods: An anonymous web-based questionnaire was sent to 447 general practitioners in one state in Switzerland, identified through their affiliation to a medical association. The questionnaire evaluated physicians' willingness to pay for medical meetings, their perception of a bias in prescription practices induced by commercial support, their opinion on the introduction of a binding legislation and alternative financing options, their frequency of exchange with sales representatives and other relevant socioeconomic factors. We built a multivariate predictor logistic regression model to identify determinants of willingness to pay. Results: Of the 115 physicians who responded (response rate 26%), 48% were willing to pay more than what they currently pay for congresses, 79% disagreed that commercial support introduced a bias in their prescription practices and 61% disagreed that it introduced a bias in their colleagues' prescription practices. Based on the multivariate logistic regression, perception of a bias in peers prescription practices (OR=7.47, 95% CI 1.65-38.18) and group practice structure (OR=4.62, 95% CI 1.34-22.29) were significantly associated with an increase in willingness to pay. Two thirds (76%) of physicians did not support the introduction of a binding legislation and 53% were in favour of creating a general fund administered by an independent body. Conclusion: Our results suggest that almost half of physicians surveyed are willing to pay more than what they currently pay for congresses. Predictors of an increase in physicians' willingness to pay were perception of the influence of bias in peers prescription practices and group practice structure. Most responders did not agree that sponsoring introduced prescribing bias nor did they support the 2 introduction of a binding legislation prohibiting sponsoring but a majority did agree to an independent body that would centrally administer a general fund.

Forecast of acute respiratory infections: expected nonepidemic mobidity in Cuba

A forecast of nonepidemic morbidity due to acute respiratory infections were carry out by using time series analysis. The data consisted of the weekly reports of medical patient consultation from ambulatory facilities from the whole country. A version of regression model was fitted to the data. Using this approach, we were able to detect the starting data of the epidemic under routine surveillance conditions for various age groups. It will be necessary to improve the data reporting system in order to introduce these procedures at the local health center level, as well as on the provincial level.

Detecting epistasis with restricted response patterns in pairs of biallelic loci.

Well-established examples of genetic epistasis between a pair of loci typically show characteristic patterns of phenotypic distributions in joint genotype tables. However, inferring epistasis given such data is difficult due to the lack of power in commonly used approaches, which decompose the epistatic patterns into main plus interaction effects followed by testing the interaction term. Testing additive-only or all terms may have more power, but they are sensitive to nonepistatic patterns. Alternatively, the epistatic patterns of interest can be enumerated and the best matching one is found by searching through the possibilities. Although this approach requires multiple testing correction over possible patterns, each pattern can be fitted with a regression model with just one degree of freedom and thus the overall power can still be high, if the number of possible patterns is limited. Here we compare the power of the linear decomposition and pattern search methods, by applying them to simulated data generated under several patterns of joint genotype effects with simple biological interpretations. Interaction-only tests are the least powerful; while pattern search approach is the most powerful if the range of possibilities is restricted, but still includes the true pattern.

Validity of serology for American Trypanosomiasis with eluates from filter paper

This study evaluates whether blood collected on filter paper kept at 4 degrees C and tested at different intervals of time (1, 7, 15, 30 and 60 days after collection) would present similar results when compared to the serum samples and whether the type of filter paper influences the results. Eluates from filter paper samples were tested for Trypanosoma cruzi antibodies using indirect immunofluorescence antibody test (IFAT), indirect haemagglutination (IHA) and enzyme-linked immunosorbent assay (ELISA) as reference, the antibody titer in sera. Analysis of data showed that results obtained with IFAT, IHA (cut off point = 1:40) and ELISA in sera had similar sensitivity and good concordance among reactions. The use of a multiple linear regression model indicated that titer fall in eluates occurs up to the 7th day after the collection, and it is more marked for samples with lower antibodies titers. However, no significant differences were observed by IFAT, IHA (cut off point = 1:20) and ELISA in the proportion of positive reactions between sera and eluates. The results also showed that Melitta, Klabin or Whatman (reference) filter papers could be indicated for surveys, since they have shown similar capacity of maintenance of anti-T. cruzi immunoglobulins.

