A novel prognostic tool to predict mortality in patients with atrial fibrillation: The BASIC-AF risk scoreKey messages

Background: This study sought to develop and validate a risk score to predict mortality in patients with atrial fibrillation (AF) after a hospitalization for cardiac reasons. Methods: The new risk score was derived from a prospective cohort of hospitalized patients with concurrent AF. The outcome me...

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Autores principales:	Athanasios Samaras, Anastasios Kartas, Evangelos Akrivos, George Fotos, George Dividis, Dimitra Vasdeki, Eleni Vrana, Georgios Rampidis, Haralambos Karvounis, George Giannakoulas, Apostolos Tzikas
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	atrial fibrillation mortality risk score left atrial volume biomarkers machine learning Diseases of the circulatory (Cardiovascular) system RC666-701
Acceso en línea:	https://doaj.org/article/996d0cf7a666423db5f8a6ab205255f5
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spelling	oai:doaj.org-article:996d0cf7a666423db5f8a6ab205255f52021-11-14T04:31:06ZA novel prognostic tool to predict mortality in patients with atrial fibrillation: The BASIC-AF risk scoreKey messages1109-966610.1016/j.hjc.2021.01.007https://doaj.org/article/996d0cf7a666423db5f8a6ab205255f52021-09-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S1109966621000075https://doaj.org/toc/1109-9666Background: This study sought to develop and validate a risk score to predict mortality in patients with atrial fibrillation (AF) after a hospitalization for cardiac reasons. Methods: The new risk score was derived from a prospective cohort of hospitalized patients with concurrent AF. The outcome measures were all-cause and cardiovascular mortality. Random forest was used for variable selection. A risk points model with predictor variables was developed by weighted Cox regression coefficients and was internally validated by bootstrapping. Results: In total, 1130 patients with AF were included. During a median follow-up of 2 years, 346 (30.6%) patients died and 250 patients had a cardiovascular cause of death. N-terminal pro-B-type natriuretic peptide and high-sensitivity troponin-T were the most important predictors of mortality, followed by indexed left atrial volume, history and type of heart failure, age, history of diabetes mellitus, and intraventricular conduction delay, all forming the BASIC-AF risk score (Biomarkers, Age, ultraSound, Intraventricular conduction delay, and Clinical history). The score had good discrimination for all-cause (c-index = 0.85 and 95% CI 0.82–0.88) and cardiovascular death (c-index = 0.84 and 95% CI 0.81-0.87). The predicted probability of mortality varied more than 50-fold across deciles and adjusted well to observed mortality rates. A decision curve analysis revealed a significant net benefit of using the BASIC-AF risk score to predict the risk of death, when compared with other existing risk schemes. Conclusions: We developed and internally validated a well-performing novel risk score for predicting death in patients with AF. The BASIC-AF risk score included routinely assessed parameters, selected through machine-learning algorithms, and may assist in tailored risk stratification and management of these patients.Athanasios SamarasAnastasios KartasEvangelos AkrivosGeorge FotosGeorge DividisDimitra VasdekiEleni VranaGeorgios RampidisHaralambos KarvounisGeorge GiannakoulasApostolos TzikasElsevierarticleatrial fibrillationmortalityrisk scoreleft atrial volumebiomarkersmachine learningDiseases of the circulatory (Cardiovascular) systemRC666-701ENHellenic Journal of Cardiology, Vol 62, Iss 5, Pp 339-348 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	atrial fibrillation mortality risk score left atrial volume biomarkers machine learning Diseases of the circulatory (Cardiovascular) system RC666-701
spellingShingle	atrial fibrillation mortality risk score left atrial volume biomarkers machine learning Diseases of the circulatory (Cardiovascular) system RC666-701 Athanasios Samaras Anastasios Kartas Evangelos Akrivos George Fotos George Dividis Dimitra Vasdeki Eleni Vrana Georgios Rampidis Haralambos Karvounis George Giannakoulas Apostolos Tzikas A novel prognostic tool to predict mortality in patients with atrial fibrillation: The BASIC-AF risk scoreKey messages
description	Background: This study sought to develop and validate a risk score to predict mortality in patients with atrial fibrillation (AF) after a hospitalization for cardiac reasons. Methods: The new risk score was derived from a prospective cohort of hospitalized patients with concurrent AF. The outcome measures were all-cause and cardiovascular mortality. Random forest was used for variable selection. A risk points model with predictor variables was developed by weighted Cox regression coefficients and was internally validated by bootstrapping. Results: In total, 1130 patients with AF were included. During a median follow-up of 2 years, 346 (30.6%) patients died and 250 patients had a cardiovascular cause of death. N-terminal pro-B-type natriuretic peptide and high-sensitivity troponin-T were the most important predictors of mortality, followed by indexed left atrial volume, history and type of heart failure, age, history of diabetes mellitus, and intraventricular conduction delay, all forming the BASIC-AF risk score (Biomarkers, Age, ultraSound, Intraventricular conduction delay, and Clinical history). The score had good discrimination for all-cause (c-index = 0.85 and 95% CI 0.82–0.88) and cardiovascular death (c-index = 0.84 and 95% CI 0.81-0.87). The predicted probability of mortality varied more than 50-fold across deciles and adjusted well to observed mortality rates. A decision curve analysis revealed a significant net benefit of using the BASIC-AF risk score to predict the risk of death, when compared with other existing risk schemes. Conclusions: We developed and internally validated a well-performing novel risk score for predicting death in patients with AF. The BASIC-AF risk score included routinely assessed parameters, selected through machine-learning algorithms, and may assist in tailored risk stratification and management of these patients.
format	article
author	Athanasios Samaras Anastasios Kartas Evangelos Akrivos George Fotos George Dividis Dimitra Vasdeki Eleni Vrana Georgios Rampidis Haralambos Karvounis George Giannakoulas Apostolos Tzikas
author_facet	Athanasios Samaras Anastasios Kartas Evangelos Akrivos George Fotos George Dividis Dimitra Vasdeki Eleni Vrana Georgios Rampidis Haralambos Karvounis George Giannakoulas Apostolos Tzikas
author_sort	Athanasios Samaras
title	A novel prognostic tool to predict mortality in patients with atrial fibrillation: The BASIC-AF risk scoreKey messages
title_short	A novel prognostic tool to predict mortality in patients with atrial fibrillation: The BASIC-AF risk scoreKey messages
title_full	A novel prognostic tool to predict mortality in patients with atrial fibrillation: The BASIC-AF risk scoreKey messages
title_fullStr	A novel prognostic tool to predict mortality in patients with atrial fibrillation: The BASIC-AF risk scoreKey messages
title_full_unstemmed	A novel prognostic tool to predict mortality in patients with atrial fibrillation: The BASIC-AF risk scoreKey messages
title_sort	novel prognostic tool to predict mortality in patients with atrial fibrillation: the basic-af risk scorekey messages
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/996d0cf7a666423db5f8a6ab205255f5
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A novel prognostic tool to predict mortality in patients with atrial fibrillation: The BASIC-AF risk scoreKey messages

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