Changes in renal function after nephroureterectomy for upper urinary tract carcinoma: analysis of a large multicenter cohort (Radical Nephroureterectomy Outcomes (RaNeO) Research Consortium)

Purpose To investigate prevalence and predictors of renal function variation in a multicenter cohort treated with radical nephroureterectomy (RNU) for upper tract urothelial carcinoma (UTUC). Methods Patients from 17 tertiary centers were included. Renal function variation was evaluated at postoperative day (POD)-1, 6 and 12 months. Timepoints differences were Delta 1 = POD-1 eGFR - baseline eGFR; Delta 2 = 6 months eGFR - POD-1 eGFR; Delta 3 = 12 months eGFR - 6 months eGFR. We defined POD-1 acute kidney injury (AKI) as an increase in serum creatinine by >= 0.3 mg/dl or a 1.5 1.9-fold from baseline. Additionally, a cutoff of 60 ml/min in eGFR was considered to define renal function decline at 6 and 12 months. Logistic regression (LR) and linear mixed (LM) models were used to evaluate the association between clinical factors and eGFR decline and their interaction with follow-up. Results A total of 576 were included, of these 409(71.0%) and 403(70.0%) had an eGFR < 60 ml/min at 6 and 12 months, respectively, and 239(41.5%) developed POD-1 AKI. In multivariable LR analysis, age (Odds Ratio, OR 1.05, p < 0.001), male gender (OR 0.44, p = 0.003), POD-1 AKI (OR 2.88, p < 0.001) and preoperative eGFR < 60 ml/min (OR 7.58, p < 0.001) were predictors of renal function decline at 6 months. Age (OR 1.06, p < 0.001), coronary artery disease (OR 2.68, p = 0.007), POD-1 AKI (OR 1.83, p = 0.02), and preoperative eGFR < 60 ml/min (OR 7.80, p < 0.001) were predictors of renal function decline at 12 months. In LM models, age (p = 0.019), hydronephrosis (p < 0.001), POD-1 AKI (p < 0.001) and pT-stage (p = 0.001) influenced renal function variation (ss 9.2 +/- 0.7, p < 0.001) during follow-up. Conclusion Age, preoperative eGFR and POD-1 AKI are independent predictors of 6 and 12 months renal function decline after RNU for UTUC

Effectiveness of dietary interventions among adults of retirement age: a systematic review and meta-analysis of randomized controlled trials

Background Retirement from work involves significant lifestyle changes and may represent an opportunity to promote healthier eating patterns in later life. However, the effectiveness of dietary interventions during this period has not been evaluated. Methods We undertook a systematic review of dietary interventions among adults of retirement transition age (54 to 70 years). Twelve electronic databases were searched for randomized controlled trials evaluating the promotion of a healthy dietary pattern, or its constituent food groups, with three or more months of follow-up and reporting intake of specific food groups. Random-effects models were used to determine the pooled effect sizes. Subgroup analysis and meta-regression were used to assess sources of heterogeneity. Results Out of 9,048 publications identified, 68 publications reporting 24 studies fulfilled inclusion criteria. Twenty-two studies, characterized by predominantly overweight and obese participants, were included in the meta-analysis. Overall, interventions increased fruit and vegetable (F&V) intake by 87.5 g/day (P <0.00001), with similar results in the short-to-medium (that is, 4 to 12 months; 85.6 g/day) and long-term (that is, 13 to 58 months; 87.0 g/day) and for body mass index (BMI) stratification. Interventions produced slightly higher intakes of fruit (mean 54.0 g/day) than of vegetables (mean 44.6 g/day), and significant increases in fish (7 g/day, P = 0.03) and decreases in meat intake (9 g/day, P <0.00001). Conclusions Increases in F&V intakes were positively associated with the number of participant intervention contacts. Dietary interventions delivered during the retirement transition are therefore effective, sustainable in the longer term and likely to be of public health significance

Ada Ravenscar Code Archetypes for Component-based Development

We promote a model-driven software development that centres on component-orientation. In keeping with Dijkstra\u2019s principle of separation of concerns, we want the user design space to be limited to the internals of components \u2013 for which strictly sequential functional code is to be used \u2013 and the interfaces provided to and required from other components, where extra-functional requirements are declaratively specified by means of annotations. We want the user model to be directly amenable to response time analysis. To this end we prescribe that the component model must statically bind to a computational model that matches the analysis theory in use. We want to ensure semantic preservation across the entire transformation chain, from the user model, to the analysis model, to the implementation model (i.e., the code) and, eventually to the execution environment. The Ada Ravenscar Profile is an excellent candidate implementation language for use in our endeavour. In this paper we present a set of code archetypes written against the constraints of the Ravenscar Profile, which we developed in conformance with our notion of separation of concerns, to drive the model to code transformation step of our development infrastructure

On Component-Based Development Methods and High-Integrity Real-Time Systems

Component-based development approaches are becoming commonplace in business applications: they must therefore have some merit. In striking contrast to that, their penetration in the industrial practice of high-integrity real-time systems is virtually nil. This oddity needs explaining. In this paper we reflect on the presumed reasons of this situation and elaborate on possible systematic remedies. We contend that in order to make it in the high-integrity real-time systems domain, a component-based development approach must be constructed around four fundamental ingredients: a component model, a computational model, a programming model, and a congruent execution platform. Of those four ingredients, the computational model is key to bridging the lack of architectural concerns that afflicts the real-time workload models. We relate the component model to real-time systems theories. We illustrate how those elements could be neatly encased in a development method centred on model-driven engineering. We conclude by noting that the incorporation of component-based development methods, augmented with the cited ingredients, into model-driven engineering promises important savings in the development time and cost and also facilitates the industrial adoption of state-of-the-art techniques off real-time theory

A Component Model for On-board Software Applications

Component-based development has become more common news than exotic novelty in mainstream industry. Its adoption has accrued high facilitation potential for software reuse and better organization of the product. Surprisingly however, component-oriented approaches have fared far worse in the domain of high-integrity real-time systems. One of the fundamental reasons of this difficulty stems from the larger incidence of extra-functional concerns than in conventional industry and the more stringent demands on the ultimate product quality. It is not intrinsic however that component-based software engineering cannot just make it in that domain. Hence adopting it may be an effort worth pursuing. In this paper we present the main conceptual and methodological steps taken by an initiative of the European Space Agency aimed at the creation of a component model suited for the development of on-board software

Fitting Schedulability Analysis Theory into Model-Driven Engineering

The theory behind state-of-the-art schedulability analysis has reached such a level of sophistication that its complete mastering by the average industrial practitioner is practically infeasible. The centrality of automation promoted by model-driven engineering may facilitate the uptake of the front-end of the analysis theory by the industrial world. In this paper we qualitatively evaluate how current approaches to model-based schedulability analysis may employ and feed state-of-the-art analysis equations; we then illustrate a new strategy which, by way of model transformation, warrants a high degree of confidence in and permits an iterative refinement of the input to sophisticated analysis equations. We contend that model-driven engineering is well suited for fitting the most advanced analysis theories and to chart the course for future improvements in the area of model-based schedulability analysis