Clinical factors associated with severe coronary stenosis in patients undergoing cardiac surgery
Abstract Background Many cardiovascular patients undergoing valve surgeries require coronary angiography (CAG). Positive results may lead to bypass surgery, while negative results require no treatment. Although informative, CAG is costly and exposes patients to significant radiation. This study aime...
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BMC
2025-05-01
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| Series: | BMC Cardiovascular Disorders |
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| Online Access: | https://doi.org/10.1186/s12872-025-04835-0 |
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| author | Rui Wang Wei Gao Xinyu Che Ruopei Shen Chunfeng Dai Yan Xia Ao Chen Danbo Lu Jiaqi Ma Hungju Chen Chenguang Li Zhangwei Chen Juying Qian Junbo Ge |
| author_facet | Rui Wang Wei Gao Xinyu Che Ruopei Shen Chunfeng Dai Yan Xia Ao Chen Danbo Lu Jiaqi Ma Hungju Chen Chenguang Li Zhangwei Chen Juying Qian Junbo Ge |
| author_sort | Rui Wang |
| collection | DOAJ |
| description | Abstract Background Many cardiovascular patients undergoing valve surgeries require coronary angiography (CAG). Positive results may lead to bypass surgery, while negative results require no treatment. Although informative, CAG is costly and exposes patients to significant radiation. This study aimed to develop a model to reduce unnecessary procedures. Methods A retrospective cohort study was conducted on 5,086 patients who underwent valve repair/replacement or other cardiac surgeries at Zhongshan Hospital between 2016 and 2021 and received CAG. Patients treated between 2016 and 2020 formed the training set, while those treated in 2021 constituted the validation set. Severe coronary stenosis was defined as a ≥ 50% reduction in luminal diameter. Logistic regression analysis identified independent predictors in the training set, and a scoring system (Coronary Angiography Positivity Prediction Score) was constructed based on the β-coefficients of each variable. The model was evaluated for discrimination and calibration. Results Among 4,049 patients, 536 (13.2%) had severe coronary stenosis. Independent predictors included age ≥ 60 years, male sex, hypertension, diabetes, hyperlipidemia, and left ventricular ejection fraction ≤ 58%. The scoring system ranged from 0 to 11 points and demonstrated good discrimination, with an area under the receiver operating characteristic curve of 0.715 (95% confidence interval: 0.694–0.740) in the training set. In the high-risk group (≥ 6 points), the probability of severe coronary stenosis was 23.1%, compared to 8% in the low-risk group (< 6 points). The scoring system also performed well in the validation set with the curve of 0.740 (95% CI, 0.695–0.784). Conclusion We developed and validated a scoring system based on six clinical variables to predict severe coronary stenosis in patients undergoing valve surgeries. This tool may help optimize individual treatment strategies and reduce unnecessary CAG procedures. |
| format | Article |
| id | doaj-art-db7a736a4910423fa2fb2a98a1e05276 |
| institution | OA Journals |
| issn | 1471-2261 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Cardiovascular Disorders |
| spelling | doaj-art-db7a736a4910423fa2fb2a98a1e052762025-08-20T01:52:22ZengBMCBMC Cardiovascular Disorders1471-22612025-05-012511810.1186/s12872-025-04835-0Clinical factors associated with severe coronary stenosis in patients undergoing cardiac surgeryRui Wang0Wei Gao1Xinyu Che2Ruopei Shen3Chunfeng Dai4Yan Xia5Ao Chen6Danbo Lu7Jiaqi Ma8Hungju Chen9Chenguang Li10Zhangwei Chen11Juying Qian12Junbo Ge13School of Health Science and Engineering, University of Shanghai for Science and TechnologyDepartment of Cardiology, Zhongshan Hospital, Fudan University, Shanghai Institute of Cardiovascular DiseasesDepartment of Cardiology, Zhongshan Hospital, Fudan University, Shanghai Institute of Cardiovascular DiseasesSchool of Health Science and Engineering, University of Shanghai for Science and TechnologyDepartment of Cardiology, Zhongshan Hospital, Fudan University, Shanghai Institute of Cardiovascular DiseasesDepartment of Cardiology, Zhongshan Hospital, Fudan