Leili Pourafkari1, Samad Ghaffari1, George R Bancroft2, Arezou Tajlil1, Nader D Nader3. 1. Cardiovascular Research Center, Tabriz University of Medical Sciences, Tabriz, Iran. 2. Department of Anesthesiology, University at Buffalo, Buffalo, NY, USA. 3. Department of Anesthesiology, University at Buffalo, Buffalo, NY, USA nnader@buffalo.edu.
Abstract
BACKGROUND: Atrial fibrillation is a complication of mitral valve stenosis that causes several adverse neurologic outcomes. Our objective was to establish a mathematical model to predict the risk of atrial fibrillation in patients with mitral stenosis. METHODS: Of 819 patients with mitral stenosis who were screened, 603 were enrolled in the study and grouped according to whether they were in sinus rhythm or atrial fibrillation. Demographic, echocardiographic, and hemodynamic data were recorded. Logistic regression models were constructed to identify the relative risks for each contributing factor and calculate the probability of developing atrial fibrillation. Receiver operating characteristic curves were plotted. RESULTS: Two hundred (33%) patients had atrial fibrillation; this group was older, in a higher functional class, more likely to have suffered previous thromboembolic events, and had significantly larger left atrial diameters, lower ejection fractions, and lower left atrial appendage emptying flow velocity. The factors independently associated with atrial fibrillation were left atrial strain (odds ratio = 7.53 [4.47-12.69], p < 0.001), right atrial pressure (odds ratio = 1.09 [1.02-1.17], p = 0.01), age (odds ratio = 1.14 [1.05-1.25], p = 0.002), and ejection fraction (odds ratio = 0.92 [0.87-0.97], p = 0.003). The area under the curve for the combined receiver operating characteristic for this model was 0.90 ± 0.12. CONCLUSION: Age, right atrial pressure, ejection fraction, and left atrial strain can be used to construct a mathematical model to predict the development of atrial fibrillation in rheumatic mitral stenosis.
BACKGROUND:Atrial fibrillation is a complication of mitral valve stenosis that causes several adverse neurologic outcomes. Our objective was to establish a mathematical model to predict the risk of atrial fibrillation in patients with mitral stenosis. METHODS: Of 819 patients with mitral stenosis who were screened, 603 were enrolled in the study and grouped according to whether they were in sinus rhythm or atrial fibrillation. Demographic, echocardiographic, and hemodynamic data were recorded. Logistic regression models were constructed to identify the relative risks for each contributing factor and calculate the probability of developing atrial fibrillation. Receiver operating characteristic curves were plotted. RESULTS: Two hundred (33%) patients had atrial fibrillation; this group was older, in a higher functional class, more likely to have suffered previous thromboembolic events, and had significantly larger left atrial diameters, lower ejection fractions, and lower left atrial appendage emptying flow velocity. The factors independently associated with atrial fibrillation were left atrial strain (odds ratio = 7.53 [4.47-12.69], p < 0.001), right atrial pressure (odds ratio = 1.09 [1.02-1.17], p = 0.01), age (odds ratio = 1.14 [1.05-1.25], p = 0.002), and ejection fraction (odds ratio = 0.92 [0.87-0.97], p = 0.003). The area under the curve for the combined receiver operating characteristic for this model was 0.90 ± 0.12. CONCLUSION: Age, right atrial pressure, ejection fraction, and left atrial strain can be used to construct a mathematical model to predict the development of atrial fibrillation in rheumatic mitral stenosis.
Authors: Nan Phyu Sin Toe Myint; Ne Myo Aung; Myint Soe Win; Thu Ya Htut; Anna P Ralph; David A Cooper; Myo Lwin Nyein; Mar Mar Kyi; Josh Hanson Journal: PLoS One Date: 2018-02-21 Impact factor: 3.240
Authors: Jean Jacques Noubiap; Ulrich Flore Nyaga; Aude Laetitia Ndoadoumgue; Jan René Nkeck; Anderson Ngouo; Jean Joel Bigna Journal: Glob Heart Date: 2020-05-18