• Eva K Masel, Patrick Huber, Sophie Schur, Katharina A Kierner, Romina Nemecek, and Herbert H Watzke.
• Division of Palliative Care, Department of Internal Medicine I, Medical University of Vienna, Waehringer Guertel 18-20, A-1090, Vienna, Austria, eva.masel@meduniwien.ac.at.
• Support Care Cancer. 2015 Aug 1;23(8):2335-9.

PurposeDischarging a patient admitted to an inpatient palliative care unit (PCU) is a major challenge. A predictor of the feasibility of home discharge at the time of admission would be very useful. We tried to identify such predictors in a prospective observational study.MethodsSixty patients with advanced cancer admitted to a PCU were enrolled. Sociodemographic data were recorded and a panel of laboratory tests performed. The Karnofsky performance status scale (KPS) and the palliative performance scale (PPS) were determined. A palliative care physician and nurse independently predicted whether the patient would die at the ward. The association of these variables with home discharge or death at the PCU was determined.ResultsSixty patients (26 men and 34 women) with advanced cancer were included in the study. Discharge was achieved in 45 % of patients, while 55 % of patients died at the PCU. The median stay of discharged patients was 15.2 days, and the median stay of deceased patients 13.6 days. Median KPS and PPS on admission was 56.2 % for the entire group and significantly higher for discharged patients (60.7 %) compared to deceased patients (52.4 %). Median BMI on admission was 22.8 in the entire group and was similar in discharged and deceased patients. No correlation was found between a panel of sociodemographic variables and laboratory tests with regard to discharge or death. In a binary logistic regression model, the probability of discharge as estimated by the nurse/physician and the KPS and PPS were highly significant (p = 0.008).ConclusionEstimation by a nurse and a physician were highly significant predictors of the likelihood of discharge and remained significant in a multivariate logistic regression model including KPS and PPS. Other variables, such as a panel of laboratory tests or sociodemographic variables, were not associated with discharge or death.

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