Cardiac magnetic resonance findings predict increased resource utilization in elective coronary artery bypass grafting

Morbidity following CABG (coronary artery bypass grafting) is difficult to predict and leads to increased healthcare costs. We hypothesized that pre-operative CMR (cardiac magnetic resonance) findings would predict resource utilization in elective CABG. Over a 12-month period, patients requiring elective CABG were invited to undergo CMR 1 day prior to CABG. Gadolinium-enhanced CMR was performed using a trueFISP inversion recovery sequence on a 1.5 tesla scanner (Sonata; Siemens). Clinical data were collected prospectively. Admission costs were quantified based on standardized actual cost/day. Admission cost greater than the median was defined as 'increased'. Of 458 elective CABG cases, 45 (10%) underwent pre-operative CMR. Pre-operative characteristics [mean (S.D.) age, 64 (9) years, mortality (1%) and median (interquartile range) admission duration, 7 (6–8) days] were similar in patients who did or did not undergo CMR. In the patients undergoing CMR, eight (18%) and 11 (24%) patients had reduced LV (left ventricular) systolic function by CMR [LVEF (LV ejection fraction) <55%] and echocardiography respectively. LE (late enhancement) with gadolinium was detected in 17 (38%) patients. The average cost/day was $2723. The median (interquartile range) admission cost was$19059 ($10891–157917). CMR LVEF {OR (odds ratio), 0.93 [95% CI (confidence interval), 0.87–0.99]; P=0.03} and SV (stroke volume) index [OR 1.07 (95% CI, 1.00–1.14); P=0.02] predicted increased admission cost. CMR LVEF (P=0.08) and EuroScore tended to predict actual admission cost (P=0.09), but SV by CMR (P=0.16) and LV function by echocardiography (P=0.95) did not. In conclusion, in this exploratory investigation, pre-operative CMR findings predicted admission duration and increased admission cost in elective CABG surgery. The cost-effectiveness of CMR in risk stratification in elective CABG surgery merits prospective assessment

Technical considerations towards mobile user QoE enhancement via Cloud interaction

This paper discusses technical considerations of a Cloud infrastructure which interacts with mobile devices in order to migrate part of the computational overhead from the mobile device to the Cloud. The aim of the interaction between the mobile device and the Cloud is the enhancement of parameters that affect the Quality of Experience (QoE) of the mobile end user through the offloading of computational aspects of demanding applications. This paper shows that mobile user’s QoE can be potentially enhanced by offloading computational tasks to the Cloud which incorporates a predictive context-aware mechanism to schedule delivery of content to the mobile end-user using a low-cost interaction model between the Cloud and the mobile user. With respect to the proposed enhancements, both the technical considerations of the cloud infrastructure are examined, as well as the interaction between the mobile device and the Cloud

Continuous glucose monitoring sensors: Past, present and future algorithmic challenges

Continuous glucose monitoring (CGM) sensors are portable devices that allow measuring and visualizing the glucose concentration in real time almost continuously for several days and are provided with hypo/hyperglycemic alerts and glucose trend information. CGM sensors have revolutionized Type 1 diabetes (T1D) management, improving glucose control when used adjunctively to self-monitoring blood glucose systems. Furthermore, CGM devices have stimulated the development of applications that were impossible to create without a continuous-time glucose signal, e.g., real-time predictive alerts of hypo/hyperglycemic episodes based on the prediction of future glucose concentration, automatic basal insulin attenuation methods for hypoglycemia prevention, and the artificial pancreas. However, CGM sensors’ lack of accuracy and reliability limited their usability in the clinical practice, calling upon the academic community for the development of suitable signal processing methods to improve CGM performance. The aim of this paper is to review the past and present algorithmic challenges of CGM sensors, to show how they have been tackled by our research group, and to identify the possible future ones

Sustainable urban development in practice:the SAVE concept

The need for sustainable development of the urban environment presents the research community with a number of challenges and opportunities. A considerable volume of research has been undertaken into the constituent parts of this complex problem and a number of tool kits and methodologies have been developed to enable and encourage the application of specific aspects of research in practice. However, there is limited evidence of the holistic integration of the body of knowledge arising from the research within real-life decision-making practices. In this paper we present an overview of the existing body of knowledge relating to sustainable development of the urban environment and propose a generic framework for its integration within current practices. This framework recognises the need to: understand social, economic, and environmental issues; understand the decision-making processes; provide a means of measurement, assessment, or valuation of the issues; provide analytical methods for the comparative assessment of complex data to enable an evaluation of strategies and design options and to communicate effectively throughout the process with a wide range of stakeholders. The components of a novel sustainability assessment, visualisation and enhancement (SAVE) framework, developed by the authors to ‘operationalise’ the body of knowledge are presented and justified. These include: decision-mapping methods to identify points of intervention; indicator identification and measurement approaches; appropriate mathematical and analytical tools and an interactive simulation and visualisation platform which integrates and communicates complex multivariate information to diverse stakeholder groups. We report on the application of the SAVE framework to a major urban development project and reflect on its current and potential impact on the development. Conclusions are also drawn about its general applicability