Abstract
OBJECTIVES: To identify risk factors for intraoperative rupture during microscopic clipping of intracranial aneurysms (IA) and to develop a predictive nomogram for improved preoperative risk assessment and surgical outcomes. METHODS: A retrospective analysis was conducted on 286 IA patients who underwent surgical clipping between January 2018 and January 2023. Patients were classified into rupture (n=56) and non-rupture (n=230) groups based on intraoperative outcomes. Clinical data, including demographics, aneurysm size, morphology, and preoperative functional status, were collected. Independent risk factors were identified using multivariate logistic regression, and a nomogram model was constructed. Model performance was evaluated by ROC curves, calibration plots, and decision curve analysis (DCA). Six-month postoperative outcomes and complication rates were compared between the groups. RESULTS: Univariate analysis showed that age ≥60 years, cerebral vasospasm, aneurysm diameter ≥10 mm, irregular morphology, anterior communicating artery location, preoperative Hunt-Hess grade >III, and the use of adjunctive techniques were associated with increased rupture risk. Multivariate regression identified cerebral vasospasm (OR=2.387, P=0.012), aneurysm size ≥10 mm (OR=2.298, P=0.018), anterior communicating artery aneurysm (OR=2.800, P=0.004), Hunt-Hess grade >III (OR=2.625, P=0.006), and adjunctive techniques (OR=2.492, P=0.012) as independent predictors. Interestingly, irregular morphology emerged as a protective factor (OR=0.348, P=0.003). The nomogram achieved an AUC of 0.856 in the training cohort and 0.763 in the validation cohort (P=0.438). Calibration curves demonstrated strong agreement between predicted and observed outcomes, while DCA indicated clinical benefit at threshold probabilities of 0-41%. At six months, patients in the rupture group had significantly worse modified Rankin Scale scores and higher complication rates (P<0.05). CONCLUSION: The proposed nomogram provides a reliable tool for predicting intraoperative rupture during IA clipping, enabling individualized preoperative risk assessment and optimization of surgical strategies, particularly in high-risk patients.