ORIGINAL RESEARCH article
Front. Neurol.
Sec. Endovascular and Interventional Neurology
Volume 16 - 2025 | doi: 10.3389/fneur.2025.1538753
Platelet aggregation rate serves as a significant predictive indicator for Thromboembolic events in the context of stent-assisted embolization for unruptured arterial aneurysms
Provisionally accepted- Department of Neurosurgery, Zhongnan Hospital, Wuhan University, Wuhan, Hubei Province, China
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running title: Platelet Aggregation Rate as a Predictor of Thromboembolic Events in Stent-Assisted Embolization for Unruptured AneurysmsPerioperative cerebrovascular thromboembolic events are serious complications of stentassisted embolization (SAE) for unruptured intracranial aneurysms (UIAs). To date, there have been no definitive clinical trial results to effectively predict and prevent the occurrence of this complication. This study aims to elucidate the correlation between platelet aggregation rate (PAR) and thromboembolic events (TEs), with the goal of predicting the occurrence of cerebraovascular TEs in these patients.In this retrospective, single-center cohort study, we included 704 cases of unruptured intracranial aneurysms treated with stent-assisted intervention from 2016 to 2020. Cerebraovascular TEs were defined as cerebral ischemic events occurring within 7 days before or after the interventional procedure. Light Transmission Aggregometry (LTA) was used to detect PAR in patients. Clinical data, including patients' demographic information and perioperative PAR, were collected. Multivariate analysis was conducted to examine the correlation between these factors and the occurrence of TEs. Additionally, Lasso regression was employed to select clinical indicators associated with perioperative TEs. Receiver Operating Characteristic (ROC) curves were generated for prognostic indicators such as PAR, with the optimal cutoff value determined. A nomogram was then simulated, and predictive accuracy of the model was evaluated using Decision Curve Analysis (DCA).A total of 562 patients were included in the final analysis. Significant differences were observed in the incidence of thrombosis between the control group and the experimental group (9.38% vs. 4.96%). The ROC curve of platelet aggregation index, highly correlated with prognosis and derived from Lasso regression, identified the optimal cutoff value for the maximum preoperative PAR as 19.81. A nomogram was constructed based on selected clinical baseline data, and its calibration was assessed using data from the prediction group. The net benefit of the experimental group model's DCA curve was significantly improved.For patients undergoing SAE for UIAs, utilizing PAR and other indicators as reference standards for treatment results in better prognosis compared to empirical treatment based on guidelines. Guiding antiplatelet therapy using PAR and other indicators is both meaningful and beneficial to clinical practice.
Keywords: Platelet Aggregation Rate, Stent-Assisted Embolization, Unruptured Intracranial Aneurysms, Thromboembolic Events SAE, stent-assisted embolization, UIAs, unruptured intracranial aneurysms, PAR, platelet aggregation rates, TEs, thromboembolic events, DAPT, dual antiplatelet therapy, LTA, light transmission aggregometry, DSA, digital subtraction angiography, PRP, plateletrich plasma
Received: 03 Dec 2024; Accepted: 15 Apr 2025.
Copyright: © 2025 Huang, Bao, Feng, Li, Liu and Zhao. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Xiang Li, Department of Neurosurgery, Zhongnan Hospital, Wuhan University, Wuhan, 430071, Hubei Province, China
Kui Liu, Department of Neurosurgery, Zhongnan Hospital, Wuhan University, Wuhan, 430071, Hubei Province, China
Wenyuan Zhao, Department of Neurosurgery, Zhongnan Hospital, Wuhan University, Wuhan, 430071, Hubei Province, China
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