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Forecasting the Risk of Heart Failure Hospitalization After Acute Coronary Syndromes: the CORALYS HF Score

2023; Elsevier BV; Volume: 206; Linguagem: Inglês

10.1016/j.amjcard.2023.08.010

1879-1913

Fabrizio D'Ascenzo, Enrico Fabris, Caterina Gregorio, Gianluca Mittone, Ovidio De Filippo, Wojciech Wańha, Sergio Leonardi, Sergio Raposeiras‐Roubín, Alessandra Chinaglia, Alessandra Truffa, Zenon Huczek, Nicola Gaibazzi, Alfonso Ielasi, Bernardo Cortese, Andrea Borin, Beniamino Pagliaro, Iván J. Núñez‐Gil, Fabrizio Ugo, Giorgio Marengo, Lucia Barbieri, Federico Marchini, Piotr Desperak, María Melendo‐Viu, Claudio Montalto, Matteo Bianco, Francesco Bruno, Massimo Mancone, Marcos Ferrández-Escarabajal, Nuccia Morici, Marco Scaglione, Domenico Tuttolomondo, Mariusz Gąsior, Maciej Mazurek, Guglielmo Gallone, Gianluca Campo, Wojciech Wojakowski, Emad Abu Assi, Giulio Stefanini, Gianfranco Sinagra, Gaetano Maria De Ferrari,

Cardiovascular Function and Risk Factors

The present study aimed to identify patients at a higher risk of hospitalization for heart failure (HF) in a population of patients with acute coronary syndrome (ACS) treated with percutaneous coronary revascularization without a history of HF or reduced left ventricular (LV) ejection fraction before the index admission. We performed a Cox regression multivariable analysis with competitive risk and machine learning models on the incideNce and predictOrs of heaRt fAiLure After Acute coronarY Syndrome (CORALYS) registry (NCT 04895176), an international and multicenter study including consecutive patients admitted for ACS in 16 European Centers from 2015 to 2020. Of 14,699 patients, 593 (4.0%) were admitted for the development of HF up to 1 year after the index ACS presentation. A total of 2 different data sets were randomly created, 1 for the derivative cohort including 11,626 patients (80%) and 1 for the validation cohort including 3,073 patients (20%). On the Cox regression multivariable analysis, several variables were associated with the risk of HF hospitalization, with reduced renal function, complete revascularization, and LV ejection fraction as the most relevant ones. The area under the curve at 1 year was 0.75 (0.72 to 0.78) in the derivative cohort, whereas on validation, it was 0.72 (0.67 to 0.77). The machine learning analysis showed a slightly inferior performance. In conclusion, in a large cohort of patients with ACS without a history of HF or LV dysfunction before the index event, the CORALYS HF score identified patients at a higher risk of hospitalization for HF using variables easily accessible at discharge. Further approaches to tackle HF development in this high-risk subset of patients are needed. The present study aimed to identify patients at a higher risk of hospitalization for heart failure (HF) in a population of patients with acute coronary syndrome (ACS) treated with percutaneous coronary revascularization without a history of HF or reduced left ventricular (LV) ejection fraction before the index admission. We performed a Cox regression multivariable analysis with competitive risk and machine learning models on the incideNce and predictOrs of heaRt fAiLure After Acute coronarY Syndrome (CORALYS) registry (NCT 04895176), an international and multicenter study including consecutive patients admitted for ACS in 16 European Centers from 2015 to 2020. Of 14,699 patients, 593 (4.0%) were admitted for the development of HF up to 1 year after the index ACS presentation. A total of 2 different data sets were randomly created, 1 for the derivative cohort including 11,626 patients (80%) and 1 for the validation cohort including 3,073 patients (20%). On the Cox regression multivariable analysis, several variables were associated with the risk of HF hospitalization, with reduced renal function, complete revascularization, and LV ejection fraction as the most relevant ones. The area under the curve at 1 year was 0.75 (0.72 to 0.78) in the derivative cohort, whereas on validation, it was 0.72 (0.67 to 0.77). The machine learning analysis showed a slightly inferior performance. In conclusion, in a large cohort of patients with ACS without a history of HF or LV dysfunction before the index event, the CORALYS HF score identified patients at a higher risk of hospitalization for HF using variables easily accessible at discharge. Further approaches to tackle HF development in this high-risk subset of patients are needed.