Sawhney, SimonTan, ZhiBlack, CorriMarks, AngharadMcLernon, David JRonksley , PaulJames, Matthew T2021-06-242021-06-242021-07Sawhney, S, Tan, Z, Black, C, Marks, A, McLernon, D J, Ronksley , P & James, M T 2021, 'Validation of Risk Prediction Models to Inform Clinical Decisions After Acute Kidney Injury', American Journal of Kidney Diseases, vol. 78, no. 1, pp. 28-37. https://doi.org/10.1053/j.ajkd.2020.12.0080272-6386ORCID: /0000-0001-8905-2429/work/88320366ORCID: /0000-0003-1910-462X/work/88320637ORCID: /0000-0002-7960-4573/work/97666995https://hdl.handle.net/2164/16733Wellcome Trust Research Training Fellowship: 102729/Z/13/Z Academy of Medical Sciences Starter Grant for Clinical Lecturers: SGL020\1076 We acknowledge the support of the Grampian Data Safe Haven (DaSH) facility within the Aberdeen Centre for Health Data Science and the associated financial support of the University of Aberdeen, and NHS Research Scotland (through NHS Grampian investment in DaSH). More information is available at the DaSH website: http://www.abdn.ac.uk/iahs/facilities/grampian-data-safe-haven.php10866177engacute kidney injury (AKI)chronic kidney disease (CKD)CKD progressionCKD surveillancedeathfollow-up carehospital readmissionmodel-guided decisionsmortalitynet benefitpost-AKI carepost-discharge monitoringrisk predictionR MedicineNephrologyWellcome Trust102729/Z/13/ZSupplementary InformationTables/Figures JARJournal article10.1053/j.ajkd.2020.12.008http://www.scopus.com/inward/record.url?scp=85107720553&partnerID=8YFLogxK781