ArticleScientific reports2025
Development and validation of a risk prediction model for abdominal aortic aneurysm: a nationwide population-based cohort study.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Prediction model for aortic dissection, aortic aneurysm, and peripheral artery disease.Hypertension research : official journal of the Japanese Society of Hypertension · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.