Developing predictive nomogram models using quantitative electroencephalography for brain function in type a aortic dissection: a prospective observational study

作者：Y. Wang, Yi Jiang, Lin Mi, Wenxue Liu, Yunxing Xue, Yang Chen, Xuan Luo, Yongqing Cheng, Jun Pan, Jason Zhensheng Qu, Dongjin Wang · 发表于：International Journal of Surgery · 年份：2025 · DOI：10.1097/js9.0000000000002235 · 被引用次数：7 · 研究领域：Aortic Disease and Treatment Approaches、Intensive Care Unit Cognitive Disorders、Cardiac and Coronary Surgery Techniques

BACKGROUND: Type A aortic dissection (TAAD) remains a significant challenge in cardiac surgery, presenting high risks of adverse outcomes such as permanent neurological dysfunction and mortality despite advances in medical technology and surgical techniques. This study investigates the use of quantitative electroencephalography (QEEG) to monitor and predict neurological outcomes during the perioperative period in TAAD patients. METHODS: This prospective observational study was conducted at the hospital, involving patients undergoing TAAD surgery from February 2022 to January 2023. QEEG parameters, including the dynamic amplitude-integrated electroencephalography (aEEG) grade, which assesses changes in brain function over time, alongside aEEG and relative band power (RBP), were monitored and analyzed to assess brain function preoperatively, intraoperatively, and within 2 hours postoperatively. A predictive nomogram model was developed using these QEEG metrics along with other clinical variables to forecast neurological outcomes. RESULTS: In this study, we analyzed the factors contributing to adverse outcomes (AO) and transient neurological dysfunction (TND) following TAAD surgery. For AO, multivariable analysis identified pre-mental status (odds ratio [OR] = 4.652, 95% confidence interval [CI] = 2.316-10.074, P < 0.001), cardiopulmonary bypass time (OR = 1.014, 95% CI = 1.006-1.023, P = 0.001), and dynamic aEEG grade (OR = 9.926, 95% CI = 4.493-25.268, P < 0.001) as independen...