Factors associated with delayed onset of active labor following vaginal misoprostol administration among women at Mbarara Regional Referral Hospital, Uganda

Abstract

Objective To determine the factors associated with delayed onset of active labor following labor induction with vaginal misoprostol. Methods We conducted a prospective cohort study over 6 months at a tertiary hospital in Uganda. We enrolled mothers with pregnancies of at least 28 weeks, who were undergoing labor induction with 50 µg of vaginal misoprostol, administered every 6 hours with a maximum of four doses, and followed them up until onset of active labor. Labor onset was considered delayed if it occurred later than 12 hours after the first dose. Bivariate and multivariate analysis was performed to determine factors associated with delayed onset of active labor. Results Of the 88 mothers enrolled, 22.7% (n=20) had delayed onset of active labor. Nulliparity (adjusted relative risk [aRR] 2.34, 95% confidence interval [CI] 1.17–4.68) and gestational age less than 37 weeks (aRR 3.79, 95% CI 1.40–10.23) were associated with delayed onset of active labor following vaginal misoprostol administration whereas higher body mass index (aRR 0.38, 95% CI 0.18–0.79) decreased the risk. Conclusion Delayed onset of active labor following labor induction remains an important obstetric care challenge. Mothers undergoing labor induction should have their body mass index documented, and nulliparous women and mothers at less than 37 weeks of gestation should have their labor monitored for a longer duration following labor induction.

Labour Care Guide implementation as a decision-making tool for monitoring labour among healthcare providers in Uganda: protocol for a mixed-methods study

“…We will first summarise health-related and sociodemographic data between arms. For our primary effectiveness outcomes, we will fit a multivariable logistic regression model, with study arm as the predictor of interest, and age, high-risk pregnancy and health facility at enrolment as a priori additional variables in the model, due to their strong association with the selected outcome 34–36. Although not designed to detect a difference, we will also explore additional secondary outcomes, as listed above.…”

Labour Care Guide implementation as a decision-making tool for monitoring labour among health care providers in Southwestern Uganda: A protocol for a multisite Effectiveness-Implementation study

“…We will first summarize health-related and socio-demographic data between arms. For our primary effectiveness outcomes, we will fit a multivariable logistic regression model, with study arm as the predictor of interest, and age, high-risk pregnancy and health facility at enrollment as a priori additional variables in the model, due to their strong association with the selected outcome [25][26][27]. Although not designed to detect a difference, we will also explore additional secondary outcomes, as listed above.…”