ORIGINAL RESEARCH article
Front. Neurol.
Sec. Endovascular and Interventional Neurology
Volume 16 - 2025 | doi: 10.3389/fneur.2025.1602006
This article is part of the Research TopicEmerging Trends in Moyamoya Disease: Diagnostic and Therapeutic InnovationsView all 3 articles
Development and Validation of a Predictive Model for Perioperative Low-Density Lipoprotein as a Risk Factor for Postoperative Cerebral Infarction
Provisionally accepted
- 1The Affiliated Hospital of Qingdao University, Qingdao, China
- 2Qingdao Municipal Hospital, Qingdao, Shandong Province, China
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Moyamoya disease (MMD) is a rare progressive cerebrovascular disorder with a high risk of postoperative cerebral infarction. Low-density lipoprotein (LDL) is a key risk factor for atherosclerosis, but the association between perioperative dynamic changes in LDL levels and the risk of postoperative cerebral infarction in MMD patients has not been thoroughly studied.This retrospective, single-center study included 266 MMD patients who underwent surgical treatment at The Affiliated Hospital of Qingdao University between 2015 and 2022. Preoperative, 24-hour postoperative, and recovery-phase LDL levels (minimum, maximum, and mean) were recorded. Key variables were selected using LASSO regression, and a risk prediction model for cerebral infarction was constructed using multivariate logistic regression analysis.Among the 266 patients, preoperative LDL (P=0.049), postoperative LDL (P=0.027), and mean LDL during the recovery period (P=0.036) were significantly associated with the occurrence of postoperative cerebral infarction. The integrated model, combining LDL indicators and clinical variables, demonstrated excellent predictive ability (AUC=0.82) and good calibration. Decision curve analysis (DCA) further validated the model's application in clinical decision-making, indicating its effectiveness in identifying high-risk patients. Conclusion： Dynamic monitoring of LDL levels during the perioperative period is of great significance for predicting the risk of postoperative cerebral infarction in MMD patients. The constructed risk prediction model provides a scientific basis for early identification of high-risk patients and the development of individualized intervention strategies, with the potential to improve clinical management and patient outcomes.
Keywords: Moyamoya Disease, postoperative cerebral infarction, Low-density lipoprotein, Prediction model, dynamic monitoring
Received: 28 Mar 2025; Accepted: 05 May 2025.
Copyright: © 2025 Wu, Xu, Zhang, Mu, Yu, Xu, Wang and Cui. 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:
Chao Wang, The Affiliated Hospital of Qingdao University, Qingdao, China
Zhenwen Cui, The Affiliated Hospital of Qingdao University, Qingdao, China
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