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Predictive performance of six mortality risk scores and the development of a novel model in a prospective cohort of patients undergoing valve surgery secondary to rheumatic fever

BACKGROUND: Mortality prediction after cardiac procedures is an essential tool in clinical decision making. Although rheumatic cardiac disease remains a major cause of heart surgery in the world no previous study validated risk scores in a sample exclusively with this condition. OBJECTIVES: Develop...

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Autores principales: Mejia, Omar A. V., Antunes, Manuel J., Goncharov, Maxim, Dallan, Luís R. P., Veronese, Elinthon, Lapenna, Gisele A., Lisboa, Luiz A. F., Dallan, Luís A. O., Brandão, Carlos M. A., Zubelli, Jorge, Tarasoutchi, Flávio, Pomerantzeff, Pablo M. A., Jatene, Fabio B.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6034795/
https://www.ncbi.nlm.nih.gov/pubmed/29979692
http://dx.doi.org/10.1371/journal.pone.0199277
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author Mejia, Omar A. V.
Antunes, Manuel J.
Goncharov, Maxim
Dallan, Luís R. P.
Veronese, Elinthon
Lapenna, Gisele A.
Lisboa, Luiz A. F.
Dallan, Luís A. O.
Brandão, Carlos M. A.
Zubelli, Jorge
Tarasoutchi, Flávio
Pomerantzeff, Pablo M. A.
Jatene, Fabio B.
author_facet Mejia, Omar A. V.
Antunes, Manuel J.
Goncharov, Maxim
Dallan, Luís R. P.
Veronese, Elinthon
Lapenna, Gisele A.
Lisboa, Luiz A. F.
Dallan, Luís A. O.
Brandão, Carlos M. A.
Zubelli, Jorge
Tarasoutchi, Flávio
Pomerantzeff, Pablo M. A.
Jatene, Fabio B.
author_sort Mejia, Omar A. V.
collection PubMed
description BACKGROUND: Mortality prediction after cardiac procedures is an essential tool in clinical decision making. Although rheumatic cardiac disease remains a major cause of heart surgery in the world no previous study validated risk scores in a sample exclusively with this condition. OBJECTIVES: Develop a novel predictive model focused on mortality prediction among patients undergoing cardiac surgery secondary to rheumatic valve conditions. METHODS: We conducted prospective consecutive all-comers patients with rheumatic heart disease (RHD) referred for surgical treatment of valve disease between May 2010 and July of 2015. Risk scores for hospital mortality were calculated using the 2000 Bernstein-Parsonnet, EuroSCORE II, InsCor, AmblerSCORE, GuaragnaSCORE, and the New York SCORE. In addition, we developed the rheumatic heart valve surgery score (RheSCORE). RESULTS: A total of 2,919 RHD patients underwent heart valve surgery. After evaluating 13 different models, the top performing areas under the curve were achieved using Random Forest (0.982) and Neural Network (0.952). Most influential predictors across all models included left atrium size, high creatinine values, a tricuspid procedure, reoperation and pulmonary hypertension. Areas under the curve for previously developed scores were all below the performance for the RheSCORE model: 2000 Bernstein-Parsonnet (0.876), EuroSCORE II (0.857), InsCor (0.835), Ambler (0.831), Guaragna (0.816) and the New York score (0.834). A web application is presented where researchers and providers can calculate predicted mortality based on the RheSCORE. CONCLUSIONS: The RheSCORE model outperformed pre-existing scores in a sample of patients with rheumatic cardiac disease.
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spelling pubmed-60347952018-07-19 Predictive performance of six mortality risk scores and the development of a novel model in a prospective cohort of patients undergoing valve surgery secondary to rheumatic fever Mejia, Omar A. V. Antunes, Manuel J. Goncharov, Maxim Dallan, Luís R. P. Veronese, Elinthon Lapenna, Gisele A. Lisboa, Luiz A. F. Dallan, Luís A. O. Brandão, Carlos M. A. Zubelli, Jorge Tarasoutchi, Flávio Pomerantzeff, Pablo M. A. Jatene, Fabio B. PLoS One Research Article BACKGROUND: Mortality prediction after cardiac procedures is an essential tool in clinical decision making. Although rheumatic cardiac disease remains a major cause of heart surgery in the world no previous study validated risk scores in a sample exclusively with this condition. OBJECTIVES: Develop a novel predictive model focused on mortality prediction among patients undergoing cardiac surgery secondary to rheumatic valve conditions. METHODS: We conducted prospective consecutive all-comers patients with rheumatic heart disease (RHD) referred for surgical treatment of valve disease between May 2010 and July of 2015. Risk scores for hospital mortality were calculated using the 2000 Bernstein-Parsonnet, EuroSCORE II, InsCor, AmblerSCORE, GuaragnaSCORE, and the New York SCORE. In addition, we developed the rheumatic heart valve surgery score (RheSCORE). RESULTS: A total of 2,919 RHD patients underwent heart valve surgery. After evaluating 13 different models, the top performing areas under the curve were achieved using Random Forest (0.982) and Neural Network (0.952). Most influential predictors across all models included left atrium size, high creatinine values, a tricuspid procedure, reoperation and pulmonary hypertension. Areas under the curve for previously developed scores were all below the performance for the RheSCORE model: 2000 Bernstein-Parsonnet (0.876), EuroSCORE II (0.857), InsCor (0.835), Ambler (0.831), Guaragna (0.816) and the New York score (0.834). A web application is presented where researchers and providers can calculate predicted mortality based on the RheSCORE. CONCLUSIONS: The RheSCORE model outperformed pre-existing scores in a sample of patients with rheumatic cardiac disease. Public Library of Science 2018-07-06 /pmc/articles/PMC6034795/ /pubmed/29979692 http://dx.doi.org/10.1371/journal.pone.0199277 Text en © 2018 Mejia et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Mejia, Omar A. V.
Antunes, Manuel J.
Goncharov, Maxim
Dallan, Luís R. P.
Veronese, Elinthon
Lapenna, Gisele A.
Lisboa, Luiz A. F.
Dallan, Luís A. O.
Brandão, Carlos M. A.
Zubelli, Jorge
Tarasoutchi, Flávio
Pomerantzeff, Pablo M. A.
Jatene, Fabio B.
Predictive performance of six mortality risk scores and the development of a novel model in a prospective cohort of patients undergoing valve surgery secondary to rheumatic fever
title Predictive performance of six mortality risk scores and the development of a novel model in a prospective cohort of patients undergoing valve surgery secondary to rheumatic fever
title_full Predictive performance of six mortality risk scores and the development of a novel model in a prospective cohort of patients undergoing valve surgery secondary to rheumatic fever
title_fullStr Predictive performance of six mortality risk scores and the development of a novel model in a prospective cohort of patients undergoing valve surgery secondary to rheumatic fever
title_full_unstemmed Predictive performance of six mortality risk scores and the development of a novel model in a prospective cohort of patients undergoing valve surgery secondary to rheumatic fever
title_short Predictive performance of six mortality risk scores and the development of a novel model in a prospective cohort of patients undergoing valve surgery secondary to rheumatic fever
title_sort predictive performance of six mortality risk scores and the development of a novel model in a prospective cohort of patients undergoing valve surgery secondary to rheumatic fever
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6034795/
https://www.ncbi.nlm.nih.gov/pubmed/29979692
http://dx.doi.org/10.1371/journal.pone.0199277
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