Phaloprakarn Chadakarn, Tangjitgamol Siriwan, Manusirivithaya Sumonmal
Department of Obstetrics and Gynecology, Bangkok Metropolitan Administration Medical College and Vajira Hospital, Dusit District, Bangkok, Thailand.
Eur J Obstet Gynecol Reprod Biol. 2009 Jul;145(1):71-5. doi: 10.1016/j.ejogrb.2009.04.016. Epub 2009 May 15.
To develop a risk score to predict women who are likely to have an abnormal glucose challenge test (GCT) for gestational diabetes mellitus (GDM) screening.
A cohort of 1876 pregnant women who underwent a GCT between March 2005 and December 2005 at our institution were studied. A multivariable analysis was performed to determine the clinical features that were significantly associated with an abnormal GCT. These factors were incorporated into the equation which was subsequently transformed to the risk score. The validity of this risk score was then tested in a different cohort of 1900 women who underwent a GCT between October 2006 and July 2007.
Of 1876 women in the derivation cohort, 586 (31.2%) had positive GDM screening. In a multivariable analysis, age, body mass index, family history of diabetes, prior macrosomia, and history of >or=2 spontaneous abortions were significantly associated with an abnormal GCT. These five variables were added into the equation to determine the risk score. At a cutoff score of >or=380, the sensitivity, specificity, positive predictive value, and negative predictive value to predict an abnormal GCT were 86.9%, 45.0%, 41.8%, and 88.3%, respectively. When the equation with the same cutoff score was tested in the validation cohort, a similar diagnostic performance was obtained. By adopting this risk scoring approach to GDM screening, 41.3% of women could avoid GCT.
Our risk score based on clinical data is simple, noninvasive, costless, and reliable to identify women who are likely to have an abnormal GCT.
开发一种风险评分系统,以预测可能在妊娠期糖尿病(GDM)筛查中葡萄糖耐量试验(GCT)结果异常的女性。
对2005年3月至2005年12月在我院接受GCT的1876名孕妇进行队列研究。进行多变量分析以确定与GCT异常显著相关的临床特征。将这些因素纳入方程,随后转换为风险评分。然后在2006年10月至2007年7月接受GCT的另一组1900名女性中测试该风险评分的有效性。
在推导队列的1876名女性中,586名(31.2%)GDM筛查呈阳性。在多变量分析中,年龄、体重指数、糖尿病家族史、既往巨大儿史以及≥2次自然流产史与GCT异常显著相关。将这五个变量加入方程以确定风险评分。在截断分数≥380时,预测GCT异常的敏感性、特异性、阳性预测值和阴性预测值分别为86.9%、45.0%、41.8%和88.3%。当在验证队列中使用相同截断分数的方程进行测试时,获得了相似的诊断性能。通过采用这种风险评分方法进行GDM筛查,41.3%的女性可以避免进行GCT。
我们基于临床数据的风险评分简单、无创、成本低廉且可靠,可用于识别可能GCT结果异常的女性。