Comparison of vancomycin and linezolid in patients with peripheral vascular disease and/or diabetes in an observational European study of complicated skin and soft-tissue infections due to methicillin-resistant <i>Staphylococcus aureus</i>

AbstractSuboptimal antibiotic penetration into soft tissues can occur in patients with poor circulation due to peripheral vascular disease (PVD) or diabetes. We conducted a real-world analysis of antibiotic treatment, hospital resource use and clinical outcomes in patients with PVD and/or diabetes receiving linezolid or vancomycin for the treatment of methicillin-resistant Staphylococcus aureus complicated skin and soft-tissue infections (MRSA cSSTIs) across Europe. This subgroup analysis evaluated data obtained from a retrospective, observational medical chart review study that captured patient data from 12 European countries. Data were obtained from the medical records of patients ≥ 18 years of age, hospitalized with an MRSA cSSTI between 1 July 2010 and 30 June 2011 and discharged alive by 31 July 2011. Hospital length of stay and length of treatment were compared between the treatment groups using inverse probability of treatment weights to adjust for clinical and demographic differences. A total of 485 patients had PVD or diabetes and received treatment with either vancomycin (n = 258) or linezolid (n = 227). After adjustment, patients treated with linezolid compared with vancomycin respectively had significantly shorter hospital stays (17.9 ± 13.6 vs. 22.6 ± 13.6 days; p < 0.001) and treatment durations (12.9 ± 7.9 vs. 16.4 ± 8.3 days; p < 0.001). The proportions of patients prescribed oral, MRSA-active antibiotics at discharge were 43.2% and 12.4% of patients in the linezolid and vancomycin groups, respectively (p < 0.001). The reduction in resource use may result in lower hospital costs for patients with PVD and/or diabetes and MRSA cSSTIs if treated with linezolid compared with vancomycin

The listening talker: A review of human and algorithmic context-induced modifications of speech

International audienceSpeech output technology is finding widespread application, including in scenarios where intelligibility might be compromised - at least for some listeners - by adverse conditions. Unlike most current algorithms, talkers continually adapt their speech patterns as a response to the immediate context of spoken communication, where the type of interlocutor and the environment are the dominant situational factors influencing speech production. Observations of talker behaviour can motivate the design of more robust speech output algorithms. Starting with a listener-oriented categorisation of possible goals for speech modification, this review article summarises the extensive set of behavioural findings related to human speech modification, identifies which factors appear to be beneficial, and goes on to examine previous computational attempts to improve intelligibility in noise. The review concludes by tabulating 46 speech modifications, many of which have yet to be perceptually or algorithmically evaluated. Consequently, the review provides a roadmap for future work in improving the robustness of speech output

Usability and digital inclusion: standards and guidelines

This article aims at discussing e-government website usability in relation to concerns about digital inclusion. E-government web design should consider all aspects of usability, including those that make it more accessible to all. Traditional concerns of social exclusion are being superseded by fears that lack of digital competence and information literacy may result in dangerous digital exclusion. Usability is considered as a way to address this exclusion and should therefore incorporate inclusion and accessibility guidelines. This article makes an explicit link between usability guidelines and digital inclusion and reports on a survey of local government web presence in Portugal

Commercial Serological Antibody Detection Tests for the Diagnosis of Pulmonary Tuberculosis: A Systematic Review

Based on a systematic review, Madhukar Pai and colleagues conclude that none of the commercial immune-based tests for pulmonary tuberculosis so far evaluated perform well enough to replace sputum smear microscopy

Modeling latent information in voting data with Dirichlet process priors

We apply a specialized Bayesian method that helps us deal with the methodological challenge of unobserved heterogeneity among immigrant voters. Our approach is based on generalized linear mixed Dirichlet models (GLMDMs) where random effects are specified semiparametrically using a Dirichlet process mixture prior that has been shown to account for unobserved grouping in the data. Such models are drawn from Bayesian nonparametrics to help overcome objections handling latent effects with strongly informed prior distributions. Using 2009 German voting data of immigrants, we show that for difficult problems of missing key covariates and unexplained heterogeneity this approach provides (1) overall improved model fit, (2) smaller standard errors on average, and (3) less bias from omitted variables. As a result, the GLMDM changed our substantive understanding of the factors affecting immigrants’ turnout and vote choice. Once we account for unobserved heterogeneity among immigrant voters, whether a voter belongs to the first immigrant generation or not is much less important than the extant literature suggests. When looking at vote choice, we also found that an immigrant’s degree of structural integration does not affect the vote in favor of the CDU/CSU, a party that is traditionally associated with restrictive immigration policy