Prediction of dialysis adequacy using data-driven machine learning algorithms.

Background: Adequate delivery of hemodialysis (HD), measured by the spKt/V derived from urea reduction, is an important determinant of clinical outcomes in chronic hemodialysis patients. However, the need for pre- and postdialysis blood samples prevented the assessment of spKt/V in every session.

Methods: This retrospective single-center study was performed on end-stage renal disease (ESKD) patients aged ≥ 18 years who received standard thrice-weekly chronic HD therapy.