Sawhney, SimonFraser, Simon D2017-08-102017-08-102017-07-01Sawhney, S & Fraser, S D 2017, 'Epidemiology of AKI : Utilizing Large Databases to Determine the Burden of AKI', Advances in Chronic Kidney Disease, vol. 24, no. 4, pp. 194-204. https://doi.org/10.1053/j.ackd.2017.05.0011548-5595ORCID: /0000-0002-7960-4573/work/97667009http://hdl.handle.net/2164/9100S.S. is supported by a Clinical Research Training Fellowship from the Wellcome Trust (Ref 102729/Z/13/Z). We also acknowledge the support from The Farr Institute of Health Informatics Research. The Farr Institute is supported by a 10-funder consortium: Arthritis Research UK, the British Heart Foundation, Cancer Research UK, the Economic and Social Research Council, the Engineering and Physical Sciences Research Council, the Medical Research Council, the National Institute of Health Research, the National Institute for Social Care and Health Research (Welsh Assembly government), the Chief Scientist Office (Scottish government Health Directorates), and the Wellcome Trust (MRC grant nos: Scotland MR/K007017/1). The funders of this study had no role in study design; collection, analysis, and interpretation of data; writing the report; and the decision to submit the report for publication.111754301engacute kidney injuryincidenceprognosisbig-dataquality improvementR MedicineWellcome Trust102729/Z/13/ZMedical Research Council (MRC)MR/K007017/1RJournal article10.1053/j.ackd.2017.05.001244