58 research outputs found
An Evaluation of the Effectiveness of Risk Minimization Measures for Tigecycline in the European Union
Background: Risk minimization measures (RMM) were implemented from February 2011 in the European Union to address risks of superinfection, off-label use and lack of efficacy associated with tigecycline. The objective of this study was to evaluate RMM effectiveness by describing prescription patterns among adults and children treated with any dose of tigecycline for any indication pre- and post-RMM implementation; incidence proportions of superinfection and lack of efficacy among adults treated with approved doses of tigecycline for complicated intra-abdominal infection and complicated skin and soft tissue infection were also evaluated. Methods: This was an observational, retrospective chart-abstraction study, including charts from 777 patients (399 pre-RMM, 378 post-RMM) at 13 sites across Austria, Germany, Italy, Greece and the United Kingdom (UK). Potential superinfection and lack of efficacy cases among those using tigecycline for on-label indication, age, dose, and duration were adjudicated. The distribution of indications for tigecycline was analyzed overall (i.e. across both study periods) and stratified by study period. Numbers and incidence proportions of superinfection and lack of efficacy cases (potential and adjudicated) were calculated overall and by study period. Results: Off-label use (indication or age) decreased from 54.2% [95% confidence interval (95% CI): 49.0, 59.3%] pre-RMM to 35.7% (95% CI 30.4, 41.2%) post-RMM. Overall, 45.7% (95% CI 41.9, 49.5%) of patients were prescribed tigecycline off-label; the most commonly reported off-label indications were characterized as \u201cother\u201d (25.5%), hospital acquired pneumonia (8.2%), other pneumonia (6.3%), bacteremia (5.2%) and diabetic foot infection (1.5%). Across study periods, incidence proportions of definite or probable superinfection and lack of efficacy in adults treated for approved indications, authorized treatment doses and duration were 4.5% (95% CI 2.1, 8.4%) and 5.5% (95% CI 2.8, 9.7%), respectively. Conclusions: Off-label use of tigecycline decreased following RMM implementation. Overall incidence proportions of definite or probable superinfection and lack of efficacy were low. EU PAS register number: EUPAS3674
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Generic, network schema agnostic sparse tensor factorization for single-pass clustering of heterogeneous information networks
Heterogeneous information networks (e.g. bibliographic networks and social media networks) that consist of multiple interconnected objects are ubiquitous. Clustering analysis is an effective method to understand the semantic information and interpretable structure of the heterogeneous information networks, and it has attracted the attention of many researchers in recent years. However, most studies assume that heterogeneous information networks usually follow some simple schemas, such as bi-typed networks or star network schema, and they can only cluster one type of object in the network each time. In this paper, a novel clustering framework is proposed based on sparse tensor factorization for heterogeneous information networks, which can cluster multiple types of objects simultaneously in a single pass without any network schema information. The types of objects and the relations between them in the heterogeneous information networks are modeled as a sparse tensor. The clustering issue is modeled as an optimization problem, which is similar to the well-known Tucker decomposition. Then, an Alternating Least Squares (ALS) algorithm and a feasible initialization method are proposed to solve the optimization problem. Based on the tensor factorization, we simultaneously partition different types of objects into different clusters. The experimental results on both synthetic and real-world datasets have demonstrated that our proposed clustering framework, STFClus, can model heterogeneous information networks efficiently and can outperform state-of-the-art clustering algorithms as a generally applicable single-pass clustering method for heterogeneous network which is network schema agnostic
Core matrix rotation to natural zeros in three-mode factor analysis
This paper presents a new rotation method to simplify the interpretation of the core matrix in three-mode factor analysis. The rotated solution is compared, theoretically and empirically, with the TUCKALS solution (Kroonenberg, 1994)
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