University, Shanghai Institute of Cardiovascular DiseasesDepartment of Cardiology, Zhongshan Hospital, Fudan University, Shanghai Institute of Cardiovascular DiseasesDepartment of Cardiology, Zhongshan Hospital, Fudan University, Shanghai Institute of Cardiovascular DiseasesDepartment of Cardiology, Zhongshan Hospital, Fudan University, Shanghai Institute of Cardiovascular DiseasesDepartment of Cardiology, Zhongshan Hospital, Fudan University, Shanghai Institute of Cardiovascular DiseasesDepartment of Cardiology, Zhongshan Hospital, Fudan University, Shanghai Institute of Cardiovascular DiseasesSchool of Health Science and Engineering, University of Shanghai for Science and TechnologySchool of Health Science and Engineering, University of Shanghai for Science and TechnologyDepartment of Cardiology, Zhongshan Hospital, Fudan University, Shanghai Institute of Cardiovascular DiseasesAbstract Background Many cardiovascular patients undergoing valve surgeries require coronary angiography (CAG). Positive results may lead to bypass surgery, while negative results require no treatment. Although informative, CAG is costly and exposes patients to significant radiation. This study aimed to develop a model to reduce unnecessary procedures. Methods A retrospective cohort study was conducted on 5,086 patients who underwent valve repair/replacement or other cardiac surgeries at Zhongshan Hospital between 2016 and 2021 and received CAG. Patients treated between 2016 and 2020 formed the training set, while those treated in 2021 constituted the validation set. Severe coronary stenosis was defined as a ≥ 50% reduction in luminal diameter. Logistic regression analysis identified independent predictors in the training set, and a scoring system (Coronary Angiography Positivity Prediction Score) was constructed based on the β-coefficients of each variable. The model was evaluated for discrimination and calibration. Results Among 4,049 patients, 536 (13.2%) had severe coronary stenosis. Independent predictors included age ≥ 60 years, male sex, hypertension, diabetes, hyperlipidemia, and left ventricular ejection fraction ≤ 58%. The scoring system ranged from 0 to 11 points and demonstrated good discrimination, with an area under the receiver operating characteristic curve of 0.715 (95% confidence interval: 0.694–0.740) in the training set. In the high-risk group (≥ 6 points), the probability of severe coronary stenosis was 23.1%, compared to 8% in the low-risk group (< 6 points). The scoring system also performed well in the validation set with the curve of 0.740 (95% CI, 0.695–0.784). Conclusion We developed and validated a scoring system based on six clinical variables to predict severe coronary stenosis in patients undergoing valve surgeries. This tool may help optimize individual treatment strategies and reduce unnecessary CAG procedures.https://doi.org/10.1186/s12872-025-04835-0Valve replacementCoronary angiographyCardiovascular risk factorsEchocardiography |
| spellingShingle | Rui Wang Wei Gao Xinyu Che Ruopei Shen Chunfeng Dai Yan Xia Ao Chen Danbo Lu Jiaqi Ma Hungju Chen Chenguang Li Zhangwei Chen Juying Qian Junbo Ge Clinical factors associated with severe coronary stenosis in patients undergoing cardiac surgery BMC Cardiovascular Disorders Valve replacement Coronary angiography Cardiovascular risk factors Echocardiography |
| title | Clinical factors associated with severe coronary stenosis in patients undergoing cardiac surgery |
| title_full | Clinical factors associated with severe coronary stenosis in patients undergoing cardiac surgery |
| title_fullStr | Clinical factors associated with severe coronary stenosis in patients undergoing cardiac surgery |
| title_full_unstemmed | Clinical factors associated with severe coronary stenosis in patients undergoing cardiac surgery |
| title_short | Clinical factors associated with severe coronary stenosis in patients undergoing cardiac surgery |
| title_sort | clinical factors associated with severe coronary stenosis in patients undergoing cardiac surgery |
| topic | Valve replacement Coronary angiography Cardiovascular risk factors Echocardiography |
| url | https://doi.org/10.1186/s12872-025-04835-0 |
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