• Nina R O'Connor, Meredith Dougherty, Pamela S Harris, and David J Casarett.
• University of Pennsylvania Perelman School of Medicine, Philadelphia Pennsylvania, †Kansas City Hospice and Palliative Care, Kansas City, Missouri.
• Clin J Am Soc Nephrol. 2013 Dec 1;8(12):2117-22.

Background And ObjectivesTextbooks report that patients with ESRD survive for 7-10 days after discontinuation of dialysis. Studies describing actual survival are limited, however, and research has not defined patient characteristics that may be associated with longer or shorter survival times. The goals of this study were to determine the mean life expectancy of patients admitted to hospice after discontinuation of dialysis, and to identify independent predictors of survival time.Design, Setting, Participants, & MeasurementsData for demographics, clinical characteristics, and survival were obtained from 10 hospices for patients with ESRD who discontinued dialysis before hospice admission. Data were collected for patients admitted between January 1, 2008 and May 15, 2012. All hospices were members of the Coalition of Hospices Organized to Investigate Comparative Effectiveness network, which obtains de-identified data from an electronic medical record.ResultsOf 1947 patients who discontinued dialysis, the mean survival after hospice enrollment was 7.4 days (range, 0-40 days). Patients who discontinued dialysis had significantly shorter survival compared with other patients (n=124,673) with nonrenal hospice diagnoses (mean survival 54.4 days; hazard ratio, 2.96; 95% confidence interval, 2.82 to 3.09; P<0.001). A Cox proportional hazards model identified seven independent predictors of earlier mortality after dialysis discontinuation, including male sex, referral from a hospital, lower functional status (Palliative Performance Scale score), and the presence of peripheral edema.ConclusionsPatients who discontinue dialysis have significantly shorter survival than other hospice patients. Individual survival time varies greatly, but several variables can be used to predict survival and tailor a patient's care plan based on estimated prognosis.

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