How can big data help to understand the migration phenomenon? In this paper, we try to answer this question through an analysis of various phases of migration, comparing traditional and novel data sources and models at each phase. We concentrate on three phases of migration, at each phase describing the state of the art and recent developments and ideas. The first phase includes the journey, and we study migration flows and stocks, providing examples where big data can have an impact. The second phase discusses the stay, i.e. migrant integration in the destination country. We explore various data sets and models that can be used to quantify and understand migrant integration, with the final aim of providing the basis for the construction of a novel multi-level integration index. The last phase is related to the effects of migration on the source countries and the return of migrants.
In the study population, both a general screening program in 65-75 year old men and an approach targeted to subgroups at higher risk merit evaluation in a cost-effectiveness study. In 50-64 year old men, strategies for population selection should consider CVD risk stratification tools.
Ageing of the world's population raises important questions about the utilisation of the health care system. It is not clear how much should be invested in the last years of life whereas the costs are known to increase in parallel. Since intensive care units (ICU) are costly with highly specialised personnel, it seems of paramount importance that they would be used efficiently. Indeed, in the present context of predicted shortage of physicians in Switzerland, society and politics will need evidence that the care provided by ICUs is appropriate. There is no explicit limitation of care in any country according to age and nonagerians are admitted nowadays into ICUs with critical illness. This review article will address the question of elderly patients in ICU and their outcome. Outcome does not imply surviving ICU but only later during the hospital stay and after discharge. Furthermore, we emphasise the need of examining not solely the hospital survival but the quality of life of the patients when they return to their real life. The fundamental questions are actually "Do they go back to life?" "What is life for elderly people?" These questions lead to more basic questions such as "Are they able to go back home or are they institutionalised? How is their quality of life and functional status after ICU?". We tried to address these questions through the existing literature and our experience while caring for these particular patients. Some clues on the prognostic factors related to their outcome are reported.
Purpose The length of time a critically ill coronavirus disease 2019 (COVID-19) patient remains infectious and should therefore be isolated remains unknown. This prospective study was undertaken in critically ill patients to evaluate the reliability of single negative real-time polymerase chain reaction (RT-PCR) in lower tracheal aspirates (LTA) in predicting a second negative test and to analyze clinical factors potentially influencing the viral shedding. Methods From April 9, 2020 onwards, intubated COVID-19 patients treated in the intensive care unit were systematically evaluated for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by RT-PCR of nasopharyngeal swabs and LTA. The time to negativity was defined as the time between the onset of symptoms and the viral clearance in LTA. In order to identify risk factors for prolonged viral shedding, we used univariate and multivariate Cox proportional hazards models. Results Forty-eight intubated SARS-CoV-2 patients were enrolled. Overall, we observed that the association of the first negative RT-PCR with a second negative result was 96.7%. Median viral shedding was 25 (IQR: 21.5-28) days since symptoms' onset. In the univariate Cox model analysis, type 2 diabetes mellitus was associated with a prolonged viral RNA shedding (hazard ratio [HR]: 0.41, 95% CI: 0.06-3.11, p = 0.04). In the multivariate Cox model analysis, type 2 diabetes was associated with a prolonged viral RNA shedding (HR: 0.31, 95% CI: 0.11-0.89, p = 0.029). Conclusion Intubated patients with type 2 diabetes mellitus may have prolonged SARS-CoV-2 shedding. In critically ill COVID-19 patients, one negative LTA should be sufficient to assess and exclude infectivity.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.