Tabriz University of Medical Sciences, Iran.
Zanjan University of Medical Sciences, Iran.
Clin Nurs Res. 2022 Sep;31(7):1325-1331. doi: 10.1177/10547738221091878. Epub 2022 Apr 29.
In this prospective cohort study, we aimed to investigate external validity of the Allouche's nomogram to predict preterm birth in symptomatic women in Iran. We employed six variables of cervical length, uterine contractions, rupture of membranes, vaginal bleeding, gestational age, and multiple pregnancy to draw the nomograms. These variables were examined in the first day of women's hospitalization and participants followed up until giving birth. The concordance index of area under the curve (AUC) was used for validation of the nomograms. Of the participants 10% gave birth within 48 hours and 29% before 34 weeks. The nomogram had sufficient accuracy in predicting birth within 48 hours (AUC 0.89 [95% CI 0.82-0.96]) and birth before 34 weeks (AUC 0.89 [95% CI 0.84-0.94]). The optimal risk threshold for nomogram predicting birth within 48 hours was 0.16. Use of these two nomograms, can improve the health of women and their neonates.
在这项前瞻性队列研究中，我们旨在研究 Allouche 列线图在伊朗有症状的女性中预测早产的外部有效性。我们采用了宫颈长度、子宫收缩、胎膜破裂、阴道出血、胎龄和多胎妊娠这 6 个变量来绘制列线图。这些变量在女性住院的第一天进行检查，参与者一直随访到分娩。曲线下面积（AUC）的一致性指数用于验证列线图。在参与者中，10%的人在 48 小时内分娩，29%的人在 34 周前分娩。该列线图在预测 48 小时内分娩（AUC 0.89 [95%CI 0.82-0.96]）和 34 周前分娩（AUC 0.89 [95%CI 0.84-0.94]）方面具有足够的准确性。预测 48 小时内分娩的最佳风险阈值为 0.16。使用这两个列线图可以改善妇女及其新生儿的健康状况。
