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| Prediction of rupture risk for middle cerebral artery aneurysm in patients with hypertension based on nomogram |
| SU Na, ZHOU Jiafeng, LIN Boli, ZHU Dongqin, YANG Yunjun, CHEN Yongchun |
| Department of Radiology, the First Affiliated Hospital of Wenzhou Medical University, Wenzhou 325015, China |
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| Cite this article: |
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SU Na,ZHOU Jiafeng,LIN Boli, et al. Prediction of rupture risk for middle cerebral artery aneurysm in patients with hypertension based on nomogram[J]. JOURNAL OF WEZHOU MEDICAL UNIVERSITY, 2022, 52(8): 638-644.
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Abstract Objective: To investigate the risk factors of middle cerebral artery (MCA) aneurysm rupture in patients with hypertension, and to construct a nomogram prediction model. Methods: The clinical and imaging data of hospitalized patients with MCA aneurysms complicated with hypertension from January 2009 to June 2020 were collected retrospectively. All patients underwent CT angiography (CTA) and the morphological parameters of aneurysms were measured. Multivariate logistic regression was used to analyze the independent risk factors of MCA aneurysm rupture in patients with hypertension and a nomogram prediction model was constructed. The area under receiver operating characteristic curve (AUC) was used to evaluate the diagnostic efficiency of the model. Results: A total of 254 patients with MCA aneurysms complicated with hypertension were finally included in this study. Multivariate logistic regression showed that gender (OR=2.277, P=0.022), aspect ratio (OR=10.270,
P<0.001), irregular shape (OR=4.747, P<0.001) and location (OR=3.161, P=0.001) were independent risk factors for MCA aneurysm rupture in patients with hypertension. The nomogram prediction model has good diagnostic efficiency (AUC=0.866) and the prediction accuracy is 82.68%. Conclusion: Aspect ratio, irregular shape,location and gender are independent risk factors for MCA aneurysm rupture in patients with hypertension. It is feasible to predict the rupture risk of MCA aneurysm in patients with hypertension based on nomogram, which provides a visual basis for clinical personalized diagnosis and treatment.
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Received: 01 March 2022
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. [J]. JOURNAL OF WEZHOU MEDICAL UNIVERSITY, 2022, 52(9): 762-763. |
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