Does grade retention affect achievement? Some evidence from PISA

Grade retention practices are at the forefront of the educational debate. In this paper, we use PISA 2009 data for Spain to measure the effect of grade retention on students’ achievement. One important problem when analyzing this question is that school outcomes and the propensity to repeat a grade are likely to be determined simultaneously. We address this problem by estimating a Switching Regression Model. We …find that grade retention has a negative impact on educational outcomes, but we confi…rm the importance of endogenous selection, which makes observed differences between repeaters and non-repeaters appear 14.6% lower than they actually are. The effect on PISA scores of repeating is much smaller (-10% of non-repeaters’ average) than the counterfactual reduction that non-repeaters would suffer had they been retained as repeaters (-24% of their average). Furthermore, those who repeated a grade during primary education suffered more than those who repeated a grade of secondary school, although the effect of repeating at both times is, as expected, much larger.

Risk factors for positive tuberculin skin tests among migrant and resident children in Lausanne, Switzerland.

SETTING: Ambulatory paediatric clinic in Lausanne, Switzerland, a country with a significant proportion of tuberculosis (TB) among immigrants. AIM: To assess the factors associated with positive tuberculin skin tests (TST) among children examined during a health check-up or during TB contact tracing, notably the influence of BCG vaccination (Bacille Calmette Guérin) and history of TB contact. METHOD: A descriptive study of children who had a TST (2 Units RT23) between November 2002 and April 2004. Age, sex, history of TB contact, BCG vaccination status, country of origin and birth outside Switzerland were recorded. RESULTS: Of 234 children, 176 (75%) had a reaction equal to zero and 31 (13%) tested positive (>10 mm). In a linear regression model, the size of the TST varied significantly according to the history of TB contact, age, TB incidence in the country of origin and BCG vaccination status but not according to sex or birth in or outside Switzerland. In a logistic regression model including all the recorded variables, age (Odds Ratio = 1.21, 95% CI 1.08; 1.35), a history of TB contact (OR = 7.31, 95% CI 2.23; 24) and the incidence of TB in the country of origin (OR = 1.01, 95% CI 1.00; 1.02) were significantly associated with a positive TST but sex (OR = 1.18, 95% CI 0.50; 2.78) and BCG vaccination status (OR = 2.97, 95% CI 0.91; 9.72) were not associated. CONCLUSIONS: TB incidence in the country of origin, BCG vaccination and age influence the TSTreaction (size or proportion of TST > or = 10 mm). However the most obvious risk factor for a positive TST is a history of contact with TB.

Quantitative integration of geophysical and hydraulic data : from the local towards the regional scale range

