Mater Clinical Unit, Faculty of Medicine, The University of Queensland, Raymond Terrace, South Brisbane, Queensland 4101, Australia; Mater Research, Faculty of Medicine, The University of Queensland, Raymond Terrace, South Brisbane, Queensland 4101, Australia.
Mater Research, Level 3, Aubigny Place, Raymond Terrace, Brisbane, Queensland 4101, Australia.
Diabetes Res Clin Pract. 2018 May;139:331-338. doi: 10.1016/j.diabres.2018.02.036. Epub 2018 Mar 14.
To develop a risk "engine" or calculator, integrating the risks of hyperglycemia, maternal BMI and other basic demographic data commonly available at the time of the pregnancy oral glucose tolerance test (OGTT), to predict an individual's absolute risk of specific adverse pregnancy outcomes.
Data from the Brisbane HAPO cohort was analysed using logistic regression to determine the relationship between four clinical outcomes (primary CS, birth injury, large-for-gestational age, excess neonatal adiposity) with different combinations of OGTT results and maternal demographics (age, height, BMI, parity). Existing sets of international GDM diagnostic criteria were also applied to the cohort.
191 (15.3%) women were diagnosed as GDM by one or more existing criteria. All international criteria performed poorly compared to risk models utilising OGTT results only, or OGTT results in combination with maternal demographics.
The risk engine's empirical performance on receiver - operator curve analysis was superior to the existing GDM diagnostic criteria tested. This concept shows promise for use in clinical practice, but further development is required.
开发一种风险“引擎”或计算器，整合妊娠口服葡萄糖耐量试验（OGTT）时常见的高血糖、产妇 BMI 及其他基本人口统计学数据的风险，以预测个体特定不良妊娠结局的绝对风险。
使用逻辑回归分析布里斯班 HAPO 队列的数据，以确定 OGTT 结果和产妇人口统计学数据（年龄、身高、BMI、产次）的不同组合与四种临床结局（主要剖宫产、分娩损伤、巨大儿、新生儿脂肪过多）之间的关系（年龄、身高、BMI、产次）。也将现有的国际 GDM 诊断标准应用于该队列。
191 名（15.3%）女性被一种或多种现有标准诊断为 GDM。与仅使用 OGTT 结果或 OGTT 结果结合产妇人口统计学数据的风险模型相比，所有国际标准的表现都较差。
接收器操作特征曲线分析中风险引擎的经验性能优于测试的现有 GDM 诊断标准。该概念有望在临床实践中得到应用，但需要进一步开发。
