Atlas interactivo de mortalidad de Andalucía (AIMA)

Until now, mortality atlases have been static. Most of them describe the geographical distribution of mortality using count data aggregated over time and standardized mortality rates. However, this methodology has several limitations. Count data aggregated over time produce a bias in the estimation of death rates. Moreover, this practice difficult the study of temporal changes in geographical distribution of mortality. On the other hand, using standardized mortality hamper to check differences in mortality among groups. The Interactive Mortality Atlas in Andalusia (AIMA) is an alternative to conventional static atlases. It is a dynamic Geographical Information System that allows visualizing in web-site more than 12.000 maps and 338.00 graphics related to the spatio-temporal distribution of the main death causes in Andalusia by age and sex groups from 1981. The objective of this paper is to describe the methods used for AIMA development, to show technical specifications and to present their interactivity. The system is available from the link products in www.demap.es. AIMA is the first interactive GIS that have been developed in Spain with these characteristics. Spatio-temporal Hierarchical Bayesian Models were used for statistical data analysis. The results were integrated into web-site using a PHP environment and a dynamic cartography in Flash. Thematic maps in AIMA demonstrate that the geographical distribution of mortality is dynamic, with differences among year, age and sex groups. The information nowadays provided by AIMA and the future updating will contribute to reflect on the past, the present and the future of population health in Andalusia.

Three-year multicenter surveillance of community-acquired Listeria monocytogenes meningitis in adults

BACKGROUND. Listeria monocytogenes is the third most frequent cause of bacterial meningitis. The aim of this study is to know the incidence and risk factors associated with development of acute community-acquired Lm meningitis in adult patients and to evaluate the clinical features, management, and outcome in this prospective case series. METHODS. A descriptive, prospective, and multicentric study carried out in 9 hospitals in the Spanish Network for Research in Infectious Diseases (REIPI) over a 39-month period. All adults patients admitted to the participating hospitals with the diagnosis of acute community-acquired bacterial meningitis (Ac-ABM) were included in this study. All these cases were diagnosed on the basis of a compatible clinical picture and a positive cerebrospinal fluid (CSF) culture or blood culture. The patients were followed up until death or discharge from hospital. RESULTS. Two hundred and seventy-eight patients with Ac-ABM were included. Forty-six episodes of Lm meningitis were identified in 46 adult patients. In the multivariate analysis only age (OR 1.026; 95% CI 1.00-1.05; p = 0.042), immunosuppression (OR 2.520; 95% CI 1.05-6.00; p = 0.037), and CSF/blood glucose ratio (OR 39.42; 95% CI 4.01-387.50; p = 0.002) were independently associated with a Lm meningitis. The classic triad of fever, neck stiffness and altered mental status was present in 21 (49%) patients, 32% had focal neurological findings at presentation, 12% presented cerebellum dysfunction, and 9% had seizures. Twenty-nine (68%) patients were immunocompromised. Empirical antimicrobial therapy was intravenous ampicillin for 34 (79%) of 43 patients, in 11 (32%) of them associated to aminoglycosides. Definitive ampicillin plus gentamicin therapy was significantly associated with unfavourable outcome (67% vs 28%; p = 0.024) and a higher mortality (67% vs 32%; p = 0.040).The mortality rate was 28% (12 of 43 patients) and 5 of 31 (16.1%) surviving patients developed adverse clinical outcome. CONCLUSIONS Elderly or immunocompromised patients, and a higher CSF/blood glucose ratio in patients with Ac-ABM must alert clinicians about Lm aetiology. Furthermore, we observed a high incidence of acute community-acquired Lm meningitis in adults and the addition of aminoglycosides to treatment should be avoid in order to improve the patients' outcome. Nevertheless, despite developments in intensive care and antimicrobial therapy, this entity is still a serious disease that carries high morbidity and mortality rates.

