The rigour applied to interpreting the data for the adult CKD blood pressure targets (Chapters 3 and 4) has not been applied to kidney transplant recipients (Chapter 5). The most likely reason is what is stated in the text: that a blood pressure target has already been stated in another KDIGO Guideline.[16] The KDIGO

Management of Blood Pressure in CKD Work Group state that there is no new data to contradict the previous statement, although they reduced the grade from 2C to 2D. Consistency is not just a problem for KDIGO, as management of blood pressure permeates many areas of nephrology PD-332991 and therefore, many guidelines. For example, the KHA-CARI Guideline for the Detection, Prevention and Management of Early Chronic Kidney Disease, which recommends blood pressure targets[6] (Table 1) was preceded by five different guidelines that are now ‘out of date’ and three guidelines that remain current, all of which make statements about issues covered in the KDIGO BP Guideline (see http://www.cari.org.au/ckd_prevent_list_published.php accessed 15/7/2013). The KDIGO Clinical Practice Guideline on the Management of Blood Pressure Galunisertib in CKD makes reasonable statements about the management of blood pressure in

CKD and is less accepting of the evidence for lower blood pressure targets than previous guidelines. By providing a blood pressure target for most patient groups, they are able to be implemented by clinicians. This guideline is useful to illustrate the paucity of evidence in a fundamental area of nephrology practice but highlights the difficulties of maintaining consistency in the grading of that evidence for a topic that transcends different aminophylline areas of nephrology practice and therefore appears in different guidelines. I thank Dr Elisabeth Hodson of the Centre for Kidney Research, The Sydney Children’s Hospital Network (Westmead), for reviewing the

Paediatric Chapter and for her comments on this manuscript. “
“The Framingham Risk Score (FRS), calculated by considering conventional risk factors of cardiovascular diseases, was developed to predict coronary heart disease in various populations. However, reverse epidemiology has been raised concerning these risk factors in predicting high cardiovascular mortality in hemodialysis patients. Our objectives are to determine whether FRS is associated with overall and cardiovascular mortality and the role of new risk markers when they were added to a FRS model in hemodialysis patients. This study enrolled 201 hemodialysis patients aged 20–80 years old. The FRS is used to identify individuals categorized as low (<6% 10-year risk), intermediate (6–20% risk) or high risk (>20% risk). Medical records were reviewed to collect clinical information. Data of ankle-brachial index (ABI) and brachial-ankle pulse wave velocity (baPWV) were obtained by an ABI-form device. The mean follow-up period was 4.