Ian Ford1, Michele Robertson2, Michel Komajda3, Michael Böhm4, Jeffrey S Borer5, Luigi Tavazzi6, Karl Swedberg7. 1. Robertson Centre for Biostatistics, University of Glasgow, Glasgow, UK. Electronic address: Ian.Ford@glasgow.ac.uk. 2. Robertson Centre for Biostatistics, University of Glasgow, Glasgow, UK. 3. Pierre et Marie Curie Paris VI University, La Pitié-Salpétrière Hospital, Paris, France. 4. Universitätskliniken des Saarlandes, Klinik für Innere Medizin III, Homburg/Saar, Germany. 5. Division of Cardiovascular Medicine, The Howard Gilman Institute for Heart Valve Disease and The Schiavone Institute for Cardiovascular Translational Research, State University of New York Downstate Medical Center, NY, USA. 6. Maria Cecilia Hospital, GVM Care and Research, Ettore Sansavini Health Science Foundation, Cotignola, Italy. 7. Department of Molecular and Clinical Medicine, Sahlgrenska Academy, University of Gothenburg, Göteborg, Sweden.
Abstract
AIMS: We identified easily obtained baseline characteristics associated with outcomes in patients with chronic heart failure (HF) and elevated heart rate (HR) receiving contemporary guideline-recommended therapy in the SHIFT trial, and used them to develop a prognostic model. METHODS: We selected the 10 best predictors for each of four outcomes (cardiovascular death or HF hospitalisation; all-cause mortality; cardiovascular mortality; and HF hospitalisation). All variables with p<0.05 for association were entered into a forward stepwise Cox regression model. Our initial analysis excluded baseline therapies, though randomisation to ivabradine or placebo was forced into the model for the composite endpoint and HF hospitalisation. RESULTS:Increased resting HR, low ejection fraction, raised creatinine, New York Heart Association class III/IV, longer duration of HF, history of left bundle branch block, low systolic blood pressure and, for three models, age were strong predictors of all outcomes. Additional predictors were low body mass index, male gender, ischaemic HF, low total cholesterol, no history of hyperlipidaemia or dyslipidaemia and presence of atrial fibrillation/flutter. The c-statistics for the four outcomes ranged from 67.6% to 69.5%. There was no evidence for lack of fit of the models with the exception of all-cause mortality (p=0.017). Similar results were found including baseline therapies. CONCLUSION: The SHIFT Risk Model includes simple, readily obtainable clinical characteristics to produce important prognostic information in patients with chronic HF, systolic dysfunction, and elevated HR. This may help better calibrate management to individual patient risk.
RCT Entities:
AIMS: We identified easily obtained baseline characteristics associated with outcomes in patients with chronic heart failure (HF) and elevated heart rate (HR) receiving contemporary guideline-recommended therapy in the SHIFT trial, and used them to develop a prognostic model. METHODS: We selected the 10 best predictors for each of four outcomes (cardiovascular death or HF hospitalisation; all-cause mortality; cardiovascular mortality; and HF hospitalisation). All variables with p<0.05 for association were entered into a forward stepwise Cox regression model. Our initial analysis excluded baseline therapies, though randomisation to ivabradine or placebo was forced into the model for the composite endpoint and HF hospitalisation. RESULTS: Increased resting HR, low ejection fraction, raised creatinine, New York Heart Association class III/IV, longer duration of HF, history of left bundle branch block, low systolic blood pressure and, for three models, age were strong predictors of all outcomes. Additional predictors were low body mass index, male gender, ischaemic HF, low total cholesterol, no history of hyperlipidaemia or dyslipidaemia and presence of atrial fibrillation/flutter. The c-statistics for the four outcomes ranged from 67.6% to 69.5%. There was no evidence for lack of fit of the models with the exception of all-cause mortality (p=0.017). Similar results were found including baseline therapies. CONCLUSION: The SHIFT Risk Model includes simple, readily obtainable clinical characteristics to produce important prognostic information in patients with chronic HF, systolic dysfunction, and elevated HR. This may help better calibrate management to individual patient risk.
Authors: Meaghan Lunney; Marinella Ruospo; Patrizia Natale; Robert R Quinn; Paul E Ronksley; Ioannis Konstantinidis; Suetonia C Palmer; Marcello Tonelli; Giovanni Fm Strippoli; Pietro Ravani Journal: Cochrane Database Syst Rev Date: 2020-02-27
Authors: Ramon F Abarquez; Paul Ferdinand M Reganit; Carmen N Chungunco; Jean Alcover; Felix Eduardo R Punzalan; Eugenio B Reyes; Elleen L Cunanan Journal: ASEAN Heart J Date: 2016-03-08