Scoring Methods for Ordinal Multidimensional Forced-Choice Items

In most psychological tests and questionnaires, a test score is obtained bytaking the sum of the item scores. In virtually all cases where the test orquestionnaire contains multidimensional forced-choice items, this traditionalscoring method is also applied. We argue that the summation of scores obtained with multidimensional forced-choice items produces uninterpretabletest scores. Therefore, we propose three alternative scoring methods: a weakand a strict rank preserving scoring method, which both allow an ordinalinterpretation of test scores; and a ratio preserving scoring method, whichallows a proportional interpretation of test scores. Each proposed scoringmethod yields an index for each respondent indicating the degree to whichthe response pattern is inconsistent. Analysis of real data showed that withrespect to rank preservation, the weak and strict rank preserving methodresulted in lower inconsistency indices than the traditional scoring method;with respect to ratio preservation, the ratio preserving scoring method resulted in lower inconsistency indices than the traditional scoring method

Comparing methods for dimensionality reduction when data are density functions

Functional Data Analysis (FDA) deals with samples where a whole function is observedfor each individual. A particular case of FDA is when the observed functions are densityfunctions, that are also an example of infinite dimensional compositional data. In thiswork we compare several methods for dimensionality reduction for this particular typeof data: functional principal components analysis (PCA) with or without a previousdata transformation and multidimensional scaling (MDS) for diferent inter-densitiesdistances, one of them taking into account the compositional nature of density functions. The difeerent methods are applied to both artificial and real data (householdsincome distributions)

Dynamic graphics of parametrically linked multivariate methods used in compositional data analysis

Many multivariate methods that are apparently distinct can be linked by introducing oneor more parameters in their definition. Methods that can be linked in this way arecorrespondence analysis, unweighted or weighted logratio analysis (the latter alsoknown as "spectral mapping"), nonsymmetric correspondence analysis, principalcomponent analysis (with and without logarithmic transformation of the data) andmultidimensional scaling. In this presentation I will show how several of thesemethods, which are frequently used in compositional data analysis, may be linkedthrough parametrizations such as power transformations, linear transformations andconvex linear combinations. Since the methods of interest here all lead to visual mapsof data, a "movie" can be made where where the linking parameter is allowed to vary insmall steps: the results are recalculated "frame by frame" and one can see the smoothchange from one method to another. Several of these "movies" will be shown, giving adeeper insight into the similarities and differences between these methods

Statistical treatment of grain-size curves and empirical distributions: densities as compositions?

The preceding two editions of CoDaWork included talks on the possible considerationof densities as infinite compositions: Egozcue and D´ıaz-Barrero (2003) extended theEuclidean structure of the simplex to a Hilbert space structure of the set of densitieswithin a bounded interval, and van den Boogaart (2005) generalized this to the setof densities bounded by an arbitrary reference density. From the many variations ofthe Hilbert structures available, we work with three cases. For bounded variables, abasis derived from Legendre polynomials is used. For variables with a lower bound, westandardize them with respect to an exponential distribution and express their densitiesas coordinates in a basis derived from Laguerre polynomials. Finally, for unboundedvariables, a normal distribution is used as reference, and coordinates are obtained withrespect to a Hermite-polynomials-based basis.To get the coordinates, several approaches can be considered. A numerical accuracyproblem occurs if one estimates the coordinates directly by using discretized scalarproducts. Thus we propose to use a weighted linear regression approach, where all k-order polynomials are used as predictand variables and weights are proportional to thereference density. Finally, for the case of 2-order Hermite polinomials (normal reference)and 1-order Laguerre polinomials (exponential), one can also derive the coordinatesfrom their relationships to the classical mean and variance.Apart of these theoretical issues, this contribution focuses on the application of thistheory to two main problems in sedimentary geology: the comparison of several grainsize distributions, and the comparison among different rocks of the empirical distribution of a property measured on a batch of individual grains from the same rock orsediment, like their composition

Bacteremia due to extended-spectrum beta-lactamase-producing Escherichia coli in the CTX-M era: a new clinical challenge.

