Aim: To construct evidence-based algorithms for the assessment and management of common amniotic fluid abnormalities detected during labour.
Population: Low-risk singleton, term pregnant women in labour.
Setting: Birth facilities in low- and middle-income countries.
Search strategy: We searched international guidelines published by the American College of Obstetricians and Gynecologists (ACOG), the National Institute for Health and Care Excellence (NICE), the Royal Australian and New Zealand College of Obstetricians and Gynaecologists (RANZCOG), the Royal College of Obstetricians and Gynaecologists (RCOG), the Society of Obstetrics and Gynaecology (SOGC) and the World Health Organization (WHO). We also searched The Cochrane Library and MEDLINE up to 20 January 2020 using keywords for relevant systematic reviews and randomised trials.
Case scenarios: We developed evidence-based intrapartum care algorithms for four case scenarios: oligohydramnios; meconium-stained amniotic fluid; bloody amniotic fluid or vaginal bleeding; and purulent amniotic fluid or discharge. These conditions may be associated with fetal and /or maternal morbidity. Differential diagnosis includes uteroplacental insufficiency, fetal growth restriction, fetal distress, abruption, placenta or vasa praevia, uterine rupture and intra-amniotic infection, respectively. Algorithms include how to assess for, diagnose and manage these conditions.
Conclusions: Four algorithms are presented, to provide a systematic approach and guidance on the clinical management for the following amniotic fluid abnormalities: oligohydramnios; meconium-stained liquor; bloody amniotic fluid or vaginal bleeding; and purulent amniotic fluid or discharge. These algorithms may be beneficial in supporting clinical decision making, particularly in low-resource settings.
Tweetable abstract: Evidence based algorithms for management of common amniotic fluid abnormalities seen during labour.
Keywords: Amniotic fluid; bleeding; chorioamnionitis; intrapartum; liquor; meconium; oligohydramnios.
© 2022 John Wiley & Sons Ltd.