Des progrès significatifs ont été réalisés dans le domaine de l'intégration quantitative des données géophysique et hydrologique l'échelle locale. Cependant, l'extension à de plus grandes échelles des approches correspondantes constitue encore un défi majeur. Il est néanmoins extrêmement important de relever ce défi pour développer des modèles fiables de flux des eaux souterraines et de transport de contaminant. Pour résoudre ce problème, j'ai développé une technique d'intégration des données hydrogéophysiques basée sur une procédure bayésienne de simulation séquentielle en deux étapes. Cette procédure vise des problèmes à plus grande échelle. L'objectif est de simuler la distribution d'un paramètre hydraulique cible à partir, d'une part, de mesures d'un paramètre géophysique pertinent qui couvrent l'espace de manière exhaustive, mais avec une faible résolution (spatiale) et, d'autre part, de mesures locales de très haute résolution des mêmes paramètres géophysique et hydraulique. Pour cela, mon algorithme lie dans un premier temps les données géophysiques de faible et de haute résolution à travers une procédure de réduction déchelle. Les données géophysiques régionales réduites sont ensuite reliées au champ du paramètre hydraulique à haute résolution. J'illustre d'abord l'application de cette nouvelle approche dintégration des données à une base de données synthétiques réaliste. Celle-ci est constituée de mesures de conductivité hydraulique et électrique de haute résolution réalisées dans les mêmes forages ainsi que destimations des conductivités électriques obtenues à partir de mesures de tomographic de résistivité électrique (ERT) sur l'ensemble de l'espace. Ces dernières mesures ont une faible résolution spatiale. La viabilité globale de cette méthode est testée en effectuant les simulations de flux et de transport au travers du modèle original du champ de conductivité hydraulique ainsi que du modèle simulé. Les simulations sont alors comparées. Les résultats obtenus indiquent que la procédure dintégration des données proposée permet d'obtenir des estimations de la conductivité en adéquation avec la structure à grande échelle ainsi que des predictions fiables des caractéristiques de transports sur des distances de moyenne à grande échelle. Les résultats correspondant au scénario de terrain indiquent que l'approche d'intégration des données nouvellement mise au point est capable d'appréhender correctement les hétérogénéitées à petite échelle aussi bien que les tendances à gande échelle du champ hydraulique prévalent. Les résultats montrent également une flexibilté remarquable et une robustesse de cette nouvelle approche dintégration des données. De ce fait, elle est susceptible d'être appliquée à un large éventail de données géophysiques et hydrologiques, à toutes les gammes déchelles. Dans la deuxième partie de ma thèse, j'évalue en détail la viabilité du réechantillonnage geostatique séquentiel comme mécanisme de proposition pour les méthodes Markov Chain Monte Carlo (MCMC) appliquées à des probmes inverses géophysiques et hydrologiques de grande dimension . L'objectif est de permettre une quantification plus précise et plus réaliste des incertitudes associées aux modèles obtenus. En considérant une série dexemples de tomographic radar puits à puits, j'étudie deux classes de stratégies de rééchantillonnage spatial en considérant leur habilité à générer efficacement et précisément des réalisations de la distribution postérieure bayésienne. Les résultats obtenus montrent que, malgré sa popularité, le réechantillonnage séquentiel est plutôt inefficace à générer des échantillons postérieurs indépendants pour des études de cas synthétiques réalistes, notamment pour le cas assez communs et importants où il existe de fortes corrélations spatiales entre le modèle et les paramètres. Pour résoudre ce problème, j'ai développé un nouvelle approche de perturbation basée sur une déformation progressive. Cette approche est flexible en ce qui concerne le nombre de paramètres du modèle et lintensité de la perturbation. Par rapport au rééchantillonage séquentiel, cette nouvelle approche s'avère être très efficace pour diminuer le nombre requis d'itérations pour générer des échantillons indépendants à partir de la distribution postérieure bayésienne. - Significant progress has been made with regard to the quantitative integration of geophysical and hydrological data at the local scale. However, extending corresponding approaches beyond the local scale still represents a major challenge, yet is critically important for the development of reliable groundwater flow and contaminant transport models. To address this issue, I have developed a hydrogeophysical data integration technique based on a two-step Bayesian sequential simulation procedure that is specifically targeted towards larger-scale problems. The objective is to simulate the distribution of a target hydraulic parameter based on spatially exhaustive, but poorly resolved, measurements of a pertinent geophysical parameter and locally highly resolved, but spatially sparse, measurements of the considered geophysical and hydraulic parameters. To this end, my algorithm links the low- and high-resolution geophysical data via a downscaling procedure before relating the downscaled regional-scale geophysical data to the high-resolution hydraulic parameter field. I first illustrate the application of this novel data integration approach to a realistic synthetic database consisting of collocated high-resolution borehole measurements of the hydraulic and electrical conductivities and spatially exhaustive, low-resolution electrical conductivity estimates obtained from electrical resistivity tomography (ERT). The overall viability of this method is tested and verified by performing and comparing flow and transport simulations through the original and simulated hydraulic conductivity fields. The corresponding results indicate that the proposed data integration procedure does indeed allow for obtaining faithful estimates of the larger-scale hydraulic conductivity structure and reliable predictions of the transport characteristics over medium- to regional-scale distances. The approach is then applied to a corresponding field scenario consisting of collocated high- resolution measurements of the electrical conductivity, as measured using a cone penetrometer testing (CPT) system, and the hydraulic conductivity, as estimated from electromagnetic flowmeter and slug test measurements, in combination with spatially exhaustive low-resolution electrical conductivity estimates obtained from surface-based electrical resistivity tomography (ERT). The corresponding results indicate that the newly developed data integration approach is indeed capable of adequately capturing both the small-scale heterogeneity as well as the larger-scale trend of the prevailing hydraulic conductivity field. The results also indicate that this novel data integration approach is remarkably flexible and robust and hence can be expected to be applicable to a wide range of geophysical and hydrological data at all scale ranges. In the second part of my thesis, I evaluate in detail the viability of sequential geostatistical resampling as a proposal mechanism for Markov Chain Monte Carlo (MCMC) methods applied to high-dimensional geophysical and hydrological inverse problems in order to allow for a more accurate and realistic quantification of the uncertainty associated with the thus inferred models. Focusing on a series of pertinent crosshole georadar tomographic examples, I investigated two classes of geostatistical resampling strategies with regard to their ability to efficiently and accurately generate independent realizations from the Bayesian posterior distribution. The corresponding results indicate that, despite its popularity, sequential resampling is rather inefficient at drawing independent posterior samples for realistic synthetic case studies, notably for the practically common and important scenario of pronounced spatial correlation between model parameters. To address this issue, I have developed a new gradual-deformation-based perturbation approach, which is flexible with regard to the number of model parameters as well as the perturbation strength. Compared to sequential resampling, this newly proposed approach was proven to be highly effective in decreasing the number of iterations required for drawing independent samples from the Bayesian posterior distribution.

