Prediction of spontaneous onset of labor at term (PREDICT study): Research protocol

BACKGROUND: Recent studies have shown that elective induction of labor versus expectant management after 39 weeks of pregnancy result in lower incidence of perinatal complications, while the proportion of cesarean deliveries remains stable, or even decreases. Still, evidence regarding collateral consequences of the potential increase of induction of labor procedures is still lacking. Also, the results of these studies must be carefully interpreted and thoroughly counter-balanced with women’s thoughts and opinions regarding the active management of the last weeks of pregnancy. Therefore, it may be useful to develop a tool that aids in the decision-making process by differentiating women who will spontaneously go into labor from those who will require induction. OBJECTIVE: To develop a predictive model to calculate the probability of spontaneous onset of labor at term. METHODS: We designed a prospective national multicentric observational study including women enrolled at 39 weeks of gestation, carrying singleton pregnancies. After signing an informed consent form, several clinical, ultrasonographic, biophysical and biochemical variables will be collected by trained staff. If delivery has not occurred at 40 weeks of pregnancy, a second visit and evaluation will be performed. Prenatal care will be continued according to current hospital guidelines. Once recruitment is completed, the information gathered will be used to develop a logistic regression-based predictive model of spontaneous onset of labor between 39 and 41 weeks of gestation. A secondary exploration of the data collected at 40 weeks, as well as a survival analysis regarding time-to-delivery outcomes will also be performed. A total sample of 429 participants is needed for the expected number of events. CONCLUSION: This study aims to develop a model which may help in the decision-making process during follow-up of the last weeks of pregnancy. TRIAL REGISTRATION: NCT05109247 (clinicaltrials.gov).