983 resultados para Clemence, Roger D.
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The preparation and characterization of (Ph3AsOH)2[CuBr4] and [Cu(Ph3AsO)4][CuBr4] are reported (Ph3AsO = triphenylarsine oxide). Crystallographic analysis of the monoclinic crystals of (Ph3AsOH)2[CuBr4] (space group C2/c, a = 17.569 (3) Å, b = 13.090 (2) Å, c = 16.933 (2) Å, and β = 105.64 (2)°, R = 0.055 and Rw = 0.057) revealed the presence of compressed [CuBr4]2- tetrahedra of C2 symmetry with Cu-Br distances of 2.340 (1) and 2.437 (1) Å and trans-Br-Cu-Br angles of 139.2 (1) and 122.4 (1)°. The oxonium cations hydrogen bond to the bromine atoms involved in the longer Cu-Br bonds and the smaller trans-Br-Cu-Br angle. Single-crystal electronic and EPR spectra are interpreted in terms of the observed [CuBr4]2- geometry. Analysis of the electronic and EPR spectra of [Cu(Ph3AsO)4][CuBr4] led to the postulation of the presence of planar [Cu(Ph3AsO)4]2+ cations and distorted tetrahedral [CuBr4]2- anions. © 1992 American Chemical Society.
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Treatment guidelines recommend strong consideration of thrombolysis in patients with acute symptomatic pulmonary embolism (PE) that present with arterial hypotension or shock because of the high risk of death in this setting. For haemodynamically stable patients with PE, the categorization of risk for subgroups may assist with decision-making regarding PE therapy. Clinical models [e.g. Pulmonary Embolism Severity Index (PESI)] may accurately identify those at low risk of overall death in the first 3 months after the diagnosis of PE, and such patients might benefit from an abbreviated hospital stay or outpatient therapy. Though some evidence suggests that a subset of high-risk normotensive patients with PE may have a reasonable risk to benefit ratio for thrombolytic therapy, single markers of right ventricular dysfunction (e.g. echocardiography, spiral computed tomography, or brain natriuretic peptide testing) and myocardial injury (e.g. cardiac troponin T or I testing) have an insufficient positive predictive value for PE-specific mortality to drive decision-making toward such therapy. Recommendations for outpatient treatment or thrombolytic therapy for patients with PE necessitate further development of prognostic models and conduct of clinical trials that assess various treatment strategies.
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In haemodynamically stable patients with acute symptomatic pulmonary embolism (PE), studies have not evaluated the usefulness of combining the measurement of cardiac troponin, transthoracic echocardiogram (TTE), and lower extremity complete compression ultrasound (CCUS) testing for predicting the risk of PE-related death.
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HIV virulence, i.e. the time of progression to AIDS, varies greatly among patients. As for other rapidly evolving pathogens of humans, it is difficult to know if this variance is controlled by the genotype of the host or that of the virus because the transmission chain is usually unknown. We apply the phylogenetic comparative approach (PCA) to estimate the heritability of a trait from one infection to the next, which indicates the control of the virus genotype over this trait. The idea is to use viral RNA sequences obtained from patients infected by HIV-1 subtype B to build a phylogeny, which approximately reflects the transmission chain. Heritability is measured statistically as the propensity for patients close in the phylogeny to exhibit similar infection trait values. The approach reveals that up to half of the variance in set-point viral load, a trait associated with virulence, can be heritable. Our estimate is significant and robust to noise in the phylogeny. We also check for the consistency of our approach by showing that a trait related to drug resistance is almost entirely heritable. Finally, we show the importance of taking into account the transmission chain when estimating correlations between infection traits. The fact that HIV virulence is, at least partially, heritable from one infection to the next has clinical and epidemiological implications. The difference between earlier studies and ours comes from the quality of our dataset and from the power of the PCA, which can be applied to large datasets and accounts for within-host evolution. The PCA opens new perspectives for approaches linking clinical data and evolutionary biology because it can be extended to study other traits or other infectious diseases.
