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- Biancari, F, et al.
(author)
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Preoperative risk stratification of deep sternal wound infection after coronary surgery
- 2020
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In: Infection control and hospital epidemiology. - : Cambridge University Press (CUP). - 1559-6834 .- 0899-823X. ; 41:4, s. 444-451
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Journal article (peer-reviewed)abstract
- Objective:To develop a risk score for deep sternal wound infection (DSWI) after isolated coronary artery bypass grafting (CABG).Design:Multicenter, prospective study.Setting:Tertiary-care referral hospitals.Participants:The study included 7,352 patients from the European multicenter coronary artery bypass grafting (E-CABG) registry.Intervention:Isolated CABG.Methods:An additive risk score (the E-CABG DSWI score) was estimated from the derivation data set (66.7% of patients), and its performance was assessed in the validation data set (33.3% of patients).Results:DSWI occurred in 181 (2.5%) patients and increased 1-year mortality (adjusted hazard ratio, 4.275; 95% confidence interval [CI], 2.804–6.517). Female gender (odds ratio [OR], 1.804; 95% CI, 1.161–2.802), body mass index ≥30 kg/m2(OR, 1.729; 95% CI, 1.166–2.562), glomerular filtration rate <45 mL/min/1.73 m2(OR, 2.410; 95% CI, 1.413–4.111), diabetes (OR, 1.741; 95% CI, 1.178–2.573), pulmonary disease (OR, 1.935; 95% CI, 1.178–3.180), atrial fibrillation (OR, 1.854; 95% CI, 1.096–3.138), critical preoperative state (OR, 2.196; 95% CI, 1.209–3.891), and bilateral internal mammary artery grafting (OR, 2.088; 95% CI, 1.422–3.066) were predictors of DSWI (derivation data set). An additive risk score was calculated by assigning 1 point to each of these independent risk factors for DSWI. In the validation data set, the rate of DSWI increased along with the E-CABG DSWI scores (score of 0, 1.0%; score of 1, 1.8%; score of 2, 2.2%; score of 3, 6.9%; score ≥4: 12.1%;P< .0001). Net reclassification improvement, integrated discrimination improvement, and decision curve analysis showed that the E-CABG DSWI score performed better than other risk scores.Conclusions:DSWI is associated with poor outcome after CABG, and its risk can be stratified using the E-CABG DSWI score.Trial registration:clinicaltrials.gov identifier: NCT02319083
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- Mas-Machuca, Carmen, et al.
(author)
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Reliable Control and Data Planes for Softwarized Networks
- 2020
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In: Guide to Disaster-Resilient Communication Networks. - : Springer. - 9783030446840 - 9783030446857 - 9783030446871 ; , s. 243-270
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Book chapter (peer-reviewed)abstract
- Driven by the requirement of increasing performance and flexibility, networks are being softwarized by paradigms such as software-defined networking (SDN) and network function virtualization (NFV). These solutions reduce the complexity and the specialization of hardware devices, by extracting the inherently distributed control plane of forwarding network elements such as switches and routers, to a logically centralized control plane (referred as controller in SDN). The control plane acts as a broker between the network applications (e.g. monitoring, traffic engineering) and the data plane (i.e. physical network infrastructure). For scalability and robustness, the logically centralized control plane is implemented by physically distributing different controllers throughout the network. This chapter presents different solutions to increase the reliability of both planes: data and control planes. The reliability of the data plane can be increased by considering survivable virtual network embedding solutions. This chapter proposes a survivable embedding against single and double failures at either links or nodes. Furthermore, in order to provide a programmable and resilient data plane, BPFabric has been proposed for SDN which supports high performance functions suitable for detecting attacks. On the other hand, the reliability of the control plane applied to SDN can be addressed by considering enhanced controller placement solutions providing redundancy against uncorrelated as well as targeted failures while coping with latency and capacity requirements. Furthermore, a solution to increase the security and robustness of the control channel is also addressed in this chapter.
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