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Predicting Disease Progression in Patients with Bicuspid Aortic Stenosis Using Mathematical Modeling

Authors
 Darae Kim  ;  Dongwoo Chae  ;  Chi Young Shim  ;  In-Jeong Cho  ;  Geu-Ru Hong  ;  Kyungsoo Park  ;  Jong-Won Ha 
Citation
 Journal of Clinical Medicine, Vol.8(9) : E1302, 2019 
Journal Title
 Journal of Clinical Medicine 
Issue Date
2019
Keywords
bicuspid aortic valve ; mathematical model ; progression
Abstract
We aimed to develop a mathematical model to predict the progression of aortic stenosis (AS) and aortic dilatation (AD) in bicuspid aortic valve patients. Bicuspid AS patients who underwent at least two serial echocardiograms from 2005 to 2017 were enrolled. Mathematical modeling was undertaken to assess (1) the non-linearity associated with the disease progression and (2) the importance of first visit echocardiogram in predicting the overall prognosis. Models were trained in 126 patients and validated in an additional cohort of 43 patients. AS was best described by a logistic function of time. Patients who showed an increase in mean pressure gradient (MPG) at their first visit relative to baseline (denoted as rapid progressors) showed a significantly faster disease progression overall. The core model parameter reflecting the rate of disease progression, α, was 0.012/month in the rapid progressors and 0.0032/month in the slow progressors (p < 0.0001). AD progression was best described by a simple linear function, with an increment rate of 0.019 mm/month. Validation of models in a separate prospective cohort yielded comparable R squared statistics for predicted outcomes. Our novel disease progression model for bicuspid AS significantly increased prediction power by including subsequent follow-up visit information rather than baseline information alone.
Files in This Item:
T201903600.pdf Download
DOI
10.3390/jcm8091302
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Pharmacology (약리학교실) > 1. Journal Papers
1. College of Medicine (의과대학) > Dept. of Internal Medicine (내과학교실) > 1. Journal Papers
Yonsei Authors
Park, Kyungsoo(박경수) ORCID logo https://orcid.org/0000-0002-6972-1143
Shim, Chi Young(심지영) ORCID logo https://orcid.org/0000-0002-6136-0136
Chae, Dong Woo(채동우) ORCID logo https://orcid.org/0000-0002-7675-3821
Ha, Jong Won(하종원) ORCID logo https://orcid.org/0000-0002-8260-2958
Hong, Geu Ru(홍그루) ORCID logo https://orcid.org/0000-0003-4981-3304
URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/171456
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