Multicentre hospital drug utilization study on the prophylaxis of venous thromboembolism. The Venous Thromboembolism Study Group of the Spanish Society of Clinical Pharmacology.

1. Thromboembolic disease (TED) is an important cause of in-hospital morbidity and mortality. Although different prophylactic approaches have been shown to be effective and cost-effective, surveys have suggested that they are underused. The aim of this study was to estimate the prevalence of use of TED prophylaxis in our hospitals. 2. All patients admitted on a specified day to the Internal Medicine and General Surgery wards of seven Spanish university hospitals were included in the study. They were identified cross-sectionally and followed up until discharge or for 15 days. Information about the following variables was collected: risk factors for venous thromboembolism, prophylactic measures used (if any), contraindications to the use of each specific drug or other prophylactic measure, and dosage schedule of the drug used, if any. 3. Nine hundred and thirty-nine patients (53% men) were studied. The most common risk factors for venous thromboembolism were: age > or = 40 years (802; 85%), major surgery (298; 32%), immobilization > or = 6 days (285; 30%), obesity (241; 26%), and cancer (202; 22%). 4. Prophylactic measures were used in 320 patients (34%). Of these, 297 (93%) received heparin, mainly as low molecular weight heparins (248, 78%); physical measures were rarely used. 5. Five hundred and eighty-three patients (62%) fulfilled criteria for moderate or high risk of venous thromboembolism; only 275 (47%) of them received any form of prophylaxis.(ABSTRACT TRUNCATED AT 250 WORDS)     

Breast Density Analysis Using an Automatic Density Segmentation Algorithm

Breast density is a strong risk factor for breast cancer. In this paper, we present an automated approach for breast density segmentation in mammographic images based on a supervised pixel-based classification and using textural and morphological features. The objective of the paper is not only to show the feasibility of an automatic algorithm for breast density segmentation but also to prove its potential application to the study of breast density evolution in longitudinal studies. The database used here contains three complete screening examinations, acquired 2 years apart, of 130 different patients. The approach was validated by comparing manual expert annotations with automatically obtained estimations. Transversal analysis of the breast density analysis of craniocaudal (CC) and mediolateral oblique (MLO) views of both breasts acquired in the same study showed a correlation coefficient of ρ = 0.96 between the mammographic density percentage for left and right breasts, whereas a comparison of both mammographic views showed a correlation of ρ = 0.95. A longitudinal study of breast density confirmed the trend that dense tissue percentage decreases over time, although we noticed that the decrease in the ratio depends on the initial amount of breast density.     

Impact of heterogeneity and socioeconomic factors on individual behavior in decentralized sharing ecosystems

Tens of millions of individuals around the world use decentralized content distribution systems, a fact of growing social, economic, and technological importance. These sharing systems are poorly understood because, unlike in other technosocial systems, it is difficult to gather large-scale data about user behavior. Here, we investigate user activity patterns and the socioeconomic factors that could explain the behavior. Our analysis reveals that (i) the ecosystem is heterogeneous at several levels: content types are heterogeneous, users specialize in a few content types, and countries are heterogeneous in user profiles; and (ii) there is a strong correlation between socioeconomic indicators of a country and users behavior. Our findings open a research area on the dynamics of decentralized sharing ecosystems and the socioeconomic factors affecting them, and may have implications for the design of algorithms and for policymaking.Every month, ∼150 million users worldwide share files over the Internet using BitTorrent (1), the most widely used decentralized peer-to-peer (P2P) communication protocol. Eleven years after its inception, file sharing through BitTorrent is one of the top three major contributors to the overall Internet traffic, accounting for 9–27% of the total traffic, depending on the continent (2, 3).The expansion in scale and breadth of decentralized file-sharing has highlighted the conflicts between the interests of creators (musicians and writers, e.g.) and those of P2P users. Creators and creative industries argue that they are being deprived of fair compensation for their work (4), which is being widely distributed for free in violation of copyright laws. Users, however, argue that P2P can be (and is) used for sharing nonproprietary contents, and warn that widespread monitoring of online activity by corporations and law enforcement violates P2P users’ right to privacy. Proof of the complexity of the situation includes the rejection of the Anti-Counterfeiting Trade Agreement by the European Parliament and the controversy with the Stop Online Piracy Act in the United States.Despite the growing social, economic, and technological importance of BitTorrent (4), there is currently little understanding of how users behave in this complex technosocial (5, 6) ecosystem. Due to the decentralized structure of P2P ecosystems, it is very difficult to gather large-scale data about interactions and behavioral patterns of the users without their explicit consent; this is in contrast to other forms of online exchange where all of the information is stored in a central system, be it publicly accessible as in Wikipedia (7), partially accessible through a public interface as in Twitter (8, 9) or Google [through its search logs (10) or its public services (11, 12)], or restricted as in Facebook (13, 14) or in email communications within organizations (15–18).Because of the difficulty to collect complete user-level data of large and representative samples of users (3), studies of user behavior in P2P networks have so far been based on (i) small datasets; (ii) aggregate data collected from “trackers” or from individual Internet service providers (ISPs); and (iii) incomplete user data collected using a single crawler client connected to the network (19–23).Here, we investigate the complete activity patterns of a large and representative pool of BitTorrent users. Our analysis reveals that P2P sharing is highly heterogeneous, that users are specialized, giving rise to well-defined user profiles, and that the abundance of certain user profiles in a country is highly correlated with socioeconomic factors. Our findings open a research area on the dynamics of decentralized sharing ecosystems, and may have implications for the understanding and design of algorithms and for policymaking.     

A built-in co-carcinogenic effect due to viruses involved in latent or persistent infections

A new hypothesis for some cancers, which combines the chromosomal instability theories with a co-carcinogenic effect of viruses causing latent or persistent infection, is presented. The hypothesis incorporates the multi-step model of cancer and that pre-cancerous cells reach a state of chromosomal instability. Because of chromosomal instability, the genome of these cell lines will lead to changes from generation to generation and will face a remarkable selection pressure both from lost traits, apoptosis, and from the immune system. Viruses causing latent or persistent infections have evolved many different genes capable to evade the immune system. If these viruses are harboured in the genome of pre-cancerous cells they could provide them with "superpowers" and with genes that may assist the cells to elude the immune system. The theory explains why cancer predominantly is a disease of old age. Upon aging, the immune system becomes reduced including the ability to control and suppress the viruses that cause latent or persistent infections. The risk of cancer could thereby increase as the immune functions decrease. The theory provides new insights to the genesis of cancers.