Molecular epidemiology reveals long-term changes in HIV type 1 subtype B transmission in Switzerland
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Sequence data from resistance testing offer unique opportunities to characterize the structure of human immunodeficiency virus (HIV) infection epidemics.
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This study aimed to assess the performance of two prognostic models-the European Society of Cardiology (ESC) model and the simplified Pulmonary Embolism Severity Index (sPESI)-in predicting short-term mortality in patients with pulmonary embolism (PE).
The role of migration and domestic transmission in the spread of HIV-1 non-B subtypes in Switzerland
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By analyzing human immunodeficiency virus type 1 (HIV-1) pol sequences from the Swiss HIV Cohort Study (SHCS), we explored whether the prevalence of non-B subtypes reflects domestic transmission or migration patterns.
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The time passed since the infection of a human immunodeficiency virus (HIV)-infected individual (the age of infection) is an important but often only poorly known quantity. We assessed whether the fraction of ambiguous nucleotides obtained from bulk sequencing as done for genotypic resistance testing can serve as a proxy of this parameter.
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The NMMAPS data package contains daily mortality, air pollution, and weather data originally assembled as part of the National Morbidity,Mortality, and Air Pollution Study (NMMAPS). The data have recently been updated and are available for 108 United States cities for the years 1987--2000. The package provides tools for building versions of the full database in a structured and reproducible manner. These database derivatives may be more suitable for particular analyses. We describe how to use the package to implement a multi-city time series analysis of mortality and PM(10). In addition we demonstrate how to reproduce recent findings based on the NMMAPS data.
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Visualization and exploratory analysis is an important part of any data analysis and is made more challenging when the data are voluminous and high-dimensional. One such example is environmental monitoring data, which are often collected over time and at multiple locations, resulting in a geographically indexed multivariate time series. Financial data, although not necessarily containing a geographic component, present another source of high-volume multivariate time series data. We present the mvtsplot function which provides a method for visualizing multivariate time series data. We outline the basic design concepts and provide some examples of its usage by applying it to a database of ambient air pollution measurements in the United States and to a hypothetical portfolio of stocks.
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We present the cacher and CodeDepends packages for R, which provide tools for (1) caching and analyzing the code for statistical analyses and (2) distributing these analyses to others in an efficient manner over the web. The cacher package takes objects created by evaluating R expressions and stores them in key-value databases. These databases of cached objects can subsequently be assembled into “cache packages” for distribution over the web. The cacher package also provides tools to help readers examine the data and code in a statistical analysis and reproduce, modify, or improve upon the results. In addition, readers can easily conduct alternate analyses of the data. The CodeDepends package provides complementary tools for analyzing and visualizing the code for a statistical analysis and this functionality has been integrated into the cacher package. In this chapter we describe the cacher and CodeDepends packages and provide examples of how they can be used for reproducible research.
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Quantifying the health effects associated with simultaneous exposure to many air pollutants is now a research priority of the US EPA. Bayesian hierarchical models (BHM) have been extensively used in multisite time series studies of air pollution and health to estimate health effects of a single pollutant adjusted for potential confounding of other pollutants and other time-varying factors. However, when the scientific goal is to estimate the impacts of many pollutants jointly, a straightforward application of BHM is challenged by the need to specify a random-effect distribution on a high-dimensional vector of nuisance parameters, which often do not have an easy interpretation. In this paper we introduce a new BHM formulation, which we call "reduced BHM", aimed at analyzing clustered data sets in the presence of a large number of random effects that are not of primary scientific interest. At the first stage of the reduced BHM, we calculate the integrated likelihood of the parameter of interest (e.g. excess number of deaths attributed to simultaneous exposure to high levels of many pollutants). At the second stage, we specify a flexible random-effect distribution directly on the parameter of interest. The reduced BHM overcomes many of the challenges in the specification and implementation of full BHM in the context of a large number of nuisance parameters. In simulation studies we show that the reduced BHM performs comparably to the full BHM in many scenarios, and even performs better in some cases. Methods are applied to estimate location-specific and overall relative risks of cardiovascular hospital admissions associated with simultaneous exposure to elevated levels of particulate matter and ozone in 51 US counties during the period 1999-2005.
