Factors Related to Morbidity and Mortality in Patients With Chronic Heart Failure With Systolic Dysfunction The HF-ACTION Predictive Risk Score Model Christopher M. O’Connor, MD*; David J. Whellan, MD, MHS*; Daniel Wojdyla, MSc*; Eric Leifer, PhD*; Robert M. Clare, MS*; Stephen J. Ellis, PhD*; Lawrence J. Fine, MD, DrPH*; Jerome L. Fleg, MD*; Faiez Zannad, MD, PhD*; Steven J. Keteyian, PhD*; Dalane W. Kitzman, MD*; William E. Kraus, MD*; David Rendall, PA-C*; Ileana L. Pin ˜a, MD*; Lawton S. Cooper, MD, MPH*; Mona Fiuzat, PharmD*; Kerry L. Lee, PhD* Background—We aimed to develop a multivariable statistical model for risk stratification in patients with chronic heart failure with systolic dysfunction, using patient data that are routinely collected and easily obtained at the time of initial presentation. Methods and Results—In a cohort of 2331 patients enrolled in the HF-ACTION (Heart Failure: A Controlled Trial Investigating Outcomes of Exercise TraiNing) study (New York Heart Association class II–IV, left ventricular ejection fraction 0.35, randomized to exercise training and usual care versus usual care alone, median follow-up of 2.5 years), we performed risk modeling using Cox proportional hazards models and analyzed the relationship between baseline clinical factors and the primary composite end point of death or all-cause hospitalization and the secondary end point of all-cause death alone. Prognostic relationships for continuous variables were examined using restricted cubic spline functions, and key predictors were identified using a backward variable selection process and bootstrapping methods. For ease of use in clinical practice, point-based risk scores were developed from the risk models. Exercise duration on the baseline cardiopulmonary exercise test was the most important predictor of both the primary end point and all-cause death. Additional important predictors for the primary end point risk model (in descending strength) were Kansas City Cardiomyopathy Questionnaire symptom stability score, higher serum urea nitrogen, and male sex (all P0.0001). Important additional predictors for the mortality risk model were higher serum urea nitrogen, male sex, and lower body mass index (all P0.0001). Conclusions—Risk models using simple, readily obtainable clinical characteristics can provide important prognostic information in ambulatory patients with chronic heart failure with systolic dysfunction. Clinical Trial Registration—URL: http://www.clinicaltrials.gov. Unique identifier: NCT00047437. (Circ Heart Fail. 2012;5:63-71.) Key Words: heart failure  systolic heart failure  risk assessment  Cox proportional hazards models  exercise D espite advances in the treatment of patients with chronic heart failure (HF) with systolic dysfunction, these pa- tients remain at high risk for hospitalization and death. 1 This risk may be attributed to the aging of the population, progressive disease, increasing frequency of HF hospitaliza- tions, and persistently high event rates after decompensated HF episodes, with up to 30% of patients experiencing a serious adverse cardiovascular event or death after a hospital admission for HF. 2 Editorial see p 6 Clinical Perspective on p 71 Timing for the introduction of second-line therapies, in- cluding aldosterone antagonists, resynchronization pacing, Received April 29, 2011; accepted November 10, 2011. From the Duke Clinical Research Institute, Durham, NC (C.M.O., D.W., R.M.C., S.J.E., M.F., D.R., K.L.L.); Thomas Jefferson University, Philadelphia, PA (D.J.W.); National Heart, Lung, and Blood Institute, Bethesda, MD (E.L., L.J.F., J.L.F., L.S.C.); Nancy University, Nancy, France (F.Z.); Henry Ford Hospital, Detroit, MI (S.J.K.); Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, NC (D.W.K.); Departments of Psychiatry and Behavioral Science and Medicine, Duke University School of Medicine, Durham, NC (W.E.K.); and Montefiore Medical Center, New York, NY (I.L.P.). *Drs O’Connor, Whellan, Leifer, Ellis, Fine, Fleg, Zannad, Keteyian, Kitzman, Kraus, Pin ˜a, Cooper, Fiuzat, and Lee and Messrs Wojdyla, Clare, and Rendall contributed equally to this work. The online-only Data Supplement is available with this article at http://circheartfailure.ahajournals.org/lookup/suppl/doi:10.1161/ CIRCHEARTFAILURE.111.963462/-/DC1. Correspondence to Christopher M. O’Connor, MD, DUMC Box 3356, Durham, NC 27710. E-mail Oconn002@mc.duke.edu © 2011 American Heart Association, Inc. Circ Heart Fail is available at http://circheartfailure.ahajournals.org DOI: 10.1161/CIRCHEARTFAILURE.111.963462 63 by guest on October 19, 2017 http://circheartfailure.ahajournals.org/ Downloaded from by guest on October 19, 2017 http://circheartfailure.ahajournals.org/ Downloaded from by guest on October 19, 2017 http://circheartfailure.ahajournals.org/ Downloaded from by guest on October 19, 2017 http://circheartfailure.ahajournals.org/ Downloaded from by guest on October 19, 2017 http://circheartfailure.ahajournals.org/ Downloaded from by guest on October 19, 2017 http://circheartfailure.ahajournals.org/ Downloaded from