Research on the Method of Predicting Fractional Flow Reserve Based on Multiple Independent Risk Factors
The use of diameter stenosis (DS), as revealed by coronary angiography, for predicting fractional flow reserve (FFR) usually results in a high error rate of detection. In this study, we investigated a method for predicting FFR in patients with coronary stenosis based on multiple independent risk fac...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2021-08-01
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| Series: | Frontiers in Physiology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fphys.2021.716877/full |
| _version_ | 1818884253584195584 |
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| author | Honghui Zhang Honghui Zhang Gaoyang Li Qianwen Hou Yinlong Yang Hongge Wei Yujia Yang Zhuoran Qu Jinjie Xie Aike Qiao |
| author_facet | Honghui Zhang Honghui Zhang Gaoyang Li Qianwen Hou Yinlong Yang Hongge Wei Yujia Yang Zhuoran Qu Jinjie Xie Aike Qiao |
| author_sort | Honghui Zhang |
| collection | DOAJ |
| description | The use of diameter stenosis (DS), as revealed by coronary angiography, for predicting fractional flow reserve (FFR) usually results in a high error rate of detection. In this study, we investigated a method for predicting FFR in patients with coronary stenosis based on multiple independent risk factors. The aim of the study was to improve the accuracy of detection. First, we searched the existing literature to identify multiple independent risk factors and then calculated the corresponding odds ratios. The improved analytic hierarchy process (IAHP) was then used to determine the weighted value of each independent risk factor, based on the corresponding odds ratio. Next, we developed a novel method, based on the top seven independent risk factors with the highest weighted values, to predict FFR. This model was then used to predict the FFR of 253 patients with coronary stenosis, and the results were then compared with previous methods (DS alone and a simplified scoring system). In addition to DS, we identified a range of other independent risk factors, with the highest weighted values, for predicting FFR, including gender, body mass index, location of stenosis, type of coronary artery distribution, left ventricular ejection fraction, and left myocardial mass. The area under the receiver-operating characteristic curve (AUC) for the newly developed method was 84.3% (95% CI: 79.2–89.4%), which was larger than 65.3% (95% CI: 61.5–69.1%) of DS alone and 74.8% (95% CI: 68.4–81.2%) of the existing simplified scoring system. The newly developed method, based on multiple independent risk factors, effectively improves the prediction accuracy for FFR. |
| first_indexed | 2024-12-19T15:46:37Z |
| format | Article |
| id | doaj.art-b22430b75fe9461c803fe3ce705ef05c |
| institution | Directory Open Access Journal |
| issn | 1664-042X |
| language | English |
| last_indexed | 2024-12-19T15:46:37Z |
| publishDate | 2021-08-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Physiology |
| spelling | doaj.art-b22430b75fe9461c803fe3ce705ef05c2022-12-21T20:15:19ZengFrontiers Media S.A.Frontiers in Physiology1664-042X2021-08-011210.3389/fphys.2021.716877716877Research on the Method of Predicting Fractional Flow Reserve Based on Multiple Independent Risk FactorsHonghui Zhang0Honghui Zhang1Gaoyang Li2Qianwen Hou3Yinlong Yang4Hongge Wei5Yujia Yang6Zhuoran Qu7Jinjie Xie8Aike Qiao9Faculty of Environment and Life, Beijing University of Technology, Beijing, ChinaCollege of Engineering, Inner Mongolia University for Nationalities, Tongliao, ChinaInstitute of Fluid Science, Tohoku University, Miyagi, JapanFaculty of Environment and Life, Beijing University of Technology, Beijing, ChinaFaculty of Environment and Life, Beijing University of Technology, Beijing, ChinaFaculty of Environment and Life, Beijing University of Technology, Beijing, ChinaFaculty of Environment and Life, Beijing University of Technology, Beijing, ChinaFaculty of Environment and Life, Beijing University of Technology, Beijing, ChinaBeijing Anzhen Hospital, Capital Medical University, Beijing, ChinaFaculty of Environment and Life, Beijing University of Technology, Beijing, ChinaThe use of diameter stenosis (DS), as revealed by coronary angiography, for predicting fractional flow reserve (FFR) usually results in a high error rate of detection. In this study, we investigated a method for predicting FFR in patients with coronary stenosis based on multiple independent risk factors. The aim of the study was to improve the accuracy of detection. First, we searched the existing literature to identify multiple independent risk factors and then calculated the corresponding odds ratios. The improved analytic hierarchy process (IAHP) was then used to determine the weighted value of each independent risk factor, based on the corresponding odds ratio. Next, we developed a novel method, based on the top seven independent risk factors with the highest weighted values, to predict FFR. This model was then used to predict the FFR of 253 patients with coronary stenosis, and the results were then compared with previous methods (DS alone and a simplified scoring system). In addition to DS, we identified a range of other independent risk factors, with the highest weighted values, for predicting FFR, including gender, body mass index, location of stenosis, type of coronary artery distribution, left ventricular ejection fraction, and left myocardial mass. The area under the receiver-operating characteristic curve (AUC) for the newly developed method was 84.3% (95% CI: 79.2–89.4%), which was larger than 65.3% (95% CI: 61.5–69.1%) of DS alone and 74.8% (95% CI: 68.4–81.2%) of the existing simplified scoring system. The newly developed method, based on multiple independent risk factors, effectively improves the prediction accuracy for FFR.https://www.frontiersin.org/articles/10.3389/fphys.2021.716877/fullfractional flow reservecoronary stenosismultiple independent risk factorsimproved analytic hierarchy process (IAHP)coronary heart disease (CAD) |
| spellingShingle | Honghui Zhang Honghui Zhang Gaoyang Li Qianwen Hou Yinlong Yang Hongge Wei Yujia Yang Zhuoran Qu Jinjie Xie Aike Qiao Research on the Method of Predicting Fractional Flow Reserve Based on Multiple Independent Risk Factors Frontiers in Physiology fractional flow reserve coronary stenosis multiple independent risk factors improved analytic hierarchy process (IAHP) coronary heart disease (CAD) |
| title | Research on the Method of Predicting Fractional Flow Reserve Based on Multiple Independent Risk Factors |
| title_full | Research on the Method of Predicting Fractional Flow Reserve Based on Multiple Independent Risk Factors |
| title_fullStr | Research on the Method of Predicting Fractional Flow Reserve Based on Multiple Independent Risk Factors |
| title_full_unstemmed | Research on the Method of Predicting Fractional Flow Reserve Based on Multiple Independent Risk Factors |
| title_short | Research on the Method of Predicting Fractional Flow Reserve Based on Multiple Independent Risk Factors |
| title_sort | research on the method of predicting fractional flow reserve based on multiple independent risk factors |
| topic | fractional flow reserve coronary stenosis multiple independent risk factors improved analytic hierarchy process (IAHP) coronary heart disease (CAD) |
| url | https://www.frontiersin.org/articles/10.3389/fphys.2021.716877/full |
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