Arterial stiffness in chronic kidney disease: a modifiable cardiovascular risk factor? Purpose of review There is an inverse, graded relationship between worsening chronic kidney disease (CKD) and increasing cardiovascular risk independent of traditional cardiovascular risk factors. Increasing arterial stiffness is a powerful predictor of cardiovascular outcomes in CKD. Developing novel therapeutic strategies to reverse this process is an attractive concept. This review presents the results of a literature survey of the last 18 months to establish if arterial stiffness can be considered a reversible cardiovascular risk factor in patients with CKD. Recent findings Multiple potential therapeutic approaches to reduce arterial stiffness have been proposed and tested. However, arterial stiffness and blood pressure (BP) have a very close bidirectional relationship. Any change in BP will have an effect on arterial stiffness and vice versa. At present, there is no robust evidence to support the notion that arterial stiffness can be considered reversible other than as a direct consequence of reduction in BP. Summary For now, arterial stiffness should be considered an indirectly modifiable cardiovascular risk factor through optimal control of BP. Measures of arterial stiffness should be regarded as research and risk stratification tools rather than a therapeutic target in itself. Correspondence to Charles J. Ferro, Department of Nephrology, Queen Elizabeth Hospital Birmingham, Birmingham B15 2WB, UK. Tel: +44 121 3715839; fax: +44 121 3715858; e-mail: charles.ferro@uhb.nhs.uk Copyright © 2019 Wolters Kluwer Health, Inc. All rights reserved.

Acute kidney injury prediction models: current concepts and future strategies Purpose of review Acute kidney injury (AKI) is a critical condition associated with poor patient outcomes. We aimed to review the current concepts and future strategies regarding AKI risk prediction models. Recent findings Recent studies have shown that AKI occurs frequently in patients with common risk factors and certain medical conditions. Prediction models for AKI risk have been reported in medical fields such as critical care medicine, surgery, nephrotoxic agent exposure, and others. However, practical, generalizable, externally validated, and robust AKI prediction models remain relatively rare. Further efforts to develop AKI prediction models based on comprehensive clinical data, artificial intelligence, improved delivery of care, and novel biomarkers may help improve patient outcomes through precise AKI risk prediction. Summary This brief review provides insights for current concepts for AKI prediction model development. In addition, by overviewing the recent AKI prediction models in various medical fields, future strategies to construct advanced AKI prediction models are suggested. Correspondence to Hajeong Lee, MD, Ph.D., Department of Internal Medicine, Seoul National University Hospital, 101 Daehak-ro, Seoul 03080, Jongno-gu, South Korea. Tel.: +82 2 2072 4905;. e-mail: mdhjlee@gmail.com Copyright © 2019 Wolters Kluwer Health, Inc. All rights reserved.

Exploring old concepts and new paradigms No abstract available