GOALS OF WORK: Predicting inpatient mortality has clinical and financial implications and helps improve the care of patients with advanced cancer and their families. Models with excellent validity and reliability are available for mortality prediction in intensive care units. The purpose of the current study was to determine factors associated with increased likelihood of mortality in an acute palliative care unit (APCU). PATIENTS AND METHODS: We retrospectively reviewed the medical records of 500 patients admitted to the APCU. Basic characteristics and information on symptom intensity, vital signs, relevant laboratory tests, and the presence or absence of delirium were obtained from the records of the consultation that preceded the APCU admission. Univariate and multivariate analyses were conducted to compare characteristics of patients who died in the APCU with characteristics of those who were discharged alive. MAIN RESULTS: Of the 500 patients admitted to the APCU, 124 (25%) died. Factors that were jointly prognostic for death, using multivariate analysis were younger age (odds ratio [OR] for older patients [>/=65] 0.43, 95% confidence interval [CI], 0.25-0.73, p < 0.001), admission from another oncology floor (OR 5.64, 95% CI, 1.82-17.44, p = 0.003), hyponatremia (OR 3.02, 95% CI, 1.76-5.17, p < 0.001), hypernatremia (OR 4.14, 95% CI, 1.25-13.75, p = 0.020), high blood urea nitrogen (BUN) (OR 1.95, 95% CI, 1.15-3.30, p = 0.013), high heart rate (>/=101 bpm) (OR 1.72, 95% CI, 1.01-2.93, p = 0.047), high respiration rate (>/=21/min) (OR 1.67, 95% CI, 1.00-2.79, p = 0.048), and supplemental oxygen use (OR 2.69, 95% CI, 1.60-4.52, p < 0.001). CONCLUSIONS: We observed a significant association of certain factors with increased likelihood of APCU death in patients with advanced cancer. These findings need to be validated in a larger prospective study to develop a model for predicting APCU mortality for patients with advanced cancer.
GOALS OF WORK: Predicting inpatient mortality has clinical and financial implications and helps improve the care of patients with advanced cancer and their families. Models with excellent validity and reliability are available for mortality prediction in intensive care units. The purpose of the current study was to determine factors associated with increased likelihood of mortality in an acute palliative care unit (APCU). PATIENTS AND METHODS: We retrospectively reviewed the medical records of 500 patients admitted to the APCU. Basic characteristics and information on symptom intensity, vital signs, relevant laboratory tests, and the presence or absence of delirium were obtained from the records of the consultation that preceded the APCU admission. Univariate and multivariate analyses were conducted to compare characteristics of patients who died in the APCU with characteristics of those who were discharged alive. MAIN RESULTS: Of the 500 patients admitted to the APCU, 124 (25%) died. Factors that were jointly prognostic for death, using multivariate analysis were younger age (odds ratio [OR] for older patients [>/=65] 0.43, 95% confidence interval [CI], 0.25-0.73, p < 0.001), admission from another oncology floor (OR 5.64, 95% CI, 1.82-17.44, p = 0.003), hyponatremia (OR 3.02, 95% CI, 1.76-5.17, p < 0.001), hypernatremia (OR 4.14, 95% CI, 1.25-13.75, p = 0.020), high blood urea nitrogen (BUN) (OR 1.95, 95% CI, 1.15-3.30, p = 0.013), high heart rate (>/=101 bpm) (OR 1.72, 95% CI, 1.01-2.93, p = 0.047), high respiration rate (>/=21/min) (OR 1.67, 95% CI, 1.00-2.79, p = 0.048), and supplemental oxygen use (OR 2.69, 95% CI, 1.60-4.52, p < 0.001). CONCLUSIONS: We observed a significant association of certain factors with increased likelihood of APCU death in patients with advanced cancer. These findings need to be validated in a larger prospective study to develop a model for predicting APCU mortality for patients with advanced cancer.
Authors: C P Escalante; C G Martin; L S Elting; K J Price; E F Manzullo; M A Weiser; T S Harle; S B Cantor; E B Rubenstein Journal: J Pain Symptom Manage Date: 2000-11 Impact factor: 3.612
Authors: Ezekiel J Emanuel; Yinong Young-Xu; Norman G Levinsky; Gail Gazelle; Olga Saynina; Arlene S Ash Journal: Ann Intern Med Date: 2003-04-15 Impact factor: 25.391
Authors: David Hausner; Nanor Kevork; Ashley Pope; Breffni Hannon; John Bryson; Jenny Lau; Gary Rodin; Lisa W Le; Camilla Zimmermann Journal: Support Care Cancer Date: 2018-05-30 Impact factor: 3.603
Authors: Kerstin Kremeike; Ricarda M L Wetter; Volker Burst; Raymond Voltz; Kathrin Kuhr; Steffen T Simon Journal: Support Care Cancer Date: 2017-08-18 Impact factor: 3.603