Extended-spectrum beta-lactamase (ESBL)-producing Escherichia coli, particularly those producing CTX-M types of ESBL, are emerging pathogens. Bacteremia caused by these organisms represents a clinical challenge, because the organisms are frequently resistant to the antimicrobials recommended for treatment of patients with suspected E. coli sepsis. METHODS:A cohort study was performed that included all episodes of bloodstream infection due to ESBL-producing E. coli during the period from January 2001 through March 2005. Data on predisposing factors, clinical presentation, and outcome were collected. ESBLs were characterized using isoelectric focusing, polymerase chain reaction, and sequencing. RESULTS: Forty-three episodes (8.8% of cases of bacteremia due to E. coli) were included; 70% of the isolates produced a CTX-M type of ESBL. The most frequent origins of infection were the urinary (46%) and biliary tracts (21%). Acquisition was nosocomial in 21 cases (49%), health care associated in 14 cases (32%), and strictly community acquired in 8 cases (19%). Thirty-eight percent and 25% of patients had obstructive diseases of the urinary and biliary tracts, respectively, and 38% had recently received antimicrobials. Nine patients (21%) died. Compared with beta-lactam/beta-lactamase-inhibitor and carbapenem-based regimens, empirical therapy with cephalosporins or fluoroquinolones was associated with a higher mortality rate (9% vs. 35%; P=.05) and needed to be changed more frequently (24% vs. 78%; P=.001). CONCLUSIONS: ESBL-producing E. coli is a significant cause of bloodstream infection in hospitalized and nonhospitalized patients in the context of the emergence of CTX-M enzymes. Empirical treatment of sepsis potentially caused by E. coli may need to be reconsidered in areas where such ESBL-producing isolates are present.

Population pharmacokinetics and effects of efavirenz in patients with human immunodeficiency virus infection.

OBJECTIVE: The reverse transcriptase inhibitor efavirenz is currently used at a fixed dose of 600 mg/d. However, dosage individualization based on plasma concentration monitoring might be indicated. This study aimed to assess the efavirenz pharmacokinetic profile and interpatient versus intrapatient variability in patients who are positive for human immunodeficiency virus, to explore the relationship between drug exposure, efficacy, and central nervous system toxicity and to build up a Bayesian approach for dosage adaptation. METHODS: The population pharmacokinetic analysis was performed by use of NONMEM based on plasma samples from a cohort of unselected patients receiving efavirenz. With the use of a 1-compartment model with first-order absorption, the influence of demographic and clinical characteristics on oral clearance and oral volume of distribution was examined. The average drug exposure during 1 dosing interval was estimated for each patient and correlated with markers of efficacy and toxicity. The population kinetic parameters and the variabilities were integrated into a Bayesian equation for dosage adaptation based on a single plasma sample. RESULTS: Data from 235 patients with a total of 719 efavirenz concentrations were collected. Oral clearance was 9.4 L/h, oral volume of distribution was 252 L, and the absorption rate constant was 0.3 h(-1). Neither the demographic covariates evaluated nor the comedications showed a clinically significant influence on efavirenz pharmacokinetics. A large interpatient variability was found to affect efavirenz relative bioavailability (coefficient of variation, 54.6%), whereas the intrapatient variability was small (coefficient of variation, 26%). An inverse correlation between average drug exposure and viral load and a trend with central nervous system toxicity were detected. This enabled the derivation of a dosing adaptation strategy suitable to bring the average concentration into a therapeutic target from 1000 to 4000 microg/L to optimize viral load suppression and to minimize central nervous system toxicity. CONCLUSIONS: The high interpatient and low intrapatient variability values, as well as the potential relationship with markers of efficacy and toxicity, support the therapeutic drug monitoring of efavirenz. However, further evaluation is needed before individualization of an efavirenz dosage regimen based on routine drug level monitoring should be recommended for optimal patient management.

