Zeng Yile, Lin Long, Chen Jianlong, Cai Shengyu, Lai Jinqing, Hu Weipeng, Liu Yiqi
Department of Neurosurgery, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, Fujian, China.
Department of Neurosurgery, Fuzong Clinical Medical College, Fujian Medical University, Fuzhou, Fujian, China.
Front Neurol. 2025 Feb 25;16:1516627. doi: 10.3389/fneur.2025.1516627. eCollection 2025.
This study aimed to evaluate the predictive capability of glycolipid metabolism index (triglyceride-glucose index, TyG; atherogenic index of plasma, AIP; triglyceride to high-density lipoprotein cholesterol ratio, TG/HDL-C; and non-HDL-C to HDL-C ratio, NHHR) for complications and ventilator use in patients with intracerebral hemorrhage (ICH) admitted to the intensive care unit (ICU).
Patients with ICH requiring ICU admission were selected from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. Outcomes assessed included incidence of complications and use of ventilator support. Multivariate logistic regression, receiver operating characteristic (ROC) analysis, and restricted cubic spline were employed to investigate the relationship between glycolipid metabolism index and clinical outcomes in ICH patients.
A total of 733 patients were included. Multivariate logistic regression analysis revealed that elevated TyG, AIP, and TG/HDL-C levels were associated with increased incidence of complications and prolonged ventilator use. ROC curve analysis demonstrated that TyG (AUC 0.646) exhibited the strongest predictive ability for multiple complications in ICH patients. Further multiple regression analysis identified TG/HDL-C as an independent predictor of deep vein thrombosis, while TyG, AIP, and TG/HDL-C independently predicted pulmonary embolism, and TyG, AIP, NHHR, and TG/HDL-C independently predicted acute kidney injury. Moreover, ventilator use further heightened the risk of multiple complications in ICU patients with elevated glycolipid metabolism index.
Glycolipid metabolism index represent promising and readily accessible biomarkers for predicting multiple complications and ventilator use in ICU patients with ICH.
本研究旨在评估糖脂代谢指标(甘油三酯-葡萄糖指数,TyG;血浆致动脉粥样硬化指数,AIP;甘油三酯与高密度脂蛋白胆固醇比值,TG/HDL-C;以及非高密度脂蛋白胆固醇与高密度脂蛋白胆固醇比值,NHHR)对入住重症监护病房(ICU)的脑出血(ICH)患者并发症及使用呼吸机情况的预测能力。
从重症监护医学信息集市IV(MIMIC-IV)数据库中选取需要入住ICU的ICH患者。评估的结局包括并发症的发生率和呼吸机支持的使用情况。采用多因素逻辑回归、受试者工作特征(ROC)分析和限制性立方样条分析来研究糖脂代谢指标与ICH患者临床结局之间的关系。
共纳入733例患者。多因素逻辑回归分析显示,TyG、AIP和TG/HDL-C水平升高与并发症发生率增加及呼吸机使用时间延长相关。ROC曲线分析表明,TyG(AUC 0.646)对ICH患者多种并发症的预测能力最强。进一步的多因素回归分析确定TG/HDL-C是深静脉血栓形成(DVT)的独立预测因素,而TyG、AIP和TG/HDL-C独立预测肺栓塞,TyG、AIP、NHHR和TG/HDL-C独立预测急性肾损伤(AKI)。此外,使用呼吸机进一步增加了糖脂代谢指标升高的ICU患者发生多种并发症的风险。
糖脂代谢指标是预测入住ICU的ICH患者发生多种并发症及使用呼吸机情况的有前景且易于获取的生物标志物。