Key result
CT-hematology nomogram outperforms VSG score for AAA rupture prediction with an AUC of ~0.82.
Why the study?
Abdominal aortic aneurysm rupture causes sudden death, but no comprehensive model had integrated hematological parameters with CT imaging features to predict rupture risk.
Does a predictive model combining CT imaging and hematological parameters improve the prediction of AAA rupture in patients with AAA?
Case-Control (n=343)
Does a predictive model combining CT imaging and hematological parameters improve the prediction of AAA rupture in patients with AAA?
Answers are grounded in this paper and cite their sources.
A predictive model combining CT imaging and hematological parameters accurately predicts AAA rupture risk and outperforms the existing VSG score.
An abdominal aortic aneurysm (AAA) is a life-threatening condition whose rupture is a significant cause of sudden death. There is currently no comprehensive model that integrates hematological parameters with computed tomography (CT) imaging features. This study aimed to construct and verify a predictive model for AAA rupture using CT imaging and hematological parameters. A retrospective case-control study was conducted in China. It included 230 patients with AAA admitted from January 1, 2021 to April 30, 2025. Patients were grouped into ruptured and unruptured groups based on their AAA condition. A nomogram model was constructed with multivariate logistic regression by screening key variables through LASSO regression. External validation was performed on an additional cohort of 113 patients. The study cohort comprised 230 patients (mean age 63.00 ± 8.23 years, 59.57 % male), including 106 in the ruptured group and 124 in the unruptured group. The baseline characteristics between the training and external validation sets revealed no significant differences in key demographic and physiological variables between the two groups (all P > 0.05). The maximum AAA diameter exceeding 6.520 cm was significantly associated with increased rupture risk. Hematological parameters, specifically RDW >14.825 %, WBC >13.610 × 10^9/L, neutrophil count >12.065 × 10^9/L, and NLR >8.715, were identified as independent predictors of AAA rupture. The AUC of combined ROC for the training set was 0.823, and for the external validation set, it was 0.911. Additionally, a model calibration plot confirmed the accuracy of predicted probabilities compared to observed outcomes, supporting the robustness of our model. This model AUC increased by 0.04 (P = 0.03) compared to the VSG score (AUC = 0.78), and the net reclassification index increased by 23.5 % in small AAA (<5 cm). Combining CT imaging and hematological parameters can effectively predict the risk of AAA rupture.
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Yao et al. (2025) conducted a case-control in Abdominal aortic aneurysm (n=343). Combined CT imaging and hematological parameters model vs. VSG score was evaluated on AAA rupture prediction (AUC) (AUC increase of 0.04, p=0.03). A model combining CT imaging and hematological parameters effectively predicted AAA rupture risk, yielding an AUC of 0.823 and significantly outperforming the VSG score (AUC increase 0.04, P=0.03).
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