Usefulness of regional right ventricular and right atrial strain for prediction of early and late right ventricular failure following a left ventricular assist device implant: A machine learning approach

接收机工作特性 心脏病学 内科学 医学 置信区间 心力衰竭 逻辑回归 右心室衰竭 心室压 心室 血压
作者
Diego Bellavia,Attilio Iacovoni,Valentina Agnese,Calogero Falletta,Claudia Coronnello,Salvatore Pasta,Giuseppina Novo,Gabriele Di Gesaro,Michele Senni,Joseph F. Maalouf,Sergio Sciacca,Michele Pilato,Marc A. Simon,Francesco Clemenza,Sir John Gorcsan
出处
期刊:International Journal of Artificial Organs [SAGE]
卷期号:43 (5): 297-314 被引量:18
标识
DOI:10.1177/0391398819884941
摘要

Identifying candidates for left ventricular assist device surgery at risk of right ventricular failure remains difficult. The aim was to identify the most accurate predictors of right ventricular failure among clinical, biological, and imaging markers, assessed by agreement of different supervised machine learning algorithms.Seventy-four patients, referred to HeartWare left ventricular assist device since 2010 in two Italian centers, were recruited. Biomarkers, right ventricular standard, and strain echocardiography, as well as cath-lab measures, were compared among patients who did not develop right ventricular failure (N = 56), those with acute-right ventricular failure (N = 8, 11%) or chronic-right ventricular failure (N = 10, 14%). Logistic regression, penalized logistic regression, linear support vector machines, and naïve Bayes algorithms with leave-one-out validation were used to evaluate the efficiency of any combination of three collected variables in an "all-subsets" approach.Michigan risk score combined with central venous pressure assessed invasively and apical longitudinal systolic strain of the right ventricular-free wall were the most significant predictors of acute-right ventricular failure (maximum receiver operating characteristic-area under the curve = 0.95, 95% confidence interval = 0.91-1.00, by the naïve Bayes), while the right ventricular-free wall systolic strain of the middle segment, right atrial strain (QRS-synced), and tricuspid annular plane systolic excursion were the most significant predictors of Chronic-RVF (receiver operating characteristic-area under the curve = 0.97, 95% confidence interval = 0.91-1.00, according to naïve Bayes).Apical right ventricular strain as well as right atrial strain provides complementary information, both critical to predict acute-right ventricular failure and chronic-right ventricular failure, respectively.
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