Suppr超能文献

早产孕妇自发性早产的预测:羊水和宫颈液中多种蛋白质的分析

Prediction of spontaneous preterm delivery in women with preterm labor: analysis of multiple proteins in amniotic and cervical fluids.

作者信息

Holst Rose-Marie, Hagberg Henrik, Wennerholm Ulla-Britt, Skogstrand Kristin, Thorsen Poul, Jacobsson Bo

机构信息

From the Perinatal Center, Department of Obstetrics and Gynecology, Institute of Clinical Sciences, Sahlgrenska Academy, Sahlgrenska University Hospital/East, Göteborg, Sweden; the Imperial College, Institute of Reproductive and Developmental Biology, Queen Charlotte's & Chelsea Hospital, Hammersmith Campus, London, United Kingdom; the Department of Clinical Biochemistry, Statens Serum Institut, Copenhagen, Denmark; NANEA at the Department of Epidemiology, Aarhus University, Aarhus, Denmark; the Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, Georgia; and the Department of Obstetrics and Gynecology, Rikshospitalet, Oslo, Norway.

出版信息

Obstet Gynecol. 2009 Aug;114(2 Pt 1):268-277. doi: 10.1097/AOG.0b013e3181ae6a08.

Abstract

OBJECTIVE

To analyze whether specific proteins in amniotic and cervical fluids, alone or in combination with risk factors, can identify women in preterm labor with intact membranes who will deliver spontaneously within 7 days of sampling.

METHODS

In a cohort of 89 women in preterm labor, amniotic and cervical fluids were collected between 22 and 33 weeks of gestation. Twenty-seven proteins were analyzed simultaneously using multiplex technology. Individual levels of each protein were compared and calculations performed to find associations among different proteins, background variables, and spontaneous preterm delivery within 7 days of sampling. The area under the curve (AUC) was calculated using receiver operating characteristic curve analysis, and prediction models were created based on stepwise logistic regression.

RESULTS

We found two multivariable models that predicted spontaneous preterm delivery better than any single variable. One combined multivariable prediction model was based on amniotic macrophage inflammatory protein-1beta, cervical interferon-gamma, and monocyte chemotactic protein-1. This model predicted outcome with 91% sensitivity, 84% specificity, 78% positive predictive value, and 94% negative predictive value, with a likelihood ratio of 5.6 and AUC of 0.91. An alternative, noninvasive model based on cervical length, cervical interferon-gamma, interleukin-6, and monocyte chemotactic protein-1 predicted delivery within 7 days with 85% sensitivity, 82% specificity, 74% positive predictive value, and 90% negative predictive value, with a likelihood ratio of 4.7 and AUC of 0.91.

CONCLUSION

A combination of proteins from amniotic fluid and cervical fluid or cervical length can help determine which women will deliver preterm.

LEVEL OF EVIDENCE

II.

摘要

目的

分析羊水和宫颈液中的特定蛋白质单独或与危险因素联合使用时,能否识别胎膜完整的早产女性在采样后7天内自然分娩的情况。

方法

在一组89例早产女性队列中,于妊娠22至33周收集羊水和宫颈液。使用多重技术同时分析27种蛋白质。比较每种蛋白质的个体水平,并进行计算以找出不同蛋白质、背景变量与采样后7天内自然早产之间的关联。使用受试者工作特征曲线分析计算曲线下面积(AUC),并基于逐步逻辑回归创建预测模型。

结果

我们发现两个多变量模型比任何单一变量能更好地预测自然早产。一个联合多变量预测模型基于羊水巨噬细胞炎性蛋白-1β、宫颈干扰素-γ和单核细胞趋化蛋白-1。该模型预测结果的灵敏度为91%,特异度为84%,阳性预测值为78%,阴性预测值为94%,似然比为5.6,AUC为0.91。另一个基于宫颈长度、宫颈干扰素-γ、白细胞介素-6和单核细胞趋化蛋白-1的非侵入性模型预测7天内分娩的灵敏度为85%,特异度为82%,阳性预测值为74%,阴性预测值为90%,似然比为4.7,AUC为0.91。

结论

羊水和宫颈液中的蛋白质组合或宫颈长度有助于确定哪些女性会早产。

证据级别

II级。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验