Testing of Diagnostic Methods for Detection of Influenza Virusfor Optimal Performance in the Context of an Influenza Surveillance Network

Influenza surveillance networks must detect early the viruses that will cause the forthcoming annual epidemics and isolate the strains for further characterization. We obtained the highest sensitivity (95.4%) with a diagnostic tool that combined a shell-vial assay and reverse transcription-PCR on cell culture supernatants at 48 h, and indeed, recovered the strain

Autonomous underwater vehicle control using reinforcement learning policy search methods

Autonomous underwater vehicles (AUV) represent a challenging control problem with complex, noisy, dynamics. Nowadays, not only the continuous scientific advances in underwater robotics but the increasing number of subsea missions and its complexity ask for an automatization of submarine processes. This paper proposes a high-level control system for solving the action selection problem of an autonomous robot. The system is characterized by the use of reinforcement learning direct policy search methods (RLDPS) for learning the internal state/action mapping of some behaviors. We demonstrate its feasibility with simulated experiments using the model of our underwater robot URIS in a target following task

Methods for testing association between uncertain genotypes and quantitative traits.

Interpretability and power of genome-wide association studies can be increased by imputing unobserved genotypes, using a reference panel of individuals genotyped at higher marker density. For many markers, genotypes cannot be imputed with complete certainty, and the uncertainty needs to be taken into account when testing for association with a given phenotype. In this paper, we compare currently available methods for testing association between uncertain genotypes and quantitative traits. We show that some previously described methods offer poor control of the false-positive rate (FPR), and that satisfactory performance of these methods is obtained only by using ad hoc filtering rules or by using a harsh transformation of the trait under study. We propose new methods that are based on exact maximum likelihood estimation and use a mixture model to accommodate nonnormal trait distributions when necessary. The new methods adequately control the FPR and also have equal or better power compared to all previously described methods. We provide a fast software implementation of all the methods studied here; our new method requires computation time of less than one computer-day for a typical genome-wide scan, with 2.5 M single nucleotide polymorphisms and 5000 individuals.

Moderating effects of management control systems and innovation on performance. Simple methods for correcting the effects of measurement error for interaction effects in small samples

In the accounting literature, interaction or moderating effects are usually assessed by means of OLS regression and summated rating scales are constructed to reduce measurement error bias. Structural equation models and two-stage least squares regression could be used to completely eliminate this bias, but large samples are needed. Partial Least Squares are appropriate for small samples but do not correct measurement error bias. In this article, disattenuated regression is discussed as a small sample alternative and is illustrated on data of Bisbe and Otley (in press) that examine the interaction effect of innovation and style of use of budgets on performance. Sizeable differences emerge between OLS and disattenuated regression

Municipal distribution of bladder cancer mortality in Spain: Possible role of mining and industry

BACKGROUND Spain shows the highest bladder cancer incidence rates in men among European countries. The most important risk factors are tobacco smoking and occupational exposure to a range of different chemical substances, such as aromatic amines. METHODS This paper describes the municipal distribution of bladder cancer mortality and attempts to "adjust" this spatial pattern for the prevalence of smokers, using the autoregressive spatial model proposed by Besag, York and Molliè, with relative risk of lung cancer mortality as a surrogate. RESULTS It has been possible to compile and ascertain the posterior distribution of relative risk for bladder cancer adjusted for lung cancer mortality, on the basis of a single Bayesian spatial model covering all of Spain's 8077 towns. Maps were plotted depicting smoothed relative risk (RR) estimates, and the distribution of the posterior probability of RR>1 by sex. Towns that registered the highest relative risks for both sexes were mostly located in the Provinces of Cadiz, Seville, Huelva, Barcelona and Almería. The highest-risk area in Barcelona Province corresponded to very specific municipal areas in the Bages district, e.g., Suría, Sallent, Balsareny, Manresa and Cardona. CONCLUSION Mining/industrial pollution and the risk entailed in certain occupational exposures could in part be dictating the pattern of municipal bladder cancer mortality in Spain. Population exposure to arsenic is a matter that calls for attention. It would be of great interest if the relationship between the chemical quality of drinking water and the frequency of bladder cancer could be studied.