Can we predict when to start renal replacement therapy in patients with chronic kidney disease using 6 months of clinical data?

Min-Jeong Lee, Joo-Han Park, Yeo Rae Moon, Soo-Yeon Jo, Dukyong Yoon, Rae Woong Park, Jong Cheol Jeong, Inwhee Park, Gyu-Tae Shin and Heungsoo Kim

PLOS ONE, 2018, vol. 13, issue 10, 1-14

Abstract: Purpose: We aimed to develop a model of chronic kidney disease (CKD) progression for predicting the probability and time to progression from various CKD stages to renal replacement therapy (RRT), using 6 months of clinical data variables routinely measured at healthcare centers. Methods: Data were derived from the electronic medical records of Ajou University Hospital, Suwon, South Korea from October 1997 to September 2012. We included patients who were diagnosed with CKD (estimated glomerular filtration rate [eGFR]

Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0204586

DOI: 10.1371/journal.pone.0204586

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