ResearchMoz include new market research report" Global Dialysis Market Report: 2013 Edition" to its huge collection of research reports.
Albany, NY -- (SBWIRE) -- 10/14/2013 -- ESRD (End Stage Renal Disease) refers to permanent kidney failure. It is the final stage of Chronic Kidney Disease (CKD) where the kidney functions at less than 10-15% of the normal capacity. The growing prevalence of diabetes, hypertension and large elderly population are rapidly driving the number of ESRD patients globally. There are two methods used for treating ESRD patients: kidney transplant or dialysis.
Dialysis is the process of blood purification i.e. the removal of waste and toxic substances from the body and it can be done via two procedures viz. peritoneal dialysis (PD) or hemodialysis (HD). The major dialysis products include dialyzers, hemodialysis machines, dialysis concentrates and peritoneal dialysis products. Diabetes and high blood pressure are among the key causative factors for kidney failure leading to an increase in the number of patients suffering from CKD and ESRD.
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This report analyzes the global dialysis market with focus on its segments including: dialysis services, dialysis products, and dialysis drugs. Moreover, the regional market of China is also discussed. Furthermore market dynamics such as the industry trends and development, key growth drivers and challenges faced by the industry are also elicited in detail. On the contention front, the global dialysis market is fiercely competitive with a handful of player reining the whole market. The key industry players are Baxter, Fresenius, DaVita and Gambro. The competitive landscape of the industry along with the key industry players’ profiles are also added herein.
By combining SPSS Inc.’s data integration and analysis capabilities with our relevant findings, we have predicted the future growth of the industry. We employed various significant variables that have an impact on this industry and created regression models with SPSS Base to determine the future direction of the industry. Before deploying the regression model, the relationship between several independent or predictor variables and the dependent variable was analyzed using standard SPSS output, including charts, tables and tests.
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