Development and validation of a risk prediction model for abdominal aortic aneurysm: a nationwide population-based cohort study
Abstract Abdominal aortic aneurysm (AAA) is characterized by irreversible localized dilatation of the abdominal aorta. It poses a significant health risk. As AAA size tends to increase over time, there is a heightened risk of rupture, resulting in a substantially high mortality rate. Although AAA sc...
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Nature Portfolio
2025-07-01
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| Online Access: | https://doi.org/10.1038/s41598-025-11956-1 |
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| author | Hyung-jin Cho Mi-hyeong Kim Kyung-Jai Ko Kang-woong Jun Kyung-do Han Jeong-Kye Hwang |
| author_facet | Hyung-jin Cho Mi-hyeong Kim Kyung-Jai Ko Kang-woong Jun Kyung-do Han Jeong-Kye Hwang |
| author_sort | Hyung-jin Cho |
| collection | DOAJ |
| description | Abstract Abdominal aortic aneurysm (AAA) is characterized by irreversible localized dilatation of the abdominal aorta. It poses a significant health risk. As AAA size tends to increase over time, there is a heightened risk of rupture, resulting in a substantially high mortality rate. Although AAA screening programs targeting specific demographics are available, there is room for improvement in terms of inclusivity and cost-effectiveness. This study aimed to develop a predictive model for AAA occurrence utilizing seven years of data from the Korean National Health Insurance Service database (NHIS). This study utilized NHIS data from 2009 to 2020. A total of 4,234,415 individuals who underwent health examinations in 2009 were identified. After applying exclusion criteria, a total of 3,937,535 individuals were selected. Of them, 70% were used for model development and 30% were used for validation. The mean follow-up duration was 10.11 ± 1.29 years, during which 2,836 cases of AAA were identified among 1,181,131 (2.4%) participants in the validation cohort. The model incorporated a set of 10 variables, encompassing age, sex, obesity, smoking, drinking, diabetes (DM), hypertension (HTN), dyslipidemia, chronic kidney disease (CKD), and cardiocerebrovascular disease (CVD). Evaluation of the model’s predictive performance revealed an area under the curve (AUC) of 0.807 (95% CI: 0.80–0.81) when it was applied to the development cohort. The AUC remained high at 0.803 (95% CI: 0.79–0.81) when the model was applied to the validation cohort, indicating its effectiveness in forecasting AAA occurrence. A multivariable risk model for predicting the onset of AAA was successfully developed, showcasing an excellent performance with an AUC value of 0.807, surpassing traditional screening methods. This model has the potential to selectively identify high-risk patients from a slightly broader pool than current screening approaches. Priority should be given to proactive screening efforts targeting individuals at elevated risk for AAA, with the goal of reducing AAA-related mortality. |
| format | Article |
| id | doaj-art-9e313263c40a49c3bbf4ebfb68ecdea6 |
| institution | DOAJ |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Nature Portfolio |
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| series | Scientific Reports |
| spelling | doaj-art-9e313263c40a49c3bbf4ebfb68ecdea62025-08-20T03:05:23ZengNature PortfolioScientific Reports2045-23222025-07-0115111010.1038/s41598-025-11956-1Development and validation of a risk prediction model for abdominal aortic aneurysm: a nationwide population-based cohort studyHyung-jin Cho0Mi-hyeong Kim1Kyung-Jai Ko2Kang-woong Jun3Kyung-do Han4Jeong-Kye Hwang5Division of Vascular and Transplant Surgery, Department of Surgery, Eunpyeong St. Mary’s Hospital, College of Medicine, The Catholic University of KoreaDivision of Vascular and Transplant Surgery, Department of Surgery, Eunpyeong St. Mary’s Hospital, College of Medicine, The Catholic University of KoreaDepartment of Surgery, Kangdong Sacred Heart HospitalDivision of Vascular and Transplant Surgery, Department of Surgery, Bucheon St. Mary’s Hospital, College of Medicine, The Catholic University of KoreaDepartment of Statistics and Actuarial Science, Soongsil UniversityDivision of Vascular and Transplant Surgery, Department of Surgery, Eunpyeong St. Mary’s Hospital, College of Medicine, The Catholic University of KoreaAbstract Abdominal aortic aneurysm (AAA) is characterized by irreversible localized dilatation of the abdominal aorta. It poses a significant health risk. As AAA size tends to increase over time, there is a heightened risk of rupture, resulting in a substantially high mortality rate. Although AAA screening programs targeting specific demographics are available, there is room for improvement in terms of inclusivity and cost-effectiveness. This study aimed to develop a predictive model for AAA occurrence utilizing seven years of data from the Korean National Health Insurance Service database (NHIS). This study utilized NHIS data from 2009 to 2020. A total of 4,234,415 individuals who underwent health examinations in 2009 were identified. After applying exclusion criteria, a total of 3,937,535 individuals were selected. Of them, 70% were used for model development and 30% were used for validation. The mean follow-up duration was 10.11 ± 1.29 years, during which 2,836 cases of AAA were identified among 1,181,131 (2.4%) participants in the validation cohort. The model incorporated a set of 10 variables, encompassing age, sex, obesity, smoking, drinking, diabetes (DM), hypertension (HTN), dyslipidemia, chronic kidney disease (CKD), and cardiocerebrovascular disease (CVD). Evaluation of the model’s predictive performance revealed an area under the curve (AUC) of 0.807 (95% CI: 0.80–0.81) when it was applied to the development cohort. The AUC remained high at 0.803 (95% CI: 0.79–0.81) when the model was applied to the validation cohort, indicating its effectiveness in forecasting AAA occurrence. A multivariable risk model for predicting the onset of AAA was successfully developed, showcasing an excellent performance with an AUC value of 0.807, surpassing traditional screening methods. This model has the potential to selectively identify high-risk patients from a slightly broader pool than current screening approaches. Priority should be given to proactive screening efforts targeting individuals at elevated risk for AAA, with the goal of reducing AAA-related mortality.https://doi.org/10.1038/s41598-025-11956-1Aortic aneurysmAbdominalNomograms |
| spellingShingle | Hyung-jin Cho Mi-hyeong Kim Kyung-Jai Ko Kang-woong Jun Kyung-do Han Jeong-Kye Hwang Development and validation of a risk prediction model for abdominal aortic aneurysm: a nationwide population-based cohort study Scientific Reports Aortic aneurysm Abdominal Nomograms |
| title | Development and validation of a risk prediction model for abdominal aortic aneurysm: a nationwide population-based cohort study |
| title_full | Development and validation of a risk prediction model for abdominal aortic aneurysm: a nationwide population-based cohort study |
| title_fullStr | Development and validation of a risk prediction model for abdominal aortic aneurysm: a nationwide population-based cohort study |
| title_full_unstemmed | Development and validation of a risk prediction model for abdominal aortic aneurysm: a nationwide population-based cohort study |
| title_short | Development and validation of a risk prediction model for abdominal aortic aneurysm: a nationwide population-based cohort study |
| title_sort | development and validation of a risk prediction model for abdominal aortic aneurysm a nationwide population based cohort study |
| topic | Aortic aneurysm Abdominal Nomograms |
| url | https://doi.org/10.1038/s41598-025-11956-1 |
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