Predicting multi-vascular diseases in patients with coronary artery disease [version 2; peer review: 2 approved]
Background: Because of its systemic nature, the occurrence of atherosclerosis in the coronary arteries can also indicate a risk for other vascular diseases. However, screening program targeted for all patients with coronary artery disease (CAD) is highly ineffective and no studies have assessed the...
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| Format: | Article |
| Language: | English |
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F1000 Research Ltd
2023-09-01
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| Online Access: | https://f1000research.com/articles/12-750/v2 |
| _version_ | 1827808779344805888 |
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| author | Anwar Santoso Doni Firman Taofan Taofan Amir Aziz Alkatiri Luthfian Aby Nurachman Raditya Dewangga Suci Indriani Suko Adiarto |
| author_facet | Anwar Santoso Doni Firman Taofan Taofan Amir Aziz Alkatiri Luthfian Aby Nurachman Raditya Dewangga Suci Indriani Suko Adiarto |
| author_sort | Anwar Santoso |
| collection | DOAJ |
| description | Background: Because of its systemic nature, the occurrence of atherosclerosis in the coronary arteries can also indicate a risk for other vascular diseases. However, screening program targeted for all patients with coronary artery disease (CAD) is highly ineffective and no studies have assessed the risk factors for developing multi-vascular diseases in general. This study constructed a predictive model and scoring system to enable targeted screening for multi-vascular diseases in CAD patients. Methods: This cross-sectional study includes patients with CAD, as diagnosed during coronary angiography or percutaneous coronary intervention from March 2021 to December 2021. Coronary artery stenosis (CAS) and abdominal aortic aneurysm (AAA) were diagnosed using Doppler ultrasound while peripheral artery disease (PAD) was diagnosed based on ABI score. Multivariate logistic regression was conducted to construct the predictive model and risk scores. Validation was conducted using ROC analysis and Hosmer-Lemeshow test. Results: Multivariate analysis showed that ages of >60 years (OR [95% CI] = 1.579 [1.153-2.164]), diabetes mellitus (OR = 1.412 [1.036-1.924]), cerebrovascular disease (OR = 3.656 [2.326-5.747]), and CAD3VD (OR = 1.960 [1.250-3.073]) increased the odds for multi-vascular disease. The model demonstrated good predictive capability (AUC = 0.659) and was well-calibrated (Hosmer-Lemeshow p = 0.379). Targeted screening for high-risk patients reduced the number needed to screen (NNS) from 6 in the general population to 3 and has a high specificity of 96.5% Conclusions: Targeted screening using clinical risk scores was able to decrease NNS with good predictive capability and high specificity |
| first_indexed | 2024-03-11T22:33:47Z |
| format | Article |
| id | doaj.art-594b8ae8256e4e3d9af2c19941779ba8 |
| institution | Directory Open Access Journal |
| issn | 2046-1402 |
| language | English |
| last_indexed | 2024-03-11T22:33:47Z |
| publishDate | 2023-09-01 |
| publisher | F1000 Research Ltd |
| record_format | Article |
| series | F1000Research |
| spelling | doaj.art-594b8ae8256e4e3d9af2c19941779ba82023-09-23T00:00:02ZengF1000 Research LtdF1000Research2046-14022023-09-0112155734Predicting multi-vascular diseases in patients with coronary artery disease [version 2; peer review: 2 approved]Anwar Santoso0https://orcid.org/0000-0001-8247-4151Doni Firman1https://orcid.org/0000-0002-8649-8158Taofan Taofan2Amir Aziz Alkatiri3Luthfian Aby Nurachman4Raditya Dewangga5Suci Indriani6Suko Adiarto7https://orcid.org/0000-0002-2848-0566Department of Cardiology and Vascular Medicine, Faculty of Medicine, Universitas Indonesia, National Cardiovascular Center Harapan Kita, Jakarta, IndonesiaDepartment of Cardiology and Vascular Medicine, Faculty of Medicine, Universitas Indonesia, National Cardiovascular Center Harapan Kita, Jakarta, IndonesiaDepartment of Cardiology and Vascular