Clinical trial NCT02942719: The Establishment and Application of the New Labor Progress Centered System of Reducing Cesarean Section Rates in China
Official title: The Establishment and Application of the New Labor Progress Centered System of Reducing Cesarean Section Rates in China
Study type: OBSERVATIONAL
Overall status: UNKNOWN
Conditions: Pregnancy Complications
Postpartum Hemorrhage
Lead sponsor: Shanghai First Maternity and Infant Hospital
Sponsor class: OTHER
First posted: 2016-10-24
Enrollment: 15000
Sex: FEMALE
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Observational model: COHORT
Time perspective: PROSPECTIVE
Sampling method: PROBABILITY_SAMPLE
Study population: A total of 20 hospitals from different places of China participated this study. Their annual delivery amount are more than 5000 times and their cesarean section rates are about 40%. The labor progression study include a total of 15,000 puerperae.

Brief summary: 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.

Detailed description: 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.

Eligibility criteria: Inclusion Criteria:

1. Chinese pregnant women
2. singleton
3. head position
4. 37 weeks + 0 day - 41weeks + 6 days
5. primipara
6. low-risk pregnancy
7. vaginal delivery willingness
8. vaginal cervix \<7 cm after labor

Exclusion Criteria:

1. multiple pregnancy
2. non-head position
3. stillbirth
4. selective cesarean section
5. prenatal cesarean section
6. age \<18 years
7. previous childbirth history
8. pregnancy complications
9. important fetal malformations.

Primary outcomes:
measure: times of uterus contraction
timeFrame: 10 minutes
Secondary outcomes:
measure: fetal heart rate
timeFrame: 1 minute
measure: blood pressure
timeFrame: 10 minutes
measure: Apgar scores
timeFrame: 1 minute and 5minutes
Other outcomes:
Locations:
city: Shanghai
country: China
facility: Shanghai First Maternity and Infant Hospital
state: Shanghai
Study officials:
affiliation: Shanghai First Maternal and Infant Health Hospital affiliated to Tongji University Medical School
name: Tao Duan, Ph.D
role: PRINCIPAL_INVESTIGATOR
References: