Fabio N. Demarqui

The Diagnostic Accuracy of Serologic and Molecular Methods for Detecting Visceral Leishmaniasis in HIV Infected Patients: Meta-Analysis

Background Human visceral leishmaniasis (VL), a potentially fatal disease, has emerged as an important opportunistic condition in HIV infected patients. In immunocompromised patients, serological investigation is considered not an accurate diagnostic method for VL diagnosis and molecular techniques seem especially promising. Objective This work is a comprehensive systematic review and meta-analysis to evaluate the accuracy of serologic and molecular tests for VL diagnosis specifically in HIV-infected patients. Methods Two independent reviewers searched PubMed and LILACS databases. The quality of studies was assessed by QUADAS score. Sensitivity and specificity were pooled separately and compared with overall accuracy measures: diagnostic odds ratio (DOR) and symmetric summary receiver operating characteristic (sROC). Results Thirty three studies recruiting 1,489 patients were included. The following tests were evaluated: Immunofluorescence Antibody Test (IFAT), Enzyme linked immunosorbent assay (ELISA), immunoblotting (Blot), direct agglutination test (DAT) and polimerase chain reaction (PCR) in whole blood and bone marrow. Most studies were carried out in Europe. Serological tests varied widely in performance, but with overall limited sensitivity. IFAT had poor sensitivity ranging from 11% to 82%. DOR (95% confidence interval) was higher for DAT 36.01 (9.95–130.29) and Blot 27.51 (9.27–81.66) than for IFAT 7.43 (3.08–1791) and ELISA 3.06 (0.71–13.10). PCR in whole blood had the highest DOR: 400.35 (58.47–2741.42). The accuracy of PCR based on Q-point was 0.95; 95%CI 0.92–0.97, which means good overall performance. Conclusion Based mainly on evidence gained by infection with Leishmania infantum chagasi, serological tests should not be used to rule out a diagnosis of VL among the HIV-infected, but a positive test at even low titers has diagnostic value when combined with the clinical case definition. Considering the available evidence, tests based on DNA detection are highly sensitive and may contribute to a diagnostic workup.

Estimating the grid of time-points for the piecewise exponential model

One of the greatest challenges related to the use of piecewise exponential models (PEMs) is to find an adequate grid of time-points needed in its construction. In general, the number of intervals in such a grid and the position of their endpoints are ad-hoc choices. We extend previous works by introducing a full Bayesian approach for the piecewise exponential model in which the grid of time-points (and, consequently, the endpoints and the number of intervals) is random. We estimate the failure rates using the proposed procedure and compare the results with the non-parametric piecewise exponential estimates. Estimates for the survival function using the most probable partition are compared with the Kaplan–Meier estimators (KMEs). A sensitivity analysis for the proposed model is provided considering different prior specifications for the failure rates and for the grid. We also evaluate the effect of different percentage of censoring observations in the estimates. An application to a real data set is also provided. We notice that the posteriors are strongly influenced by prior specifications, mainly for the failure rates parameters. Thus, the priors must be fairly built, say, really disclosing the expert prior opinion.

Fully semiparametric Bayesian approach for modeling survival data with cure fraction.

In this paper, we consider a piecewise exponential model (PEM) with random time grid to develop a full semiparametric Bayesian cure rate model. An elegant mechanism enjoying several attractive features for modeling the randomness of the time grid of the PEM is assumed. To model the prior behavior of the failure rates of the PEM we assume a hierarchical modeling approach that allows us to control the degree of parametricity in the right tail of the survival curve. Properties of the proposed model are discussed in detail. In particular, we investigate the impact of assuming a random time grid for the PEM on the estimation of the cure fraction. We further develop an efficient collapsed Gibbs sampler algorithm for carrying out posterior computation. A Bayesian diagnostic method for assessing goodness of fit and performing model comparisons is briefly discussed. Finally, we illustrate the usefulness of the new methodology with the analysis of a melanoma clinical trial that has been discussed in the literature.

