Ultrafiltration Rate and Mortality in Maintenance Hemodialysis Patients

Magdalene M Assimon, Julia B Wenger, Lily Wang, Jennifer E Flythe, Magdalene M Assimon, Julia B Wenger, Lily Wang, Jennifer E Flythe

Abstract

Background: Observational data have demonstrated an association between higher ultrafiltration rates and greater mortality among hemodialysis patients. Prior studies were small and did not consider potential differences in the association across body sizes and other related subgroups. No study has investigated ultrafiltration rates normalized to anthropometric measures beyond body weight. Also, potential methodological shortcomings in prior studies have led to questions about the veracity of the ultrafiltration rate-mortality association.

Study design: Retrospective cohort.

Setting & participants: 118,394 hemodialysis patients dialyzing in a large dialysis organization, 2008 to 2012.

Predictors: Mean 30-day ultrafiltration rates were dichotomized at 13 and 10mL/h/kg, separately and categorized using various cutoff points. Ultrafiltration rates normalized to body weight, body mass index, and body surface area were investigated.

Outcomes: All-cause mortality.

Measurements: Multivariable survival models were used to estimate the association between ultrafiltration rate and all-cause mortality.

Results: At baseline, 21,735 (18.4%) individuals had ultrafiltration rates > 13mL/h/kg and 48,529 (41.0%) had ultrafiltration rates > 10mL/h/kg. Median follow-up was 2.3 years, and the mortality rate was 15.3 deaths/100 patient-years. Compared with ultrafiltration rates ≤ 13mL/h/kg, ultrafiltration rates > 13mL/h/kg were associated with greater mortality (adjusted HR, 1.31; 95% CI, 1.28-1.34). Compared with ultrafiltration rates ≤ 10mL/h/kg, ultrafiltration rates > 10mL/h/kg were associated with greater mortality (adjusted HR, 1.22; 95% CI, 1.20-1.24). Findings were consistent across subgroups of sex, race, dialysis vintage, session duration, and body size. Higher ultrafiltration rates were associated with greater mortality when normalized to body weight, body mass index, and body surface area.

Limitations: Residual confounding cannot be excluded given the observational study design.

Conclusions: Regardless of the threshold implemented, higher ultrafiltration rate was associated with greater mortality in the overall study population and across key subgroups. Randomized controlled trials are needed to investigate whether ultrafiltration rate reduction improves clinical outcomes.

Keywords: Hemodialysis; anthropometric measures; body mass index (BMI); body size; body surface area (BSA); body weight; end-stage renal disease (ESRD); metabolic mass; mortality; rapid fluid removal; ultrafiltration rate (UFR).

Copyright © 2016 National Kidney Foundation, Inc. Published by Elsevier Inc. All rights reserved.

Figures

Figure 1. Study design schematic
Figure 1. Study design schematic
a Source cohort consisted of 337,863 in-center hemodialysis patients with complete age, sex, race and ethnicity data.
Figure 2
Figure 2
Flow-chart of cohort selection.
Figure 3. Associations between prescribed ultrafiltration rate…
Figure 3. Associations between prescribed ultrafiltration rate and mortality by percentile of post-dialysis weight, body mass index and body surface area
Fine and Gray proportional subdistribution hazards regression models with kidney transplantation and dialysis modality change treated as competing risks were used to estimate the ultrafiltration rate and all-cause mortality association comparing mean UF rates >13 mL/h/kg to those ≤13 mL/h/kg within strata of body weight, BMI and BSA (separately). Models were adjusted for age (continuous), sex (female vs. male), race (black vs. non-black), ethnicity (Hispanic vs. non-Hispanic), dialysis vintage (1–2, 3–4, ≥5 vs. 4.0 vs. ≤3.0 g/dL), creatinine (continuous), phosphorous (4.1–5.0, 5.1–6.0, >6.0 vs. ≤4.0 mg/dL), hemoglobin (10.0–11.9, ≥12.0 vs. 170 vs. ≤130 mmHg), and missed sessions (≥3 vs. th/80th percentile for post-weight = 60.9/95.3 kg; 21.8/32.8 kg/m2 for BMI; 1.66/2.10 m2 for BSA. 80th percentile for UF rate normalized to BMI = 37 mL/h/(kg/m2); UF rate normalized to BSA = 500 mL/h/m2. 80th percentile selected for BMI and BSA based on 13 mL/h/kg being the 80th percentile of UF rate when normalized to post-HD weight. Abbreviations: HR=hazard ratio, CI=confidence interval, HD=hemodialysis

