Predicting heart failure outcome from cardiac and comorbid conditions: The 3C-HF score

Prognostic stratification in heart failure (HF) is crucial to guide clinical management and treatment decision-making. Currently available models to predict HF outcome have multiple limitations. We developed a simple risk stratification model, based on routinely available clinical information includ...

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Published inInternational journal of cardiology Vol. 163; no. 2; pp. 206 - 211
Main Authors Senni, Michele, Parrella, Piervirgilio, De Maria, Renata, Cottini, Ciro, Böhm, Michael, Ponikowski, Piotr, Filippatos, Gerasimos, Tribouilloy, Christophe, Di Lenarda, Andrea, Oliva, Fabrizio, Pulignano, Giovanni, Cicoira, Mariantonietta, Nodari, Savina, Porcu, Maurizio, Cioffi, Gianni, Gabrielli, Domenico, Parodi, Oberdan, Ferrazzi, Paolo, Gavazzi, Antonello
Format Journal Article
LanguageEnglish
Published Shannon Elsevier Ireland Ltd 20.02.2013
Elsevier
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Online AccessGet full text
ISSN0167-5273
1874-1754
1874-1754
DOI10.1016/j.ijcard.2011.10.071

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Abstract Prognostic stratification in heart failure (HF) is crucial to guide clinical management and treatment decision-making. Currently available models to predict HF outcome have multiple limitations. We developed a simple risk stratification model, based on routinely available clinical information including comorbidities, the Cardiac and Comorbid Conditions HF (3C-HF) Score, to predict all-cause 1-year mortality in HF patients. We recruited in a cohort study 6274 consecutive HF patients at 24 Cardiology and Internal Medicine Units in Europe. 2016 subjects formed the derivation cohort and 4258 the validation cohort. We entered information on cardiac and comorbid candidate prognostic predictors in a multivariable model to predict 1-year outcome. Median age was 69years, 35.8% were female, 20.6% had a normal ejection fraction, and 65% had at least one comorbidity. During 5861 person-years follow-up, 12.1% of the patients met the study end-point of all-cause death (n=750) or urgent transplantation (n=9). The variables that contributed to outcome prediction, listed in decreasing discriminating ability, were: New York Heart Association class III–IV, left ventricular ejection fraction <20%, no beta-blocker, no renin–angiotensin system inhibitor, severe valve heart disease, atrial fibrillation, diabetes with micro or macroangiopathy, renal dysfunction, anemia, hypertension and older age. The C statistic for 1-year all-cause mortality was 0.87 for the derivation and 0.82 for the validation cohort. The 3C-HF score, based on easy-to-obtain cardiac and comorbid conditions and applicable to the 1-year time span, represents a simple and valuable tool to improve the prognostic stratification of HF patients in daily practice.
AbstractList Prognostic stratification in heart failure (HF) is crucial to guide clinical management and treatment decision-making. Currently available models to predict HF outcome have multiple limitations. We developed a simple risk stratification model, based on routinely available clinical information including comorbidities, the Cardiac and Comorbid Conditions HF (3C-HF) Score, to predict all-cause 1-year mortality in HF patients. We recruited in a cohort study 6274 consecutive HF patients at 24 Cardiology and Internal Medicine Units in Europe. 2016 subjects formed the derivation cohort and 4258 the validation cohort. We entered information on cardiac and comorbid candidate prognostic predictors in a multivariable model to predict 1-year outcome. Median age was 69 years, 35.8% were female, 20.6% had a normal ejection fraction, and 65% had at least one comorbidity. During 5861 person-years follow-up, 12.1% of the patients met the study end-point of all-cause death (n=750) or urgent transplantation (n=9). The variables that contributed to outcome prediction, listed in decreasing discriminating ability, were: New York Heart Association class III-IV, left ventricular ejection fraction <20%, no beta-blocker, no renin-angiotensin system inhibitor, severe valve heart disease, atrial fibrillation, diabetes with micro or macroangiopathy, renal dysfunction, anemia, hypertension and older age. The C statistic for 1-year all-cause mortality was 0.87 for the derivation and 0.82 for the validation cohort. The 3C-HF score, based on easy-to-obtain cardiac and comorbid conditions and applicable to the 1-year time span, represents a simple and valuable tool to improve the prognostic stratification of HF patients in daily practice.