Risks and Benefits of Thrombolytic, Antiplatelet, and Anticoagulant Therapies for ST Segment Elevation Myocardial Infarction: Systematic Review

Objectives. Assess the impact of associating thrombolytics, anticoagulants, antiplatelets, and primary angioplasty (PA) on death, reinfarction (AMI), and major bleeding (MB) in STEMI therapy. Methods. Medline search was performed to identify randomized trials comparing these classes in STEMI treatment, at least 500 patients, providing death, AMI, and MB rates. Similar arms were grouped. Correlation between number of drugs and PA and the outcomes was evaluated, as well as correlation between the year of the study and the outcomes. Results. Fifty-nine papers remained after exclusions. 404.556 patients were divided into 35 groups of arms. There was correlation between the number of drugs and rates of death (r = −0.466, P = 0.005) and MB (r = 0.403, P = 0.016), confirmed by multivariate regression. This model also showed that PA is associated with lower mortality and increased MB. Year and period of publication correlated with the outcomes: death (r = −0.380, P < 0.001), MB (r = 0.212, P = 0.014), and AMI (r = −0.231, P = 0.009). Conclusion. The increasing complexity of STEMI treatment has resulted in significant reduction in mortality along with increased rates of MB. Overall, however, the benefits of treatment outweigh the associated risks of MB.

A general GEE framework for the analysis of longitudinal ordinal missing data and related issues

Generalized estimating equations (GEEs) are a well-known method for the analysis of categorical longitudinal data. This method presents computational simplicity and provides consistent parameter estimates that have a population-averaged interpretation. However, with missing data, the resulting parameter estimates are consistent only under the strong assumption of missing completely at random (MCAR). Some corrections can be done when the missing data mechanism is missing at random (MAR): inverse probability weighting GEE (WGEE) and multiple imputation GEE (MIGEE). A recent method combining ideas of these two approaches has a doubly robust property in the sense that one only needs to correctly specify the weight or the imputation model in order to obtain consistent estimates for the parameters. In this work, a proportional odds model is assumed and a doubly robust estimator is proposed for the analysis of ordinal longitudinal data with intermittently missing responses and covariates under the MAR mechanism. In addition, the association structure is modelled by means of either the correlation coefficient or local odds ratio. The performance of the proposed method is compared to both WGEE and MIGEE through a simulation study. The method is applied to a dataset related to rheumatic mitral stenosis.

Environmental factors on virulence of Aeromonas hydrophila

Aeromonas hydrophila are known for being opportunistic pathogens, harboring various virulence factors and triggering lesions and death in fish. The disease caused by bacteria can make fish inappropriate for human consumption, besides representing a risk to public health. The pathogenesis can be influenced by environmental variables, affecting fish productivity and mortality. The present study aimed to determine whether A. hydrophila harbor the virulence genes aerolysin, hydrolipase, elastase, lipase, cytotonic enterotoxin (ast), lateral flagellum (laf), and polar flagellum (fla) and to evaluate the influence of environmental variables on in vitro growth, in vivo virulence and expression of some of these genes. Polymerase chain reaction (PCR)-based screening for the presence of these virulence genes was performed on 35 isolates. Six isolates containing different profiles of virulence genes were tested for in vitro growth under different conditions of pH, temperature, and ammonia and for in vivo virulence under these same environmental conditions. RT-qPCR was used to quantify the expression of aerolysin, lipase, and fla genes. All the tested environmental factors influenced the growth of A. hydrophila, while pH and ammonia concentrations influenced the bacterial virulence. The expression of the fla gene increased when bacteria were grown in higher ammonia concentration. The mortality established by Aeromonas is influenced by several environmental factors pinpointing the importance of its control in fish farming to avoid higher economic loses associated to bacterial disease outbreaks.

Factors associated with progression of coronary artery disease measured by intravascular ultrasound: Systematic review and meta-analysis

a Servico de Cardiologia e Cirurgia Cardiovascular do Hospital das Clinicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil b Departamento de Clinica Medica da Faculdade de Medicina, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil c Programa de Pos-graduacao em Ciencias Aplicadas a Saude do Adulto, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil d Instituto de Ciencias Exatas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil e Department of Medico-Surgical Sciences and Biotechnologies, Sapienza University of Rome, Italy f Erasmus University Medical Centre, Thoraxcenter, Rotterdam, the Netherlands g Harrington Heart and Vascular Institute, University Hospitals Case Medical Center, and Case Western Reserve University, Cleveland, USA

PROGRESSION OF NATIVE CORONARY ARTERY DISEASE MEASURED BY INTRAVASCULAR ULTRASOUND: SYSTEMATIC REVIEW AND META–ANALYSIS

Much effort has been made to understand the mechanisms and to develop therapies to prevent progression of atherosclerosis. Intravascular ultrasound (IVUS) has been widely used to evaluate plaque progression in response to specific therapies, but there has been no systematic analysis of pooled data