血糖间隙对急性心肌梗死患者院内主要不良心血管事件的预测价值

Predictive value of glycemic gap in predicting nosocomial major adverse cardiovascular events in patients with acute myocardial infarction

  • 摘要:
    目的 探讨血糖间隙对急性心肌梗死(AMI)患者院内主要不良心血管事件(MACE)的预测价值。
    方法 收集2020年10月—2021年5月医院294例AMI患者的临床资料及实验室指标,入院后即刻检测静脉血糖及糖化血红蛋白水平。根据住院期间MACE发生情况将患者分为MACE组和非MACE组。采用单因素及多因素Logistic回归分析影响AMI患者发生MACE的危险因素; 探讨血糖间隙与不良事件的相关性; 采用受试者工作特征(ROC)曲线的曲线下面积(AUC)分析血糖间隙、入院血糖对AMI患者院内发生MACE的预测价值,并评价血糖间隙增强急性冠状动脉事件全球注册评分(GRACE评分)预测AMI患者院内MACE的效能。
    结果 与非MACE组相比, MACE组血糖间隙及入院血糖增高,差异有统计学意义(P<0.05)。多因素回归分析显示,血糖间隙、入院血糖是AMI患者发生MACE的独立危险因素。ROC曲线表明,血糖间隙及入院血糖对患者院内MACE的发生均有一定的预测价值,其中血糖间隙的AUC为0.750, 最佳临界值为1.511 mmol/L, 敏感度为66.7%, 特异度为74.1%。血糖间隙、GRACE评分单独及联合预测AMI患者院内发生MACE的AUC分别为0.750、0.833、0.859(P<0.05)。
    结论 血糖间隙与AMI患者的预后相关,能够提高GRACE评分对AMI患者发生MACE的预测价值。

     

    Abstract:
    Objective To investigate the value of glycemic gap in predicting nosocomial major adverse cardiovascular events (MACE) in patients with acute myocardial infarction (AMI).
    Methods Clinical materials and laboratory indexes of 294 patients with AMI in hospital from October 2020 to May 2021 were collected, they were conducted with detection of venous blood glucose and glycosylated hemoglobin immediately after hospital admission. According to the occurrence of MACE during hospitalization, the patients were divided into MACE group and non-MACE group. Univariate and multivariate Logistic regression were used to analyze the risk factors of MACE in patients with AMI; correlation between glycemic gap and adverse events was discussed; the area under the curve (AUC) of the receiver operating characteristic (ROC) curve was used to analyze the value of glycemic gap and blood glucose at hospital admission in predicting nosocomial MACE in patients with AMI, and the efficacy of glycemic gap in enhancing Global Registry for Acute Coronary Events score (GRACE score) for prediction of nosocomial MACE in patients with AMI was evaluated.
    Results Compared with the non-MACE group, the glycemic gap and blood glucose at hospital admission in the MACE group were significantly higher (P<0.05). Multivariate regression analysis showed that the glycemic gap and blood glucose at hospital admission were the independent risk factors for MACE in patients with AMI. The ROC curve showed that both the glycemic gap and the blood glucose at hospital admission have a certain predictive value for occurrence of nosocomial MACE, AUC of glycemic gap was 0.750, the optimum critical value was 1.511 mmol/L, the sensitivity was 66.7%, and the specificity was 74.1%. The AUC values of glycemic gap alone, the GRACE score alone and combination of two indexes in predicting occurrence of nosocomial MACE in patients with AMI were 0.750, 0.833 and 0.859, respectively (P<0.05).
    Conclusion Glycemic gap is related to the prognosis of patients with AMI, which can increase the value of the GRACE score in predicting occurrence of MACE in patients with AMI.

     

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