Prognostic stratification in heart failure (HF) is crucial to guide clinical management and treatment decision-making. Currently available models to predict HF outcome have multiple limitations. We developed a simple risk stratification model, based on routinely available clinical information including comorbidities, the Cardiac and Comorbid Conditions HF (3C-HF) Score, to predict all-cause 1-year mortality in HF patients. We recruited in a cohort study 6274 consecutive HF patients at 24 Cardiology and Internal Medicine Units in Europe. 2016 subjects formed the derivation cohort and 4258 the validation cohort. We entered information on cardiac and comorbid candidate prognostic predictors in a multivariable model to predict 1-year outcome. Median age was 69years, 35.8% were female, 20.6% had a normal ejection fraction, and 65% had at least one comorbidity. During 5861 person-years follow-up, 12.1% of the patients met the study end-point of all-cause death (n=750) or urgent transplantation (n=9). The variables that contributed to outcome prediction, listed in decreasing discriminating ability, were: New York Heart Association class III–IV, left ventricular ejection fraction <20%, no beta-blocker, no renin–angiotensin system inhibitor, severe valve heart disease, atrial fibrillation, diabetes with micro or macroangiopathy, renal dysfunction, anemia, hypertension and older age. The C statistic for 1-year all-cause mortality was 0.87 for the derivation and 0.82 for the validation cohort. The 3C-HF score, based on easy-to-obtain cardiac and comorbid conditions and applicable to the 1-year time span, represents a simple and valuable tool to improve the prognostic stratification of HF patients in daily practice.
Abstract Background Prognostic stratification in heart failure (HF) is crucial to guide clinical management and treatment decision-making. Currently available models to predict HF outcome have multiple limitations. We developed a simple risk stratification model, based on routinely available clinical information including comorbidities, the Cardiac and Comorbid Conditions HF (3C-HF) Score, to predict all-cause 1-year mortality in HF patients. Methods We recruited in a cohort study 6274 consecutive HF patients at 24 Cardiology and Internal Medicine Units in Europe. 2016 subjects formed the derivation cohort and 4258 the validation cohort. We entered information on cardiac and comorbid candidate prognostic predictors in a multivariable model to predict 1-year outcome. Results Median age was 69 years, 35.8% were female, 20.6% had a normal ejection fraction, and 65% had at least one comorbidity. During 5861 person-years follow-up, 12.1% of the patients met the study end-point of all-cause death (n = 750) or urgent transplantation (n = 9). The variables that contributed to outcome prediction, listed in decreasing discriminating ability, were: New York Heart Association class III–IV, left ventricular ejection fraction < 20%, no beta-blocker, no renin–angiotensin system inhibitor, severe valve heart disease, atrial fibrillation, diabetes with micro or macroangiopathy, renal dysfunction, anemia, hypertension and older age. The C statistic for 1-year all-cause mortality was 0.87 for the derivation and 0.82 for the validation cohort. Conclusions The 3C-HF score, based on easy-to-obtain cardiac and comorbid conditions and applicable to the 1-year time span, represents a simple and valuable tool to improve the prognostic stratification of HF patients in daily practice.
Prognostic stratification in heart failure (HF) is crucial to guide clinical management and treatment decision-making. Currently available models to predict HF outcome have multiple limitations. We developed a simple risk stratification model, based on routinely available clinical information including comorbidities, the Cardiac and Comorbid Conditions HF (3C-HF) Score, to predict all-cause 1-year mortality in HF patients.BACKGROUNDPrognostic stratification in heart failure (HF) is crucial to guide clinical management and treatment decision-making. Currently available models to predict HF outcome have multiple limitations. We developed a simple risk stratification model, based on routinely available clinical information including comorbidities, the Cardiac and Comorbid Conditions HF (3C-HF) Score, to predict all-cause 1-year mortality in HF patients.We recruited in a cohort study 6274 consecutive HF patients at 24 Cardiology and Internal Medicine Units in Europe. 2016 subjects formed the derivation cohort and 4258 the validation cohort. We entered information on cardiac and comorbid candidate prognostic predictors in a multivariable model to predict 1-year outcome.METHODSWe recruited in a cohort study 6274 consecutive HF patients at 24 Cardiology and Internal Medicine Units in Europe. 