MA Ruicong, GAO Jianbo, MAO Shiyuan, ZHAO Zhihao, ZONG Jing, ZHANG Fengyun, WANG Zhirong. Predictive value of glycemic gap in predicting nosocomial major adverse cardiovascular events in patients with acute myocardial infarction[J]. Journal of Clinical Medicine in Practice, 2022, 26(3): 29-33, 43. DOI: 10.7619/jcmp.20213795
Citation: MA Ruicong, GAO Jianbo, MAO Shiyuan, ZHAO Zhihao, ZONG Jing, ZHANG Fengyun, WANG Zhirong. Predictive value of glycemic gap in predicting nosocomial major adverse cardiovascular events in patients with acute myocardial infarction[J]. Journal of Clinical Medicine in Practice, 2022, 26(3): 29-33, 43. DOI: 10.7619/jcmp.20213795

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

  • 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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