References

    1. Collins AJ, Foley RN, Chavers B, et al. US Renal Data System 2013 annual data report. Am J Kidney Dis. 2014;63(1 (suppl 1)):e1–e420.
    1. Saran R, Bragg-Gresham JL, Levin NW, et al. Longer treatment time and slower ultrafiltration in hemodialysis: associations with reduced mortality in the DOPPS. Kidney Int. 2006;69(7):1222–1228.
    1. Movilli E, Gaggia P, Zubani R, et al. Association between high ultrafiltration rates and mortality in uraemic patients on regular haemodialysis. A 5-year prospective observational multicentre study. Nephrol Dial Transplant. 2007;22(12):3547–3552.
    1. Flythe JE, Kimmel SE, Brunelli SM. Rapid fluid removal during dialysis is associated with cardiovascular morbidity and mortality. Kidney Int. 2011;79(2):250–257.
    1. Burton JO, Jefferies HJ, Selby NM, McIntyre CW. Hemodialysis-induced cardiac injury: determinants and associated outcomes. Clin J Am Soc Nephrol. 2009;4(5):914–920.
    1. Burton JO, Jefferies HJ, Selby NM, McIntyre CW. Hemodialysis-induced repetitive myocardial injury results in global and segmental reduction in systolic cardiac function. Clin J Am Soc Nephrol. 2009;4(12):1925–1931.
    1. Eldehni MT, Odudu A, McIntyre CW. Randomized Clinical Trial of Dialysate Cooling and Effects on Brain White Matter. J Am Soc Nephrol. 2014;24(4):957–965.
    1. McIntyre CW, Harrison LE, Eldehni MT, et al. Circulating endotoxemia: a novel factor in systemic inflammation and cardiovascular disease in chronic kidney disease. Clin J Am Soc Nephrol. 2011;6(1):133–141.
    1. Centers for Medicare and Medicaid Services. Proposed Measure Specifications for the PY 2019 ESRD QIP. Available at . Accessed February 4, 2016.
    1. Centers for Medicare and Medicaid Services. Release of Fiscal Year 2016 End Stage Renal Disease Core Survey Data Worksheet. 2015 Available at . Accessed February 4, 2016.
    1. Farrar D, Glauber R. Multicollinearity in regression analysis: the problem revisited. The Review of Economics and Statistics. 1967;1:92–107.
    1. National Kidney Foundation. KDOQI Clinical Practice Guideline for Hemodialysis Adequacy: 2015 Update. Am J Kidney Dis. 2015;66(5):884–930.
    1. Agar JW. Personal viewpoint: Limiting maximum ultrafiltration rate as a potential new measure of dialysis adequacy. Hemodial Int. 2016;20(1):15–21.
    1. National Quality Forum. Renal Draft Report. Available at . Accessed February 4, 2016.
    1. Du Bois D, Du Bois EF. A formula to estimate the approximate surface area if height and weight be known. 1916. Nutrition. 1989;5(5):303–311. discussion 312–303.
    1. Noordzij M, Leffondré K, van Stralen KJ, Zoccali C, Dekker FW, Jager KJ. When do we need competing risks methods for survival analysis in nephrology? Nephrol Dial Transplant. 2013;28(11):2670–2677.
    1. Schafer JL. Multiple imputation: a primer. Stat Methods Med Res. 1999;8(1):3–15.
    1. Vuong Q. Likelihood ratio tests for model selection and non-nested hypotheses. Econometrica. 1989;57(2):307–334.
    1. Robins JM, Hernán MA, Brumback B. Marginal structural models and causal inference in epidemiology. Epidemiology. 2000;11(5):550–560.
    1. Hernán MA, Brumback B, Robins JM. Marginal structural models to estimate the causal effect of zidovudine on the survival of HIV-positive men. Epidemiology. 2000;11(5):561–570.
    1. Eldehni MT, McIntyre CW. Are there neurological consequences of recurrent intradialytic hypotension? Semin Dial. 2012;25(3):253–256.
    1. End Stage Renal Disease (ESRD) Quality Measure Development and Maintenance Hemodialysis Adequacy Clinical Technical Expert Panel Summary Report. Arbor Research Collaborative for Health and the University of Michigan Kidney Epidemiology and Cost Center. 2013 Available at . Accessed February 4, 2016.
    1. Arora N, Chertow GM. Oh! What a tangled web we weave. Clin J Am Soc Nephrol. 2013;8(7):1066–1067.
    1. Assimon MM, Flythe JE. Intradialytic Blood Pressure Abnormalities: The Highs, The Lows and All That Lies Between. Am J Nephrol. 2015;42(5):337–350.
    1. Flythe JE, Mangione TW, Brunelli SM, Curhan GC. Patient-Stated Preferences Regarding Volume-Related Risk Mitigation Strategies for Hemodialysis. Clin J Am Soc Nephrol. 2014;9(8):1418–1425.
    1. Schneditz D, Roob J, Oswald M, et al. Nature and rate of vascular refilling during hemodialysis and ultrafiltration. Kidney Int. 1992;42(6):1425–1433.

Source: PubMed

3
Abonnieren