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临床试验/NCT02942719
NCT02942719Unknown不适用

The Establishment and Application of the New Labor Progress Centered System of Reducing Cesarean Section Rates in China

Shanghai First Maternity and Infant Hospital1 个研究点 分布在 1 个国家目标入组 15,000 人开始时间: 2016年1月最近更新:
适应症

试验速览

阶段
不适用
入组人数
15,000
试验地点
1
主要终点
times of uterus contraction

研究概览

简要总结

  1. To describe the average labor curve and establish new labor progression standards.
  2. Cesarean section rates: Based on big data, the investigator will introduce the international advanced Robson class method and identify the appropriate level of cesarean section rate for each type population.
  3. Establishment of "Chinese maternal-fetal medical collaboration network" and APP to promote natural childbirth.

详细描述

  1. To describe the average labor curve and establish new labor progression standards. The investigator will investigate the current characteristics of obstetric population and the labor progression with obstetric intervention in China. The investigator compare the different effects of traditional labor progression management model, new labor progression management model and active labor progression management model on labor outcomes. Based on the best outcomes of maternity and infants, the investigator will establish and modify new labor progression which is suitable for Chinese.
  2. Cesarean section rates: Based on big data, the investigator will introduce the international advanced Robson class method and identify the appropriate level of cesarean section rate for each type population.the investigator compare cesarean section rates of different level hospitals and evaluate the effects of reducing cesarean section rates. The investigator also analyze the risk factors of cesarean section rates of the ten Robson classification, which will provide basis for reducing cesarean section rates under the new strategy.
  3. Establishment of "Chinese maternal-fetal medical collaboration network" and mobile application software (APP) to promote natural childbirth: The investigator establish perinatal data center using the hospital information system (HIS) system of hospital. The investigator predict the cesarean section rates and relative factors using the Robson classification method, and propose the new strategy of reducing cesarean section rates. Meanwhile, the investigator develop the quality management system toolkit which can help clinicians standardize behavior and improve obstetric safety.

研究设计

研究类型
Observational
观察模型
Cohort
时间视角
Prospective

入排标准

年龄范围
18 Years 至 —(Adult, Older Adult)
性别
Female
接受健康志愿者

入选标准

  • Chinese pregnant women
  • head position
  • 37 weeks + 0 day - 41weeks + 6 days
  • low-risk pregnancy
  • vaginal delivery willingness
  • vaginal cervix <7 cm after labor

排除标准

  • multiple pregnancy
  • non-head position
  • selective cesarean section
  • prenatal cesarean section
  • age <18 years
  • previous childbirth history
  • pregnancy complications
  • important fetal malformations.

结局指标

主要结局

times of uterus contraction

时间窗: 10 minutes

The investigator count the times of uterus contraction in 10 minutes both intrapartum and postpartum.

次要结局

  • fetal heart rate(1 minute)
  • Apgar scores(1 minute and 5minutes)
  • blood pressure(10 minutes)

研究者

申办方类型
Other
责任方
Sponsor

研究点 (1)

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