2型糖尿病伴冠心病患者血糖波动及血清Gal-3对主要不良心血管事件的预测价值

Predictive value of blood glucose fluctuation and serum Gal-3 level on major adverse cardiovascular events in patients with type 2 diabetes mellitus and coronary heart disease

摘要:

目的 探讨2型糖尿病伴冠心病患者血糖波动及血清半乳糖凝集素-3（Gal-3）对主要不良心血管事件的预测价值。方法 选取2019年3月—2021年3月吉安市中心人民医院收治的118例2型糖尿病伴冠心病患者和54例单纯2型糖尿病患者，另选取同期该院46例健康体检者。比较3组空腹血糖（FBG）、糖化血红蛋白（HbA1c）及血清Gal-3水平；比较不同病情严重程度2型糖尿病伴冠心病患者24 h血糖、血糖波动幅度及血清Gal-3水平；采用Pearson相关性分析病情严重程度与24 h血糖、血糖波动幅度及Gal-3的关系；随访1年，统计2型糖尿病伴冠心病患者主要不良心血管事件发生情况；采用单因素分析影响2型糖尿病伴冠心病患者主要不良心血管事件发生的因素，并对其影响因素进行多因素逐步Logistic回归分析；绘制受试者工作特征（ROC）曲线分析24 h血糖、血糖波动幅度及血清Gal-3预测2型糖尿病伴冠心病患者发生主要不良心血管事件的价值。结果 2型糖尿病伴冠心病患者FBG、HbA1c及血清Gal-3水平较单纯2型糖尿病患者和健康体检者高（P <0.05）；高危组24 h血糖、血糖波动幅度及血清Gal-3水平较中危组、低危组高（P <0.05）；相关性分析结果显示，患者病情严重程度（Gensini分数）与24 h血糖、血糖波动幅度及血清Gal-3呈正相关（r =0.404、0.437和0.526，均P <0.05）；随访1年，118例2型糖尿病伴冠心病患者中共有36例发生主要不良心血管事件，发生组患者2支及以上病变支数、FBG、HbA1c、24 h血糖、血糖波动幅度及血清Gal-3水平高于未发生组（P <0.05）；多因素逐步Logistic回归分析结果显示，病变支数［O^R=2.821（95% CI：1.053，7.557）］、24 h血糖［O^R=3.873，（95% CI：1.446，10.376）］、血糖波动幅度［O^R=3.636（95% CI：1.357，9.742）］、Gal-3［O^R=3.442（95% CI：1.285，9.221）］是影响2型糖尿病伴冠心病患者主要不良心血管事件发生的危险因素（P <0.05）；ROC曲线分析显示，2型糖尿病伴冠心病患者24 h血糖、血糖波动幅度及血清Gal-3预测主要不良心血管事件的最佳截断值分别为3.72 mmol/L、2.15 mmol/L和11.90 ng/mL，敏感性分别为83.33%（95% CI：0.672，0.936）、80.56%（95% CI：0.640，0.918）和86.11%（95% CI：0.705，0.953），特异性分别为76.83%（95% CI：0.662，0.854）、65.85%（95% CI：0.546，0.760）和63.41%（95% CI：0.522，0.738），曲线下面积（AUC）分别为0.840（95% CI：0.761，0.901）、0.775（95% CI：0.689，0.847）和0.813（95% CI：0.731，0.879），三者联合预测的敏感性、特异性及AUC分别为80.56%（95% CI：0.640，0.918）、97.56%（95% CI：0.915，0.997）和0.949（95% CI：0.892，0.981）。结论 2型糖尿病伴冠心病患者血糖波动及血清Gal-3影响主要不良心血管事件的发生，两者均可作为预测主要不良心血管事件的敏感指标。

Abstract:

