中文版 | English
Title

Prediction of Surgical Approach in Mitral Valve Disease by XGBoost Algorithm Based on Echocardiographic Features

Author
Corresponding AuthorXu, Jinfeng; Meng, Chunying; Liu, Yingying
Publication Years
2023-02-01
DOI
Source Title
EISSN
2077-0383
Volume12Issue:3
Abstract
In this study, we aimed to develop a prediction model to assist surgeons in choosing an appropriate surgical approach for mitral valve disease patients. We retrospectively analyzed a total of 143 patients who underwent surgery for mitral valve disease. The XGBoost algorithm was used to establish a predictive model to decide a surgical approach (mitral valve repair or replacement) based on the echocardiographic features of the mitral valve apparatus, such as leaflets, the annulus, and sub-valvular structures. The results showed that the accuracy of the predictive model was 81.09% in predicting the appropriate surgical approach based on the patient's preoperative echocardiography. The result of the predictive model was superior to the traditional complexity score (81.09% vs. 75%). Additionally, the predictive model showed that the three main factors affecting the choice of surgical approach were leaflet restriction, calcification of the leaflet, and perforation or cleft of the leaflet. We developed a novel predictive model using the XGBoost algorithm based on echocardiographic features to assist surgeons in choosing an appropriate surgical approach for patients with mitral valve disease.
Keywords
URL[Source Record]
Indexed By
Language
English
SUSTech Authorship
Corresponding
WOS Research Area
General & Internal Medicine
WOS Subject
Medicine, General & Internal
WOS Accession No
WOS:000931072000001
Publisher
Data Source
Web of Science
Citation statistics
Cited Times [WOS]:0
Document TypeJournal Article
Identifierhttp://kc.sustech.edu.cn/handle/2SGJ60CL/501444
DepartmentShenzhen People's Hospital
Affiliation
1.Jinan Univ, Shenzhen Peoples Hosp, Clin Med Coll 2, Dept Ultrasound, Shenzhen 518020, Peoples R China
2.Jinan Univ, Shenzhen Peoples Hosp, Dept Cardiovasc Surg, Clin Med Coll 2, Shenzhen 518020, Peoples R China
3.Southern Univ Sci & Technol, Affiliated Hosp 1, Shenzhen 518020, Peoples R China
Corresponding Author AffilicationShenzhen People's Hospital
Recommended Citation
GB/T 7714
Lin, Xiaoxuan,Chen, Lixin,Zhang, Defu,et al. Prediction of Surgical Approach in Mitral Valve Disease by XGBoost Algorithm Based on Echocardiographic Features[J]. JOURNAL OF CLINICAL MEDICINE,2023,12(3).
APA
Lin, Xiaoxuan.,Chen, Lixin.,Zhang, Defu.,Luo, Shuyu.,Sheng, Yuanyuan.,...&Liu, Yingying.(2023).Prediction of Surgical Approach in Mitral Valve Disease by XGBoost Algorithm Based on Echocardiographic Features.JOURNAL OF CLINICAL MEDICINE,12(3).
MLA
Lin, Xiaoxuan,et al."Prediction of Surgical Approach in Mitral Valve Disease by XGBoost Algorithm Based on Echocardiographic Features".JOURNAL OF CLINICAL MEDICINE 12.3(2023).
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