Objective To establish a risk prediction model for intracranial small aneurysm rupture based on CTA parameters and conduct internal validation.Methods A retrospective analysis was conducted in 226 patients with intracranial aneurysms who underwent CTA examination in our hospital from January 2018 to December 2022.Relevant factors and CTA examination indicators that may affect the rupture of intracranial small aneurysms were collected.Patients were divided into two groups(rupture group and non-rupture group)based on the presence or absence of aneurysm rupture.The general data of the two groups were compared with the CTA scan data.Patients were divided into 2 groups based on the presence or absence of ruptured aneurysms,and general data and CTA scan data were compared between the 2 groups,with variables screened by LASSO regression,modelled by logistic regression,and visualised by nomograms.Results A total of 121(53.53％)of the 226 patients included in this study experienced rupture.There were statistically significant differences in hypertension,family history of cerebrovascular disease,aneurysm location,aneurysm vessel location,abnormal pulsation point,tumor neck,AR,SR,flow angle and ascus between the rupture group and the non-rupture group(P＜0.05).The results of multivariate logistic regression analysis based on LASSO regression showed that abnormal fluctuation points,AR,SR,flow angle,and subcapsules were independent influencing factors for the rupture of intracranial small aneurysms(P＜0.05).Establish a column chart model for predicting the rupture of intracranial small aneurysms based on the results of multiple factor analysis.The ROC analysis results showed that the model predicted an AUC of 0.886[95％Cl(0.844,0.928)]for ruptured intracranial small aneurysms.The results of the H-L goodness-of-fit test showed that the difference between the probability of rupture of small intracranial aneurysms predicted by the model and the actual probability was not statistically significant(P＞0.05);the predicted curve was basically fitted to the standard curve.The results of the decision curve analysis showed that the net benefit to patients was greater than 0 when the threshold of the probability of rupture of small intracranial aneurysms predicted by this column line graph model was 0.15-1.00.Conclusion Rupture of small intracranial aneurysms is mainly influenced by abnormal fluctuation points,AR,and SR,and in this study the Nomogram model was used to predict the risk of rupture of small intracranial aneurysms,which can be used to guide the development of clinical decisions.
关键词
颅内小动脉瘤/CTA/多因素分析/列线图模型
Key words
Intracranial Small Aneurysm/CTA/Multi Factor Analysis/Nomogram t Model
维普
万方数据