The National Kidney Foundation (NKF), and Elsevier, the information analytics business specialising in science and health, have announced the launch of Kidney Medicine, a peer-reviewed, open access journal focused on clinical research in nephrology and hypertension.
Led by Editor-in-Chief Dr. Daniel E. Weiner, and an editorial board of experts in the field, Kidney Medicine is designed to rapidly disseminate knowledge relevant to the care of people with or at risk of kidney diseases. The journal will publish original research, case reports, and review articles spanning a wide range of topics, including qualitative and quantitative research; health care policy, delivery and disparities research; and epidemiology and outcomes research. Kidney Medicine also seeks research on assessing and improving nephrology education and patient-reported outcomes.
"As an official journal of the National Kidney Foundation, we are excited to take on the challenge of meeting the high standards of other NKF journals, like American Journal of Kidney Diseases (AJKD), Advances in CKD, and the Journal of Renal Nutrition," Dr. Weiner said. "In serving as Deputy Editor at AJKD for 10 years, I saw so many excellent articles that we could not publish. I see Kidney Medicine as filling a need in the kidney space, providing a gold open access journal with content that encompasses all clinical nephrology while additionally providing a platform for highlighting the patient-reported outcomes research and qualitative research that are essential for improving patient care."
Kidney Medicine is currently accepting submissions and will publish its first issue in early 2019. The journal promises fast and fair decisions while maintaining a rigorous peer review process. Authors publishing in Kidney Medicine will benefit from a quality review process, quick turn-around times, and open access publication of their papers on Kidney Medicine and ScienceDirect.
Brought to you by Scope e-Knowledge Center, a trusted global partner for digital content transformation solutions - Abstracting & Indexing (A&I), Knowledge Modeling (Taxonomies, Thesauri and Ontologies), and Metadata Enrichment & Entity Extraction.
