Vaginal progesterone for prevention of preterm birth in asymptomatic high-risk women with a normal cervical length: a systematic review and meta-analysis.
Jason PhungK P WilliamsL McAullifeW N MartinC FlintB AndrewJ HyettF ParkCraig E PennellPublished in: The journal of maternal-fetal & neonatal medicine : the official journal of the European Association of Perinatal Medicine, the Federation of Asia and Oceania Perinatal Societies, the International Society of Perinatal Obstetricians (2021)
Objective: To determine whether vaginal progesterone reduces spontaneous preterm birth (sPTB) before 37 weeks in asymptomatic high-risk women with a singleton pregnancy and normal mid-gestation cervical length.Study design: Databases were searched (from inception to December 2020) with the search terms "progesterone" and "premature birth" or "preterm birth". Studies were screened and included if they assessed vaginal progesterone compared to placebo in women with normal cervical length. Data were pooled and synthesized in a meta-analysis using a random effects model.Data sources: MEDLINE and Embase databases.Study synthesis: Following PRISMA screening guidelines, data from 1127 women across three studies were available for synthesis. All studies had low risk of bias and were of high quality. The primary outcome was sPTB <37 weeks, with secondary outcomes of sPTB <34 weeks. Vaginal progesterone did not significantly reduce sPTB before 37 weeks, or before 34 weeks with a relative risk (RR) of 0.76 (95% CI 0.37-1.55, p = .45) and 0.51 (95% CI 0.12-2.13, p = .35), respectively.Conclusions: Vaginal progesterone does not decrease the risk of sPTB in high-risk singleton pregnancies with a normal mid-gestation cervical length.
Keyphrases
- preterm birth
- gestational age
- birth weight
- low birth weight
- estrogen receptor
- big data
- electronic health record
- case control
- type diabetes
- randomized controlled trial
- clinical trial
- polycystic ovary syndrome
- data analysis
- systematic review
- pregnancy outcomes
- machine learning
- body mass index
- adipose tissue
- artificial intelligence
- drinking water
- skeletal muscle
- phase iii
- deep learning
- insulin resistance
- breast cancer risk
- placebo controlled
- double blind