Hua Yiming, Chen Ze, Cheng Lele, Ding Ning, Xie Yifei, Wu Hao, Jing Huaizhi, Xu Yu, Wu Yue, Lan Beidi
Department of Cardiovascular Medicine, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China.
Key Laboratory of Molecular Cardiology, Key Laboratory of Environment, Genes Related to Diseases, Ministry of Education Xi'an Jiaotong University, Xi'an, Shaanxi, China.
Front Endocrinol (Lausanne). 2025 Jun 12;16:1615051. doi: 10.3389/fendo.2025.1615051. eCollection 2025.
Glycemic variability (GV) is an increasingly important predictive indicator of vascular occlusion-related complications. Studies have demonstrated that a higher GV is associated with poor outcomes in patients with cerebral infarction (CI). The prognostic utility of GV in CI patients for predicting acute kidney injury (AKI) remains inadequately characterized. This investigation systematically examines the pathophysiological relationship between acute glycemic fluctuations and AKI development in CI populations, with particular emphasis on temporal patterns of glucose dysregulation.
This retrospective cohort analysis utilized data from the MIMIC-IV database, categorizing CI patients into quartiles based on GV metrics. Primary outcomes included AKI incidence and renal replacement therapy (RRT) initiation, with in-hospital mortality designated as the secondary endpoint. Analytical methodologies employed Kaplan-Meier survival curves with log-rank testing, multivariable-adjusted Cox proportional hazards regression, and logistic regression modeling to evaluate GV-AKI associations while controlling for critical confounders.
The analytical cohort comprised 3,343 critically ill individuals extracted from the MIMIC-IV database. Kaplan-Meier curve analysis demonstrated progressively elevated cumulative risks of AKI development, RRT requirement, and in-hospital mortality among individuals with heightened GV. Following multivariable adjustment, logistic regression models and Cox proportional hazards analyses confirmed GV as an independent predictor of AKI progression, RRT dependency, and mortality risk in cerebral infarction patients.
This investigation identifies GV as an independent prognostic determinant for AKI development in cerebral infarction patients. GV demonstrates clinical utility as a biomarker for stratifying AKI risk in this population.
血糖变异性（GV）是血管闭塞相关并发症日益重要的预测指标。研究表明，较高的GV与脑梗死（CI）患者的不良预后相关。GV在CI患者中预测急性肾损伤（AKI）的预后价值仍未得到充分描述。本研究系统地探讨了CI人群中急性血糖波动与AKI发生之间的病理生理关系，特别关注血糖失调的时间模式。
本回顾性队列分析利用了MIMIC-IV数据库中的数据，根据GV指标将CI患者分为四分位数。主要结局包括AKI发生率和开始肾脏替代治疗（RRT），住院死亡率作为次要终点。分析方法采用Kaplan-Meier生存曲线和对数秩检验、多变量调整的Cox比例风险回归以及逻辑回归模型，以评估GV与AKI的关联，同时控制关键混杂因素。
分析队列包括从MIMIC-IV数据库中提取的3343名危重症患者。Kaplan-Meier曲线分析表明，GV升高的个体发生AKI、需要RRT和住院死亡的累积风险逐渐升高。经过多变量调整后，逻辑回归模型和Cox比例风险分析证实，GV是脑梗死患者AKI进展、RRT依赖和死亡风险的独立预测因素。
本研究确定GV是脑梗死患者发生AKI的独立预后决定因素。GV作为该人群AKI风险分层的生物标志物具有临床应用价值。
