Clinical management of deviations in maternal temperature during labour and childbirth: an evidence-based intrapartum care algorithm

Aim: The development of an evidence-based algorithm for the clinical management of deviations in maternal temperature during labour and childbirth. Population: Pregnant women at any stage of labour, with singleton, term (37–42 weeks) pregnancies at low risk of developing complications. Setting: Health facilities in low- and middle-income countries. Search strategy: We searched for international guidelines and prioritised WHO guidelines. In addition, we searched for other sources of evidence in the Cochrane Database of Systematic Reviews, EMBASE, MEDLINE and CINAHL until June 2020. Studies were prioritised according to the hierarchy of evidence. Case scenarios: Two case scenarios were identified: maternal hyperthermia and hypothermia. We developed a single algorithm including both, due to commonalities in diagnosis, monitoring and management of underlying causes. The underlying conditions covered in the pathway include maternal sepsis and infection, chorioamnionitis, pyelonephritis, lower urinary tract and respiratory infections. Key decision points in the algorithm are suspicion of condition, definition, differential diagnosis, monitoring and management. Conclusions: We present an evidence-based algorithm to assist healthcare professionals in making decisions about appropriate clinical management of deviations in maternal temperature. Research is needed to assess the views of healthcare professionals and women accessing healthcare on the feasibility of implementing the algorithm. Tweetable abstract: An evidence-based intrapartum care algorithm to support management of deviations in maternal temperature in labour and childbirth. #sepsis #maternitycare.