Treatment of severe infectious purpura in children with human plasma from donors immunized with Escherichia coli J5: a prospective double-blind study. J5 study Group.

To evaluate the efficacy of anti-J5 serum in the treatment of severe infectious purpura, 73 children were randomized to receive either anti-J5 (40) or control (33) plasma. Age, blood pressure, and biologic risk factors were similar in both groups. At admission, however, tumor necrosis factor serum concentrations were 974 +/- 173 pg/ml compared with 473 +/- 85 pg/ml (P = .023) and interleukin-6 serum concentrations were 129 +/- 45 compared with 19 +/- 5 ng/ml (P = .005) in the control and treated groups, respectively. The duration of shock and the occurrence of complications were similar in both groups. The mortality rate was 36% in the control group and 25% in the treated group (P = .317; odds ratio, 0.76; 95% confidence interval, 0.46-1.26). This trend disappeared after correction for unbalances in risk factors at randomization using a logistic regression model. These results suggest that anti-j5 plasma did not affect the course or mortality of severe infectious purpura in children.

Clinical presentation and survival of smear-positive pulmonary tuberculosis patients of a University General Hospital in a developing country

From January 1995 to August 1997 we evaluated prospectively the clinical presentation, laboratory findings and short-term survival of smear-positive pulmonary tuberculosis (TB) patients who sought care at our hospital. After providing informed, written consent, the patients were interviewed and laboratory tests were performed. Information about survivorship and death was collected through September 1998. Eighty-six smear-positive pulmonary TB patients were enrolled; 26.7% were HIV-seropositive. Seventeen HIV-seronegative pulmonary TB patients (19.8%) presented chronic diseases in addition to TB. In the multiple logistic regression analysis a CD4+ cell count <= 200 cell/mm³ was independently associated with HIV seropositivity. In the Cox regression model, fitted to all patients, HIV seropositivity and age > or = 50 years were independently associated with decreased survival. Among HIV-seronegative persons, the presence of an additional disease increased the risk of death of almost six-fold. Use of antiretroviral drugs was associated with a lower risk of death among HIV-seropositive smear-positive pulmonary TB patients (RH = 0.32, 95% CI 0.10-0.92). In our study smear-positive pulmonary TB patients had a low short-term survival rate that was strongly associated with HIV infection, age and co-morbidities. Therapy with antiretroviral drugs reduced the short-term risk of death among HIV-seropositive patients after TB diagnosis.

Combining probabilistic land-use change and tree population dynamics modelling to simulate responses in mountain forests

Altitudinal tree lines are mainly constrained by temperature, but can also be influenced by factors such as human activity, particularly in the European Alps, where centuries of agricultural use have affected the tree-line. Over the last decades this trend has been reversed due to changing agricultural practices and land-abandonment. We aimed to combine a statistical land-abandonment model with a forest dynamics model, to take into account the combined effects of climate and human land-use on the Alpine tree-line in Switzerland. Land-abandonment probability was expressed by a logistic regression function of degree-day sum, distance from forest edge, soil stoniness, slope, proportion of employees in the secondary and tertiary sectors, proportion of commuters and proportion of full-time farms. This was implemented in the TreeMig spatio-temporal forest model. Distance from forest edge and degree-day sum vary through feed-back from the dynamics part of TreeMig and climate change scenarios, while the other variables remain constant for each grid cell over time. The new model, TreeMig-LAb, was tested on theoretical landscapes, where the variables in the land-abandonment model were varied one by one. This confirmed the strong influence of distance from forest and slope on the abandonment probability. Degree-day sum has a more complex role, with opposite influences on land-abandonment and forest growth. TreeMig-LAb was also applied to a case study area in the Upper Engadine (Swiss Alps), along with a model where abandonment probability was a constant. Two scenarios were used: natural succession only (100% probability) and a probability of abandonment based on past transition proportions in that area (2.1% per decade). The former showed new forest growing in all but the highest-altitude locations. The latter was more realistic as to numbers of newly forested cells, but their location was random and the resulting landscape heterogeneous. Using the logistic regression model gave results consistent with observed patterns of land-abandonment: existing forests expanded and gaps closed, leading to an increasingly homogeneous landscape.