Abstract Objectives To determine the value of surgery for infective endocarditis in patients on hemodialysis, we compared the nature and invasiveness of endocarditis in hemodialysis and ...non-hemodialysis patients and their hospital and long-term outcomes, and identified risk factors for time-related mortality after surgery. Methods From January 1997 to January 2013, 144 patients on chronic hemodialysis and 1,233 non- hemodialysis patients underwent valve surgery for infective endocarditis. Propensity matching identified 99 well-matched hemodialysis and non-hemodialysis patient pairs for comparison of outcomes. Results Staphylococcus aureus infection was more common in hemodialysis than in non-hemodialysis patients (42% vs. 21%; P <.0001), but invasive disease was similar (47%; P=. 3). Hospital mortality was 13% and 5-year survival 20% for hemodialysis patients, 20% below that expected in a general hemodialysis population but 15% above that of hemodialysis patients treated non-surgically for endocarditis. For matched patients, hospital mortality was 13% for hemodialysis patients versus 5.1% for non-hemodialysis patients (P =.05), and survival at 1 and 5 years was 56% versus 83% and 24% versus 59%, respectively ( P <.004). Use of an arteriovenous graft for dialysis access ( P =.01) and a preoperative pacemaker ( P <.0001) were risk factors for late mortality in hemodialysis patients. For matched patients, freedom from reoperation was similar for hemodialysis and non-hemodialysis patients ( P >.9 ). Conclusions Intermediate-term survival after surgery for infectious endocarditis in hemodialysis patients is substantially worse than in non-hemodialysis patients, but only slightly worse than in the general hemodialysis population and substantially better than in hemodialysis patients with endocarditis treated non-surgically, supporting continued surgical intervention for endocarditis.
Alzheimer's disease is the extremely popular cause of dementia that causes memory loss. People who have Alzheimer's disease suffer from a disorder in neurodegenerative which leads to loss in many ...brain functions. Nowadays researchers prove that early diagnosis of the disease is the most crucial aspect to enhance the care of patients' lives and enhance treatment. Traditional approaches for diagnosis of Alzheimer's disease (AD) suffers from long time with lack both efficiency and the time it takes for learning and training. Lately, deep-learning-based approaches have been considered for the classification of neuroimaging data correlated to AD. In this paper, we study the use of the Convolutional Neural Networks (CNN) in AD early detection, VGG-16 trained on our datasets is used to make feature extractions for the classification process. Experimental work explains the effectiveness of the proposed approach.
Usually, IoT devices are designed to perform specific tasks, while robots have to adapt to unpredictable situations. Artificial intelligence and machine learning help these robots cope with the ...emerging unexpected conditions. The Internet of Robotic Things is an evolving concept that brings together all-encompassing sensors and devices with robotic and autonomous systems. Both IoT devices and robots rely on sensors to understand the surrounding environment, to process data quickly, and to decide how to respond. Nevertheless, while most IoT systems can handle only well-defined tasks, robots can handle expected situations as well. The Internet of Robotic Things is a better Internet of Things (IoT) solution due to its ability to bridge the gap between IT and real operations. The IoRT may face several challenges in power consumption and network bandwidth limitation due to the growth in the information dissemination over the Robotic network. The main objective of this paper is to introduce an overview of the concepts and challenges in the Internet of Robotic Things based on Fog Computing technique. Further, a framework of Fog based IoRT is introduced.
Context-aware e-Services offer entirely new opportunities for application developers and for end users by gathering context data and offering e-services solutions that are adapted to their context. ...In this paper, using a scenario, we argue for the need for an e-services framework that supports decision-making during fault management process in electricity distribution networks. Then we discuss the different aspects needed to be covered in such a framework and introduce a high-level view of its functional components. The framework functionality was implemented using web services and an android platform. Our experimental work shows improvement in repairing faults thus reducing the associated costs and accordingly increasing user satisfaction and savings in electric power distribution.
PDF