Medicine, Faculty of Medicine, Universitas Indonesia, National Cardiovascular Center Harapan Kita, Jakarta, IndonesiaDepartment of Cardiology and Vascular Medicine, Faculty of Medicine, Universitas Indonesia, National Cardiovascular Center Harapan Kita, Jakarta, IndonesiaFaculty of Medicine, Universitas Indonesia, Depok, West Java, IndonesiaGunung Jati General Hospital, Cirebon, West Java, IndonesiaDepartment of Cardiology and Vascular Medicine, Faculty of Medicine, Universitas Indonesia, National Cardiovascular Center Harapan Kita, Jakarta, IndonesiaDepartment of Cardiology and Vascular Medicine, Faculty of Medicine, Universitas Indonesia, National Cardiovascular Center Harapan Kita, Jakarta, IndonesiaBackground: Because of its systemic nature, the occurrence of atherosclerosis in the coronary arteries can also indicate a risk for other vascular diseases. However, screening program targeted for all patients with coronary artery disease (CAD) is highly ineffective and no studies have assessed the risk factors for developing multi-vascular diseases in general. This study constructed a predictive model and scoring system to enable targeted screening for multi-vascular diseases in CAD patients. Methods: This cross-sectional study includes patients with CAD, as diagnosed during coronary angiography or percutaneous coronary intervention from March 2021 to December 2021. Coronary artery stenosis (CAS) and abdominal aortic aneurysm (AAA) were diagnosed using Doppler ultrasound while peripheral artery disease (PAD) was diagnosed based on ABI score. Multivariate logistic regression was conducted to construct the predictive model and risk scores. Validation was conducted using ROC analysis and Hosmer-Lemeshow test. Results: Multivariate analysis showed that ages of >60 years (OR [95% CI] = 1.579 [1.153-2.164]), diabetes mellitus (OR = 1.412 [1.036-1.924]), cerebrovascular disease (OR = 3.656 [2.326-5.747]), and CAD3VD (OR = 1.960 [1.250-3.073]) increased the odds for multi-vascular disease. The model demonstrated good predictive capability (AUC = 0.659) and was well-calibrated (Hosmer-Lemeshow p = 0.379). Targeted screening for high-risk patients reduced the number needed to screen (NNS) from 6 in the general population to 3 and has a high specificity of 96.5% Conclusions: Targeted screening using clinical risk scores was able to decrease NNS with good predictive capability and high specificityhttps://f1000research.com/articles/12-750/v2Coronary artery disease Peripheral artery disease Abdominal Aortic Aneurysm Carotid Artery Stenosis targeted screening predictive modeleng |
| spellingShingle | Anwar Santoso Doni Firman Taofan Taofan Amir Aziz Alkatiri Luthfian Aby Nurachman Raditya Dewangga Suci Indriani Suko Adiarto Predicting multi-vascular diseases in patients with coronary artery disease [version 2; peer review: 2 approved] F1000Research Coronary artery disease Peripheral artery disease Abdominal Aortic Aneurysm Carotid Artery Stenosis targeted screening predictive model eng |
| title | Predicting multi-vascular diseases in patients with coronary artery disease [version 2; peer review: 2 approved] |
| title_full | Predicting multi-vascular diseases in patients with coronary artery disease [version 2; peer review: 2 approved] |
| title_fullStr | Predicting multi-vascular diseases in patients with coronary artery disease [version 2; peer review: 2 approved] |
| title_full_unstemmed | Predicting multi-vascular diseases in patients with coronary artery disease [version 2; peer review: 2 approved] |
| title_short | Predicting multi-vascular diseases in patients with coronary artery disease [version 2; peer review: 2 approved] |
| title_sort | predicting multi vascular diseases in patients with coronary artery disease version 2 peer review 2 approved |
| topic | Coronary artery disease Peripheral artery disease Abdominal Aortic Aneurysm Carotid Artery Stenosis targeted screening predictive model eng |
| url | https://f1000research.com/articles/12-750/v2 |
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