European Journal of Heart Failure · 2018 · 62 citations · 31 references
MedicineCardiologyInternal MedicineClinical CardiologyClinical EpidemiologySurvival AnalysisCardiac AssessmentCardiac Risk AssessmentCardiovascular DiseaseHeart FailureSurvival OutcomesSurvival PredictionCardiac Outcome AssessmentHeart Failure Risk PredictionPilot Study Design
BACKGROUND: The Surprise Question: 'would you be surprised if this patient were to die within the next year?' has been shown to predict mortality in patients with chronic kidney disease and cancer. This prospective study aimed to determine whether the Surprise Question could identify heart failure patients with a prognosis of less than 1 year, and whether the Surprise Question can be used by different healthcare professionals. METHODS AND RESULTS: Overall, 129 consecutive patients admitted with decompensated heart failure were included. Doctors and nurses were asked to provide a 'surprised' or 'not surprised' response to the Surprise Question for each patient. Patients were followed up until death or 1 year following study inclusion. The sensitivity, specificity, positive predictive value and negative predictive value of the Surprise Question were assessed. Cox regression was used to determine covariates significantly associated with survival. The Surprise Question showed excellent sensitivity (0.85) and negative predictive value (0.88) but only fair specificity (0.59) and positive predictive value (0.52) when asked of cardiologists. There were similar levels of accuracy between doctors and specialist nurses. The Surprise Question was significantly associated with all-cause mortality in multivariate regression analysis (hazard ratio 2.8, 95% confidence interval 1.0-7.9, P = 0.046). CONCLUSION: This study demonstrates that the Surprise Question can identify heart failure patients within the last year of life. Despite over-classification of patients into the 'not surprised' category, the Surprise Question identified nearly all patients who were within the last year of life, whilst also accurately identifying those unlikely to die.
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The Measurement of Observer Agreement for Categorical Data
J. Richard Landis, Gary G. Koch · Biometrics · 1977 · 78.9K citations · Full text
John G.F. Cleland, Andrew J.S. Coats, Ewa A. Jankowska et al. · PubMed · 2021 · 19.5K citations
David E. Weissman, Diane E. Meier · Journal of Palliative Medicine · 2010 · 509 citations
Nursing, Health Services Administration, End-of-life Care +12