Outcomes after endovascular or open repair for degenerative descending thoracic aortic aneurysm using linked hospital data.

BACKGROUND The population-based effectiveness of thoracic endovascular aortic repair (TEVAR) versus open surgery for descending thoracic aortic aneurysm remains in doubt. METHODS Patients aged over 50 years, without a history of aortic dissection, undergoing repair of a thoracic aortic aneurysm between 2006 and 2011 were assessed using mortality-linked individual patient data from Hospital Episode Statistics (England). The principal outcomes were 30-day operative mortality, long-term survival (5 years) and aortic-related reinterventions. TEVAR and open repair were compared using crude and multivariable models that adjusted for age and sex. RESULTS Overall, 759 patients underwent thoracic aortic aneurysm repair, mainly for intact aneurysms (618, 81·4 per cent). Median ages of TEVAR and open cohorts were 73 and 71 years respectively (P < 0·001), with more men undergoing TEVAR (P = 0·004). For intact aneurysms, the operative mortality rate was similar for TEVAR and open repair (6·5 versus 7·6 per cent; odds ratio 0·79, 95 per cent confidence interval (c.i.) 0·41 to 1·49), but the 5-year survival rate was significantly worse after TEVAR (54·2 versus 65·6 per cent; adjusted hazard ratio 1·45, 95 per cent c.i. 1·08 to 1·94). After 5 years, aortic-related mortality was similar in the two groups, but cardiopulmonary mortality was higher after TEVAR. TEVAR was associated with more aortic-related reinterventions (23·1 versus 14·3 per cent; adjusted HR 1·70, 95 per cent c.i. 1·11 to 2·60). There were 141 procedures for ruptured thoracic aneurysm (97 TEVAR, 44 open), with TEVAR showing no significant advantage in terms of operative mortality. CONCLUSION In England, operative mortality for degenerative descending thoracic aneurysm was similar after either TEVAR or open repair. Patients who had TEVAR appeared to have a higher reintervention rate and worse long-term survival, possibly owing to cardiopulmonary morbidity and other selection bias.

Measuring the promise of open data: Development of the Impact Monitoring Framework

It is a challenge to measure the impact of releasing data to the public since the effects may not be directly linked to particular open data activities or substantial impact may only occur several years after publishing the data. This paper proposes a framework to assess the impact of releasing open data by applying the Social Return on Investment (SROI) approach. SROI was developed for organizations intended to generate social and environmental benefits thus fitting the purpose of most open data initiatives. We link the four steps of SROI (input, output, outcome, impact) with the 14 high-value data categories of the G8 Open Data Charter to create a matrix of open data examples, activities, and impacts in each of the data categories. This Impact Monitoring Framework helps data providers to navigate the impact space of open data laying out the conceptual basis for further research.

Creating a public tool to assess and promote transparency in global land deals: the experience of the Land Matrix

The Beta version of the Land Matrix (Land Matrix 2012) was launched in April 2012 as a tool to promote public participation in building a constantly evolving database on large-scale land deals, and making the data visible and understandable. The aim of the Land Matrix partnership is to promote transparency and open data in decisionmaking over land and investment, as a step towards greater accountability. Since its launch, the Land Matrix has attracted a high degree of attention, and stirred some controversy. It provides valuable lessons on the challenges and benefits of promoting open data on practices that are often shrouded in secrecy. This paper critically examines the ongoing efforts by the Land Matrix partnership to build a public tool to promote greater transparency in decision-making over land and investment at a global level. It intends to provoke discussion of the extent to which such a tool can ultimately promote greater transparency and be a step towards greater accountability and improved decision-making. It will present the Land Matrix and its value addition, before detailing the challenges it encountered related to the measurement of the largescale land acquisition phenomenon. It will then specify how it intends to address these issues in order to establish a dynamic and participatory tool for open development.

REST-based sensor networks with OData

RESTful services gained a lot of attention recently, even in the enterprise world, which is traditionally more web-service centric. Data centric RESfFul services, as previously mainly known in web environments, established themselves as a second paradigm complementing functional WSDL-based SOA. In the Internet of Things, and in particular when talking about sensor motes, the Constraint Application Protocol (CoAP) is currently in the focus of both research and industry. In the enterprise world a protocol called OData (Open Data Protocol) is becoming the future RESTful data access standard. To integrate sensor motes seamlessly into enterprise networks, an embedded OData implementation on top of CoAP is desirable, not requiring an intermediary gateway device. In this paper we introduce and evaluate an embedded OData implementation. We evaluate the OData protocol in terms of performance and energy consumption, considering different data encodings, and compare it to a pure CoAP implementation. We were able to demonstrate that the additional resources needed for an OData/JSON implementation are reasonable when aiming for enterprise interoperability, where OData is suggested to solve both the semantic and technical interoperability problems we have today when connecting systems

Risk attribution of Campylobacter infection by age group using exposure modelling

Knowledge on the relative importance of alternative sources of human campylobacteriosis is important in order to implement effective disease prevention measures. The objective of this study was to assess the relative importance of three key exposure pathways (travelling abroad, poultry meat, pet contact) for different patient age groups in Switzerland. With a stochastic exposure model data on Campylobacter incidence for the years 2002-2007 were linked with data for the three exposure pathways and the results of a case-control study. Mean values for the population attributable fractions (PAF) over all age groups and years were 27% (95% CI 17-39) for poultry consumption, 27% (95% CI 22-32) for travelling abroad, 8% (95% CI 6-9) for pet contact and 39% (95% CI 25-50) for other risk factors. This model provided robust results when using data available for Switzerland, but the uncertainties remained high. The output of the model could be improved if more accurate input data are available to estimate the infection rate per exposure. In particular, the relatively high proportion of cases attributed to 'other risk factors' requires further attention.

From big smartphone data to worldwide research: The Mobile Data Challenge

This paper presents an overview of the Mobile Data Challenge (MDC), a large-scale research initiative aimed at generating innovations around smartphone-based research, as well as community-based evaluation of mobile data analysis methodologies. First, we review the Lausanne Data Collection Campaign (LDCC), an initiative to collect unique longitudinal smartphone dataset for the MDC. Then, we introduce the Open and Dedicated Tracks of the MDC, describe the specific datasets used in each of them, discuss the key design and implementation aspects introduced in order to generate privacy-preserving and scientifically relevant mobile data resources for wider use by the research community, and summarize the main research trends found among the 100+ challenge submissions. We finalize by discussing the main lessons learned from the participation of several hundred researchers worldwide in the MDC Tracks.