Kidney International Reports

Ultrafiltration Rate Thresholds Associated With Increased Mortality Risk in Hemodialysis, Unscaled or Scaled to Body Size

Jochen G Raimann, Yuedong Wang, Ariella Mermelstein, Peter Kotanko, John Daugirdas

Abstract

Introduction: One proposed threshold ultrafiltration rate (UFR) of concern in hemodialysis patients is 13 ml/h per kg. We evaluated associations among UFR, postdialysis weight, and mortality to determine whether exceeding such a threshold would result in similar levels of risk for patients of different body weights.

Methods: Data were analyzed in this retrospective cohort study for 1 year following dialysis initiation (baseline) and over 2 years of follow-up in incident patients receiving thrice-weekly in-center hemodialysis. Patient-level UFR was averaged over the baseline period. To investigate the joint effect of UFR and postdialysis weight on survival, we fit Cox proportional hazards models using bivariate tensor product spline functions, adjusting for sex, race, age, diabetes, and predialysis serum albumin, phosphorus, and systolic blood pressure (BP). We constructed contour plots of mortality hazard ratios (MHRs) over the entire range of UFR values and postdialysis weights.

Results: In the studied 2542 patients, UFR not scaled to body weight was strongly associated with MHR, whereas postdialysis weight was inversely associated with MHR. MHR crossed 1.5 when unscaled UFR exceeded 1000 ml/h, and this relationship was largely independent of postdialysis weight in the range of 80 to 140 kg. A UFR warning level associated with a lower MHR of 1.3 would be 900 ml/h, whereas the UFR associated with an MHR of 1.0 was patient-size dependent. The MHR when exceeding a UFR threshold of 13 ml/h per kg was dependent on patient weight (MHR = 1.20, 1.45, and >2.0 for a 60, 80, and 100 kg patient, respectively).

Conclusion: UFR thresholds based on unscaled UFR give more uniform risk levels for patients of different sizes than thresholds based on UFR/kg.

About the Contributors

Jochen G. Raimann, MD, PhD, MPH

Director, Data Analytics

Jochen has worked as a full-time scientist at RRI since his start as a postdoctoral research fellow in 2007. As Senior Manager of Clinical Data Analytics, Jochen conducts epidemiological research in dialysis and oversees many analytical projects. He has first- and co-authored numerous papers and also serves as Associate Editor of the journals Trials and Scientific Reports. ochen earned his MD from the Medical University Graz, his PhD from Maastricht University, and his MPH with a focus on epidemiology and biostatistics from the City University of New York School of Public Health.

Ariella Mermelstein, MA

Data Analyst

Ariella joined RRI as a data analyst in 2020 while completing her master's degree in mathematics from the Katz School at Yeshiva University. As an integral part of the research division at RRI, Ariella collaborates across all teams on various projects, particularly the physiological effects of hemodialysis on a variety of patient populations. The scope of her work includes predictive modeling, outcome analysis, and data extraction and processing. She has submitted manuscripts for publication and is looking forward to her continued career at RRI.

Dr. Peter Kotanko, MD

RRI Research Director

SVP, Corporate Research & Development

Peter Kotanko, MD, is Research Director at the Renal Research Institute (RRI), New York. Prior to joining RRI, from 1997 to 2007 he served as vice chair of a department of internal medicine at an academic teaching hospital in Graz, Austria. Prior to moving to Graz in 1989, he worked from 1982 to 1989 in the Department of Physiology and the University Clinic of Internal Medicine in Innsbruck, Austria. From 1995 to 1996 he trained in nephrology at the Hammersmith Hospital, London, United Kingdom.