Tan Hongzhuan, Wen Shi Wu, Chen Xi Kuan, Demissie Kitaw, Walker Mark
School of Public Health, Central South University, Changsha, Hunan, PR China.
Eur J Obstet Gynecol Reprod Biol. 2007 Apr;131(2):132-7. doi: 10.1016/j.ejogrb.2006.04.038.
To create prediction models of early preterm birth for singletons, twin, and triplet pregnancies.
We used a historical cohort study with the 1996 birth registration data for singletons and the 1995-1997 linked birth/infant death dataset for multiple births of the United States. Preterm birth was defined as gestational age <32 completed weeks. Eligible study subjects were randomly allocated to two groups: one group (80% subjects) for the creation of the prediction models, and the other group (20% subjects) for the validation of the established prediction models. Multivariate logistic regressions were used to establish the prediction models. We further assessed the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of the established prediction models with different cut-off values in the validation group.
The sensitivity, specificity, PPV, and NPV of the established model were 24.58, 93.54, 5.91, and 98.69%, respectively for singletons, 64.66, 57.04, 16.29, and 92.59%, respectively for twins, and 63.57, 53.58, 42.96, and 72.78%, respectively for triplets.
The prediction models of early preterm birth for singleton, twin, and triplet pregnancies created by this study could be useful for obstetricians to identify women being at high risk of preterm birth at early gestation.
创建单胎、双胎和三胎妊娠早期早产的预测模型。
我们采用了一项历史性队列研究，使用了美国1996年单胎出生登记数据以及1995 - 1997年多胎出生/婴儿死亡关联数据集。早产定义为孕周<32足周。符合条件的研究对象被随机分为两组：一组（80%的对象）用于创建预测模型，另一组（20%的对象）用于验证所建立的预测模型。采用多变量逻辑回归来建立预测模型。我们在验证组中进一步评估了所建立的预测模型在不同临界值下的敏感性、特异性、阳性预测值（PPV）和阴性预测值（NPV）。
所建立模型的敏感性、特异性、PPV和NPV分别为：单胎妊娠时为24.58%、93.54%、5.91%和98.69%；双胎妊娠时为64.66%、57.04%、16.29%和92.59%；三胎妊娠时为63.57%、53.58%、42.96%和72.78%。
本研究创建的单胎、双胎和三胎妊娠早期早产预测模型，可能有助于产科医生在妊娠早期识别早产高危女性。
