The prevalence of pain has been reported to be >60–70% among patients with advanced and end-stage kidney disease. Although the underlying etiologies of pain may vary, pain per se has been linked to lower quality of life and depression. The latter is of great concern given its known association with reduced survival among patients with end-stage kidney disease. We herein discuss and update the management of pain in patients with chronic kidney disease with and without requirement for renal replacement therapy with the focus on optimizing pain control while minimizing therapy-induced complications.

Although many researches are increased in Sketch Based Image Retrieval (SBIR) field, it is still difficult to bridge the gap between image and sketch matching problem. Feature extraction is the critical role for SBIR to get efficient matching. In this paper, the proposed feature descriptor called Edge Orientation Histogram (EOH) for sketch based image retrieval (SBIR) system is presented. The features of database images and query sketch are extracted by EOH descriptor. And then cosine similarity measure is applied for matching features. The retrieved images similar with query sketch are displayed by rank order. Mean Average Precision (MAP) is measured as evaluation criteria. The Flickr15K benchmark dataset is used to evaluate the performance of this system.