Yang Hui, Wang Hongcai, Jiang Yan
Department of Neurology, The Fourth Affiliated Hospital of Harbin Medical University, Harbin, 150001, China.
Diabetol Metab Syndr. 2025 Mar 25;17(1):100. doi: 10.1186/s13098-025-01676-x.
Glycemic variability (GV) is a key determinant of outcomes in critically ill patients, yet its impact on cerebral infarction patients in intensive care units (ICUs) remains underexplored. This study evaluates the association between GV and clinical outcomes, including discharge outcomes, 90-day and 1-year mortality, and ICU/hospital length of stay (LOS).
This retrospective study of 778 cerebral infarction patients from the MIMIC-IV database assessed GV, calculated as the glucose standard deviation-to-mean ratio during ICU stays. Regression models evaluated GV's impact on discharge outcomes, mortality, and ICU/hospital LOS, with adjustments for confounders. Restricted cubic spline analyses identified risk thresholds, while sensitivity and subgroup analyses validated findings. Predictive performance was assessed using AUC, NRI, and IDI, and multiple imputation methods addressed missing data.
Higher GV was significantly linked to adverse outcomes. Patients in the highest GV quartile had increased risks of poor discharge outcomes (adjusted OR: 1.83; 95% CI: 1.03-3.32; P = 0.042), 90-day mortality (adjusted HR: 1.51; 95% CI: 1.03-2.22; P = 0.036), and 1-year mortality (adjusted HR: 1.53; 95% CI: 1.07-2.18; P = 0.018). RCS analysis identified critical GV thresholds (≥ 11% for 90-day and ≥ 10% for 1-year mortality). Subgroup analysis revealed stronger associations between GV and poor outcomes in non-diabetic patients (adjusted OR: 1.89; 95% CI: 1.24-2.88; P = 0.003) compared to diabetic patients (adjusted OR: 0.81; 95% CI: 0.53-1.25; P = 0.337). Sensitivity analyses confirmed the robustness of findings across imputation methods.
GV independently predicts poor outcomes in ICU cerebral infarction patients. Integrating GV metrics into clinical workflows may improve risk stratification and guide interventions. Future research should validate these findings and explore strategies to reduce GV.
血糖变异性（GV）是危重症患者预后的关键决定因素，但其对重症监护病房（ICU）中脑梗死患者的影响仍未得到充分研究。本研究评估了GV与临床结局之间的关联，包括出院结局、90天和1年死亡率以及ICU/医院住院时间（LOS）。
这项对MIMIC-IV数据库中778例脑梗死患者的回顾性研究评估了GV，GV计算为ICU住院期间血糖标准差与均值之比。回归模型评估了GV对出院结局、死亡率以及ICU/医院LOS的影响，并对混杂因素进行了调整。限制性立方样条分析确定了风险阈值，敏感性和亚组分析验证了研究结果。使用AUC、NRI和IDI评估预测性能，并采用多重填补方法处理缺失数据。
较高的GV与不良结局显著相关。GV处于最高四分位数的患者出现不良出院结局的风险增加（调整后的OR：1.83；95%CI：1.03-3.32；P = 0.042），90天死亡率增加（调整后的HR：1.51；95%CI：1.03-2.22；P = 0.036），1年死亡率增加（调整后的HR：1.53；95%CI：1.07-2.18；P = 0.018）。RCS分析确定了关键的GV阈值（90天死亡率≥11%，1年死亡率≥10%）。亚组分析显示，与糖尿病患者相比，非糖尿病患者中GV与不良结局之间的关联更强（调整后的OR：1.89；95%CI：1.24-2.88；P = 0.003），而糖尿病患者中该关联较弱（调整后的OR：0.81；95%CI：0.53-1.25；P = 0.337）。敏感性分析证实了不同填补方法下研究结果的稳健性。
GV可独立预测ICU脑梗死患者的不良结局。将GV指标纳入临床工作流程可能会改善风险分层并指导干预措施。未来的研究应验证这些发现并探索降低GV的策略。