Objective To explore the predictive value of blood glucose fluctuation and serum galectin-3 (Gal-3) level on major adverse cardiovascular events in patients with type 2 diabetes mellitus with coronary heart disease.Methods From March 2019 to March 2021, 118 patients with type 2 diabetes with coronary heart disease admitted to the hospital were selected, 54 patients with simple type 2 diabetes mellitus were selected, and 46 healthy people who came to the hospital for physical examination during the same period were selected. The levels of fasting blood glucose (FBG), glycosylated hemoglobin (HbA1c), and serum Gal-3 were compared in three groups. The 24-hour average blood glucose standard deviation, average blood glucose fluctuation range, and serum Gal-3 levels were compared in patients with type 2 diabetes mellitus with different severity of coronary heart disease. Pearson correlation was used to analyze the disease severity (Gensini score) and the 24-hour average blood sugar standard deviation, and the average blood sugar fluctuation range. After followed up for 1 year, the incidence of major adverse cardiovascular events in patients with type 2 diabetes mellitus with coronary heart disease was counted. Univariate analysis was used to analyze the factors affecting the occurrence of major adverse cardiovascular events in patients with type 2 diabetes mellitus with coronary heart disease, and Logistic regression analysis was performed on the influencing factors. The receiver operating curve (ROC) was used to analyze the 24-hour average blood glucose standard deviation, the average blood glucose fluctuation range, and the value of serum Gal-3 level in predicting the occurrence of major adverse cardiovascular events in patients with type 2 diabetes and coronary heart disease.Results Type 2 diabetic patients with coronary heart disease had higher levels of FBG, HbA1c and serum Gal-3 than patients with simple type 2 diabetes mellitus and healthy subjects (P <0.05). The 24-hour average blood sugar standard deviation, the average blood sugar fluctuation range, and the serum Gal-3 level were higher in the high-risk group than those in the median- or low-risk group (P < 0.05). Correlation analysis showed: the patient's disease severity (Gensini score) was all positively correlated with the 24-hour average blood sugar standard deviation (r = 0.404), the average blood sugar fluctuation range (r = 0.437), and the serum Gal-3 level (r = 0.526). During 1-year follow-up, 36 of the 118 T2DM patients with coronary heart disease had major adverse cardiovascular events. The composition ratio of 2 or more diseased branches, FBG, HbAlc, 24-hour average blood glucose standard deviation, average blood glucose fluctuation range, and serum Gal-3 level in the occurrence group were higher than those in the non-occurrence group. Logistic multivariate regression analysis showed: the number of lesions [O^R = 2.821, (95% CI: 1.053, 7.557) ], the 24-hour average blood glucose standard deviation [O^R=3.873, 95% CI: 1.446, 10.376) ], the average blood glucose fluctuation range [O^R = 3.636, (95% CI: 1.357, 9.742) ], and Gal-3 level [O^R = 3.442, (95% CI: 1.285, 9.221) ] were risks of major adverse cardiovascular events in type 2 diabetes patients with coronary heart disease factor (P < 0.05). ROC analysis showed that, the best cut-off points of 24-hour mean blood glucose standard deviation, mean blood glucose fluctuation range, and serum Gal-3 level for predicting major adverse cardiovascular events in type 2 diabetic patients with coronary heart disease were 3.72 mmol/L, 2.15 mmol/L, and 11.90 ng/mL, respectively, the sensitivity was 83.33% (95% CI: 0.672, 0.936), 80.56% (95% CI: 0.640, 0.918), 86.11% (95% CI: 0.705, 0.953), the specificities were 76.83% (95% CI: 0.662, 0.854), 65.85% (95% CI: 0.546, 0.760), 63.41% (95% CI: 0.522, 0.738), and the area under curve (AUC) was 0.840 (95% CI: 0.761, 0.901), 0.775 (95% CI: 0.689, 0.847), 0.813 (95% CI: 0.731, 0.879). The sensitivity, specificity, and AUC of the combination of the three were 97.56% (95% CI: 0.915, 0.997) and 0.949 (95% CI: 0.892, 0.981), respectively.Conclusion Blood glucose fluctuations and serum Gal-3 levels in type 2 diabetes patients with coronary heart disease can affect the occurrence of major adverse cardiovascular events. Clinical monitoring of blood glucose fluctuations and serum Gal-3 levels in patients can be used as sensitive indicators for predicting major adverse cardiovascular events.