2016 subjects formed the derivation cohort and 4258 the validation cohort. We entered information on cardiac and comorbid candidate prognostic predictors in a multivariable model to predict 1-year outcome.Median age was 69 years, 35.8% were female, 20.6% had a normal ejection fraction, and 65% had at least one comorbidity. During 5861 person-years follow-up, 12.1% of the patients met the study end-point of all-cause death (n=750) or urgent transplantation (n=9). The variables that contributed to outcome prediction, listed in decreasing discriminating ability, were: New York Heart Association class III-IV, left ventricular ejection fraction <20%, no beta-blocker, no renin-angiotensin system inhibitor, severe valve heart disease, atrial fibrillation, diabetes with micro or macroangiopathy, renal dysfunction, anemia, hypertension and older age. The C statistic for 1-year all-cause mortality was 0.87 for the derivation and 0.82 for the validation cohort.RESULTSMedian age was 69 years, 35.8% were female, 20.6% had a normal ejection fraction, and 65% had at least one comorbidity. During 5861 person-years follow-up, 12.1% of the patients met the study end-point of all-cause death (n=750) or urgent transplantation (n=9). The variables that contributed to outcome prediction, listed in decreasing discriminating ability, were: New York Heart Association class III-IV, left ventricular ejection fraction <20%, no beta-blocker, no renin-angiotensin system inhibitor, severe valve heart disease, atrial fibrillation, diabetes with micro or macroangiopathy, renal dysfunction, anemia, hypertension and older age. The C statistic for 1-year all-cause mortality was 0.87 for the derivation and 0.82 for the validation cohort.The 3C-HF score, based on easy-to-obtain cardiac and comorbid conditions and applicable to the 1-year time span, represents a simple and valuable tool to improve the prognostic stratification of HF patients in daily practice.CONCLUSIONSThe 3C-HF score, based on easy-to-obtain cardiac and comorbid conditions and applicable to the 1-year time span, represents a simple and valuable tool to improve the prognostic stratification of HF patients in daily practice.
Author Cicoira, Mariantonietta
Cioffi, Gianni
Parodi, Oberdan
Parrella, Piervirgilio
Filippatos, Gerasimos
De Maria, Renata
Ponikowski, Piotr
Oliva, Fabrizio
Ferrazzi, Paolo
Porcu, Maurizio
Di Lenarda, Andrea
Gavazzi, Antonello
Pulignano, Giovanni
Böhm, Michael
Tribouilloy, Christophe
Cottini, Ciro
Nodari, Savina
Gabrielli, Domenico
Senni, Michele
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  organization: Attikon University Hospital, Athens, Greece
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  organization: Service de Cardiologie, Hopital Sud, University of Amiens, France
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  organization: Divisione di Cardiologia, Azienda Ospedale Università Ospedali Riuniti Trieste, Italy
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  surname: Pulignano
  fullname: Pulignano, Giovanni
  organization: Dipartimento Cardiovascolare, Ospedale San Camillo, Roma, Italy
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  givenname: Mariantonietta
  surname: Cicoira
  fullname: Cicoira, Mariantonietta
  organization: Divisione di Cardiologia, Dipartimento di Scienze Biomediche e Chirurgiche, Università di Verona, Italy
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  surname: Nodari
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  surname: Parodi
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ContentType Journal Article
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1874-1754
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IsPeerReviewed true
IsScholarly true
Issue 2
Keywords Heart failure
Prognosis
Comorbidities
Risk models
Heart
Heart disease
Risk factor
Cardiovascular disease
Risk
Models
Cardiology
Language English
License https://www.elsevier.com/tdm/userlicense/1.0
CC BY 4.0
Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.
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  article-title: The Euro Heart Failure survey programme—a survey on the quality of care among patients with heart failure in Europe
  publication-title: Eur Heart J
  doi: 10.1016/S0195-668X(02)00823-0
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Snippet Prognostic stratification in heart failure (HF) is crucial to guide clinical management and treatment decision-making. Currently available models to predict HF...
Abstract Background Prognostic stratification in heart failure (HF) is crucial to guide clinical management and treatment decision-making. Currently available...
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StartPage 206
SubjectTerms Aged
Biological and medical sciences
Cardiology. Vascular system
Cardiovascular
Comorbidities
Female
Heart
Heart failure
Heart Failure - complications
Heart failure, cardiogenic pulmonary edema, cardiac enlargement
Humans
Male
Medical sciences
Middle Aged
Prognosis
Prospective Studies
Retrospective Studies
Risk models
Severity of Illness Index
Title Predicting heart failure outcome from cardiac and comorbid conditions: The 3C-HF score
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https://www.clinicalkey.es/playcontent/1-s2.0-S0167527311019450
https://dx.doi.org/10.1016/j.ijcard.2011.10.071
https://www.ncbi.nlm.nih.gov/pubmed/22130225
https://www.proquest.com/docview/1285080434
Volume 163
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