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Comment & Response
November 2016

Predicting 30-Day Readmission or Death in Patients With Heart Failure: Looking Beyond the C Statistic

Author Affiliations
  • 1Discipline of Medicine, University of Adelaide, Adelaide, South Australia, Australia
  • 2Center for Outcomes Research and Evaluation, Yale New Haven Hospital, New Haven, Connecticut
  • 3Section of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut
  • 4Robert Wood Johnson Clinical Scholars Program, Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut
  • 5Department of Health Policy and Management, School of Public Health, Yale School of Medicine, New Haven, Connecticut
JAMA Cardiol. 2016;1(8):965. doi:10.1001/jamacardio.2016.3101

To the Editor Huynh et al1 described a new model to predict 30-day death or readmission in patients with heart failure. Using data from 430 patients with heart failure, the model predicted 30-day death or readmission (C statistic = 0.82) or readmission alone (C statistic = 0.80) with superior accuracy compared with their test of a published claims model (C statistic = 0.56).1 First, there is an issue of generalizability in a model with a relatively small sample size and from 1 geographic location. For example, in the model, living alone (hazard ratio, 2.05; 95% CI, 1.12-3.76) and being discharged during the winter (hazard ratio, 1.61; 95% CI, 1.00-3.31) were among the strongest predictors of 30-day death or readmission.1 The effect of these variables may vary considerably by location and country, depending on weather, culture, and social services.

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