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Time series models relating short-term changes in air pollution levels to daily mortality counts typically assume that the effects of air pollution on the log relative rate of mortality do not vary with time. However, these short-term effects might plausibly vary by season. Changes in the sources of air pollution and meteorology can result in changes in characteristics of the air pollution mixture across seasons. The authors develop Bayesian semi-parametric hierarchical models for estimating time-varying effects of pollution on mortality in multi-site time series studies. The methods are applied to the updated National Morbidity and Mortality Air Pollution Study database for the period 1987--2000, which includes data for 100 U.S. cities. At the national level, a 10 micro-gram/m3 increase in PM(10) at lag 1 is associated with a 0.15 (95% posterior interval: -0.08, 0.39),0.14 (-0.14, 0.42), 0.36 (0.11, 0.61), and 0.14 (-0.06, 0.34) percent increase in mortality for winter, spring, summer, and fall, respectively. An analysis by geographical regions finds a strong seasonal pattern in the northeast (with a peak in summer) and little seasonal variation in the southern regions of the country. These results provide useful information for understanding particle toxicity and guiding future analyses of particle constituent data.
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A time series is a sequence of observations made over time. Examples in public health include daily ozone concentrations, weekly admissions to an emergency department or annual expenditures on health care in the United States. Time series models are used to describe the dependence of the response at each time on predictor variables including covariates and possibly previous values in the series. Time series methods are necessary to account for the correlation among repeated responses over time. This paper gives an overview of time series ideas and methods used in public health research.
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BACKGROUND Human immunodeficiency virus type 1 (HIV-1) transmitted drug resistance (TDR) can compromise antiretroviral therapy (ART) and thus represents an important public health concern. Typically, sources of TDR remain unknown, but they can be characterized with molecular epidemiologic approaches. We used the highly representative Swiss HIV Cohort Study (SHCS) and linked drug resistance database (SHCS-DRDB) to analyze sources of TDR. METHODS ART-naive men who have sex with men with infection date estimates between 1996 and 2009 were chosen for surveillance of TDR in HIV-1 subtype B (N = 1674), as the SHCS-DRDB contains pre-ART genotypic resistance tests for >69% of this surveillance population. A phylogeny was inferred using pol sequences from surveillance patients and all subtype B sequences from the SHCS-DRDB (6934 additional patients). Potential sources of TDR were identified based on phylogenetic clustering, shared resistance mutations, genetic distance, and estimated infection dates. RESULTS One hundred forty of 1674 (8.4%) surveillance patients carried virus with TDR; 86 of 140 (61.4%) were assigned to clusters. Potential sources of TDR were found for 50 of 86 (58.1%) of these patients. ART-naive patients constitute 56 of 66 (84.8%) potential sources and were significantly overrepresented among sources (odds ratio, 6.43 [95% confidence interval, 3.22-12.82]; P < .001). Particularly large transmission clusters were observed for the L90M mutation, and the spread of L90M continued even after the near cessation of antiretroviral use selecting for that mutation. Three clusters showed evidence of reversion of K103N or T215Y/F. CONCLUSIONS Many individuals harboring viral TDR belonged to transmission clusters with other Swiss patients, indicating substantial domestic transmission of TDR in Switzerland. Most TDR in clusters could be linked to sources, indicating good surveillance of TDR in the SHCS-DRDB. Most TDR sources were ART naive. This, and the presence of long TDR transmission chains, suggests that resistance mutations are frequently transmitted among untreated individuals, highlighting the importance of early diagnosis and treatment.