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孕妇皮下脂肪组织厚度与妊娠期糖尿病发生发展的关系。

Relationship maternal subcutaneous adipose tissue thickness and development of gestational diabetes mellitus.

作者信息

Kansu-Celik Hatice, Karakaya Burcu Kisa, Tasci Yasemin, Hancerliogullari Necati, Yaman Selen, Ozel Sule, Erkaya Salim

机构信息

Department of Obstetrics and Gynecology, Zekai Tahir Burak Woman's Health, Education and Research Hospital, Ankara, Turkey.

出版信息

Interv Med Appl Sci. 2018 Mar;10(1):13-18. doi: 10.1556/1646.10.2018.01.

Abstract

OBJECTIVE

We investigated whether the ultrasonographic measurement of maternal subcutaneous adipose tissue (SAT) thickness in the second trimester played a role in predicting gestational diabetes.

MATERIALS AND METHODS

This was a prospective cross-sectional study in which 223 women were classified as healthy ( = 177) or as gestational diabetes ( = 46) on the basis of a negative or positive two-step oral Glucose Challenge Test (GCT), respectively. The depth of the abdominal SAT was evaluated by two-dimensional ultrasonography. Body mass index (BMI), waist circumference (WC), and waist/hip ratio were determined.

RESULTS

There was a positive strong significant correlation between a 50-g GCT level and BMI, WC, and SAT thickness ( < 0.001). Receiver-operating characteristic curve analysis showed SAT thickness above 16.75 mm predicted gestational diabetes mellitus (GDM) with a sensitivity of 71.7%, a specificity of 57.1%, a positive predictive value of 32.3%, and a negative predictive value of 87.6%. There was a good correlation between SAT, BMI, and WC.

CONCLUSION

Increased SAT, BMI, and WC measurements may be helpful in predicting the risk of the development of GDM in pregnant women.

摘要

目的

我们研究了孕中期孕妇皮下脂肪组织(SAT)厚度的超声测量是否在预测妊娠期糖尿病中发挥作用。

材料与方法

这是一项前瞻性横断面研究,根据两步口服葡萄糖耐量试验(GCT)阴性或阳性,将223名女性分别分为健康组(n = 177)或妊娠期糖尿病组(n = 46)。通过二维超声评估腹部SAT的深度。测定体重指数(BMI)、腰围(WC)和腰臀比。

结果

50克GCT水平与BMI、WC和SAT厚度之间存在强正相关(P < 0.001)。受试者操作特征曲线分析显示,SAT厚度大于16.75毫米预测妊娠期糖尿病(GDM)的敏感性为71.7%,特异性为57.1%,阳性预测值为32.3%,阴性预测值为87.6%。SAT、BMI和WC之间存在良好的相关性。

结论

SAT、BMI和WC测量值的增加可能有助于预测孕妇发生GDM的风险。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2416/6167636/95b4ef965396/imas-10-01-01_f001.jpg

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