Preoperative coagulation parameters predict postoperative bleeding after endovascular treatment of intracranial aneurysms: A retrospective cohort study

Abstract

ObjectiveTo develop a simple preoperative prediction model for postoperative bleeding in patients undergoing endovascular treatment for cerebral aneurysms.MethodsIn this retrospective cohort study, we analyzed 209 patients who underwent endovascular embolization at a single center. Patients were categorized into bleeding and nonbleeding groups. Clinical characteristics and laboratory parameters were compared. Logistic regression identified independent predictors, and model performance was assessed using receiver operating characteristic analysis and bleeding risk stratification.ResultsPatients in the bleeding group had significantly higher prothrombin time, international normalized ratio, and lower fibrinogen levels (all P < 0.001). Multivariate analysis identified prothrombin time (odds ratio: 1.46), international normalized ratio: > 1.1 (odds ratio: 5.40), and fibrinogen levels (odds ratio: 0.081) as independent predictors. The model showed good discrimination (area under the receiver operating characteristic curve = 0.873). Bleeding incidence was significantly higher in the high-risk group (61.3%) than in the low-risk group (9.5%) (P < 0.001).ConclusionsA simple model based on prothrombin time, international normalized ratio, and fibrinogen levels can effectively predict bleeding risk after aneurysm embolization, aiding in individualized perioperative management. The relatively high bleeding rate observed may reflect the inclusion of minor, asymptomatic hemorrhages based on predefined imaging criteria and highlights the importance of sensitive perioperative coagulation monitoring, particularly in heterogeneous clinical contexts such as subarachnoid hemorrhage.

Keywords: Cerebral aneurysm; coagulation indicators; endovascular embolization; postoperative bleeding; risk prediction.

Figure 1.

Flow diagram of patient selection and grouping.

Figure 2.

Forest plot of independent predictors for postoperative bleeding. INR: international normalized ratio; PT: prothrombin time.

Figure 3.

(a) Receiver operating characteristic (ROC) curve of the logistic regression model predicting postoperative bleeding. The model demonstrated good discrimination (area under the curve = 0.873) and (b) distribution of postoperative bleeding according to predicted risk stratification. Patients in the high-risk group had a significantly higher incidence of bleeding than the low-risk group (P < 0.001).