Adam D DeVore1, Melissa A Greiner2, Puza P Sharma3, Laura G Qualls2, Phillip J Schulte4, Lauren B Cooper5, Robert J Mentz5, Peter S Pang6, Gregg C Fonarow7, Lesley H Curtis5, Adrian F Hernandez5. 1. Duke Clinical Research Institute, Duke University School of Medicine, Durham, NC; Department of Medicine, Duke University School of Medicine, Durham, NC. Electronic address: adam.devore@duke.edu. 2. Duke Clinical Research Institute, Duke University School of Medicine, Durham, NC. 3. Novartis Pharmaceuticals Corporation, East Hanover, NJ. 4. Department of Health Sciences Research, Mayo Clinic, Rochester, MN. 5. Duke Clinical Research Institute, Duke University School of Medicine, Durham, NC; Department of Medicine, Duke University School of Medicine, Durham, NC. 6. Indiana University School of Medicine, Indianapolis, IN. 7. Ahmanson-UCLA Cardiomyopathy Center, University of California, Los Angeles, CA.
Abstract
BACKGROUND: A subset of patients hospitalized with acute heart failure experiences in-hospital worsening heart failure, defined as persistent or worsening signs or symptoms requiring an escalation of therapy. METHODS: We analyzed data from the Acute Decompensated Heart Failure National Registry (ADHERE) linked to Medicare claims to develop and validate a risk model for in-hospital worsening heart failure. Our definition of in-hospital worsening heart failure included events such as escalation of medical therapy (eg, inotropic medications) >12hours after admission. We considered candidate risk prediction variables routinely assessed at admission, including age, medical history, biomarkers, and renal function. We used logistic regression with robust standard errors to generate a risk model in a 66% random derivation sample; we validated the model in the remaining 34%. We evaluated the calibration and discrimination of the model in both samples. RESULTS: We evaluated 23,696 patients hospitalized with acute heart failure. Baseline characteristics were well matched in the derivation and validation samples, and the occurrence of in-hospital worsening heart failure was similar in both samples (15.4% and 15.6%, respectively). In the multivariable model, the strongest predictors of in-hospital worsening heart failure were increased troponin and creatinine. The model was well calibrated and had good discrimination in the derivation sample (c statistic, 0.74) and validation sample (c statistic, 0.72). CONCLUSIONS: The ADHERE worsening heart failure risk model is a clinical tool with good discrimination for use in patients hospitalized with acute heart failure to identify those at increased risk for in-hospital worsening heart failure. This tool may be useful to target treatment strategies for patients at high risk for in-hospital worsening heart failure.
BACKGROUND: A subset of patients hospitalized with acute heart failure experiences in-hospital worsening heart failure, defined as persistent or worsening signs or symptoms requiring an escalation of therapy. METHODS: We analyzed data from the Acute Decompensated Heart Failure National Registry (ADHERE) linked to Medicare claims to develop and validate a risk model for in-hospital worsening heart failure. Our definition of in-hospital worsening heart failure included events such as escalation of medical therapy (eg, inotropic medications) >12hours after admission. We considered candidate risk prediction variables routinely assessed at admission, including age, medical history, biomarkers, and renal function. We used logistic regression with robust standard errors to generate a risk model in a 66% random derivation sample; we validated the model in the remaining 34%. We evaluated the calibration and discrimination of the model in both samples. RESULTS: We evaluated 23,696 patients hospitalized with acute heart failure. Baseline characteristics were well matched in the derivation and validation samples, and the occurrence of in-hospital worsening heart failure was similar in both samples (15.4% and 15.6%, respectively). In the multivariable model, the strongest predictors of in-hospital worsening heart failure were increased troponin and creatinine. The model was well calibrated and had good discrimination in the derivation sample (c statistic, 0.74) and validation sample (c statistic, 0.72). CONCLUSIONS: The ADHERE worsening heart failure risk model is a clinical tool with good discrimination for use in patients hospitalized with acute heart failure to identify those at increased risk for in-hospital worsening heart failure. This tool may be useful to target treatment strategies for patients at high risk for in-hospital worsening heart failure.
Authors: Agata Bielecka-Dabrowa; Breno Godoy; Joerg C Schefold; Michael Koziolek; Maciej Banach; Stephan von Haehling Journal: Curr Heart Fail Rep Date: 2018-08
Authors: Gregory J Fermann; Jon W Schrock; Phillip D Levy; Peter Pang; Javed Butler; Anna Marie Chang; Douglas Char; Deborah Diercks; Jin H Han; Brian Hiestand; Chris Hogan; Cathy A Jenkins; Christy Kampe; Yosef Khan; Vijaya A Kumar; Sangil Lee; JoAnn Lindenfeld; Dandan Liu; Karen F Miller; W Frank Peacock; Carolyn M Reilly; Chad Robichaux; Russell L Rothman; Wesley H Self; Adam J Singer; Sarah A Sterling; Alan B Storrow; William B Stubblefield; Cheryl Walsh; John Wilburn; Sean P Collins Journal: J Am Coll Emerg Physicians Open Date: 2022-04-09