妊娠糖尿病诊断中采取糖化血红蛋白随机检验的应用

The application of glycosylated hemoglobin randomized test in the diagnosis of gestational diabetes mellitus

目的:研究妊娠糖尿病(GDM)患者诊断中采取糖化血红蛋白(HbAlc)随机检验的应用价值。方法:回顾性分析2017-02～2018-02本院收治60例GDM患者的临床资料,设为GDM组;将同期在本院进行健康体检的60例健康女性设为对照组,60例正常妊娠者分为正常妊娠组。对三组对象进行空腹血糖(FPG)、HbAlc、口服葡萄糖耐量试验(GCT)监测,记录监测结果。结果:(1)GDM组FPG、HbAlc、GCT结果均比正常妊娠组高,差异具有统计学意义(P<0.05);正常妊娠组与对照组的FPG、HbAlc、GCT结果差异无统计学意义(P>0.05);(2)GDM组FPG、HbAlc、GCT阳性率均比正常妊娠组高,具有统计学意义(P<0.05);(3)HbAlc对GDM的诊断符合率、阳性预测值均比FPG、GCT高,且漏诊率、误诊率明显更低(P<0.05)。结论:HbAlc随机检验操作简单,对GDM的诊断符合率高,特异性强,在GDM早期诊断、疗效判定方面具有重要作用。

Objective: To study the application of glycosylated hemoglobin (HbAlc) randomized test in the diagnosis of gestational diabetes mellitus (GDM) patients. Methods: The clinical data of 60 GDM patients who were admitted in our hospital from Feb 2017 to Feb 2018 were retrospectively analyzed. They were divided into GDM group. 60 healthy women who underwent physical examination in our hospital at the same time were set up as the control group. 60 normal pregnancies were divided into normal pregnancy group. The fasting blood glucose (FPG), HbAlc, and oral glucose tolerance test (GCT) of the three groups were monitored and recorded. Results:(1) The results of FPG, HbAlc, GCT in the GDM group were higher than the normal pregnancy group, and the difference was statistically significant (P<0.05). There was no statistical difference in FPG, HbAlc, GCT of the normal pregnancy group and the control group (P>0.05).(2) The positive rate of FPG, HbAlc, GCT in the GDM group was statistically higher than the normal pregnancy group, and the difference was statistically significant (P<0.05).(3) The diagnostic coincidence rate and positive predictive value of HbAlc for GDM were higher than FPG and GCT, while the rate of missed diagnosis and misdiagnosis was significantly lower (P<0.05). Conclusion: HbAlc randomized test plays an important role in the early diagnosis of GDM and the evaluation of curative effect, with its simple operation, high diagnostic accordance rate of GDM, and strong specificity.