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Background: The amount of hemodialysis that patients receive is an independent predictor of mortality. However, the relative predictive ability of four common measures of dialysis dose (urea reduction ratio, single-pool Kt/V, double-pool Kt/V, and urea index) is unclear., Methods: Using The Renal Network Data System, we identified 14,810 incident hemodialysis patients in Indiana, Kentucky, Ohio, and Illinois from 1997 to 2000. We calculated each measure of hemodialysis dose during the first 6 months of treatment, then prospectively followed up patients for an additional 6 months. For each measure of dialysis dose, we developed a logistic regression model to examine the relationship between dose and patient mortality after adjustment for age, race, sex, cause of renal failure, comorbid conditions, and albumin level. We compared the predictive ability of the four models using the c statistic, a measure of how frequently survivors have a lower predicted probability of death compared with nonsurvivors. C statistics can vary from 0.50 (no predictive ability) to 1.00 (perfect predictive ability)., Results: Of all patients, 11.3% died during follow-up. Mortality was independently associated with low dialysis dose, advanced age, white race, female sex, specific comorbid conditions, and low albumin level. All four predictive models had virtually identical c statistics (range, 0.69 to 0.70)., Conclusion: Models including hemodialysis dose and patient characteristics have a modest ability to predict mortality. Moreover, all four measures of dialysis dose have an equivalent predictive ability. Decisions to use a specific measure should be based on other considerations, such as ease of use, need to troubleshoot inadequate dialysis delivery, or research on urea kinetics or nutritional factors., (Copyright 2002 by the National Kidney Foundation, Inc.)

Background: Kidney transplantation rates differ by patient and dialysis-facility characteristics, yet little is known about the sources of this variation or how access to transplantation can be improved. Examining specific steps in the transplantation process may guide quality improvement efforts that ultimately improve the equity and efficiency of transplantation., Methods: We sought to examine variation across dialysis facilities in the completion of four specific steps (medical suitability, interest in transplantation, pretransplantation workup, and waiting list) after adjustment for patient characteristics. Using 11,674 patients on chronic hemodialysis therapy between January 1993 and December 1996 at 206 facilities in Indiana, Kentucky, and Ohio, we derived facility-specific: (1) actual completion rates at each step; (2) expected completion rates based on patient age, race, sex, and cause of renal failure; and (3) ratio of actual to expected completion rates., Results: Actual completion rates varied greatly, with facilities at the 75th percentile having a twofold greater completion rate than facilities at the 25th percentile (eg, 59% versus 32% at the first step). Although patient characteristics were strongly associated with step completion, adjustment for these characteristics did not decrease variation across facilities. At each step, approximately 20% of facilities had a significantly greater than expected completion rate, whereas approximately 15% had a significantly lower than expected completion rate., Conclusion: There is substantial variation across dialysis facilities in access to kidney transplantation, even after adjustment for patient characteristics. Identifying steps with less than expected completion rates may help facilities target such efforts as treatment of medical conditions, patient education, and early referral for pretransplantation workup and waiting list placement., (Copyright 2002 by the National Kidney Foundation, Inc.)