TY - JOUR
T1 - Clinical management of uterine contraction abnormalities; an evidence-based intrapartum care algorithm
AU - Gülümser, C.
AU - Yassa, M.
AU - the WHO Intrapartum Care Algorithms Working Group
AU - Ciabati, Livia
AU - de Oliveira, Lariza Laura
AU - Souza, Renato
AU - Browne, Joyce
AU - Rijken, Marcus
AU - Fawcus, Sue
AU - Hofmeyr, Justus
AU - Liabsuetrakul, Tippawan
AU - Gülümser, Çağri
AU - Blennerhassett, Anna
AU - Lissauer, David
AU - Meher, Shireen
AU - Althabe, Fernando
AU - Bonet, Mercedes
AU - Metin Gülmezoglu, A.
AU - Oladapo, Olufemi
N1 - Funding Information: This work was funded by the Bill & Melinda Gates Foundation (Grant #OPP1084318); The United States Agency for International Development (USAID); and the UNDP‐UNFPA‐UNICEF‐WHO‐World Bank Special Programme of Research, Development and Research Training in Human Reproduction (HRP), a cosponsored programme executed by the World Health Organization (WHO). The funders had no role in design, data collection and analysis, decision to publish or preparation of the manuscript. Publisher Copyright: © 2022 John Wiley & Sons Ltd.
PY - 2022
Y1 - 2022
N2 - Aim: To develop algorithms as decision support tools for identifying, managing and monitoring abnormal uterine activity during labour. Population: Women with singleton, term (37–42 weeks) pregnancies in active labour at admission. Setting: Institutional birth settings in low- and middle-income countries (the algorithm may be applicable to any health facility). Search strategy: PubMed was searched up to January 2020 using keywords. We also searched The Cochrane Library, and international guidelines from World Health Organization (WHO), National Institute for Health and Care Excellence (NICE), American College of Obstetricians and Gynecologists (ACOG) and French College of Gynaecologists and Obstetricians (CNGOF). Case scenarios: Algorithms were developed for two case scenarios: uterine hypoactivity and excessive uterine contractions. Key themes in the algorithm are: diagnosis, identification of probable causes, assessment of maternal and fetal condition and labour progress, monitoring and management. Conclusion: The algorithms for uterine hypoactivity and excessive uterine contractions have been developed to facilitate safe and effective management of abnormal uterine activity during labour. Research is needed to assess the views of healthcare professionals and women accessing healthcare to explore the feasibility of implementing these algorithms, and impact on labour outcomes. Tweetable abstract: An evidence-based algorithm to support clinical management of abnormal uterine activity during labour.
AB - Aim: To develop algorithms as decision support tools for identifying, managing and monitoring abnormal uterine activity during labour. Population: Women with singleton, term (37–42 weeks) pregnancies in active labour at admission. Setting: Institutional birth settings in low- and middle-income countries (the algorithm may be applicable to any health facility). Search strategy: PubMed was searched up to January 2020 using keywords. We also searched The Cochrane Library, and international guidelines from World Health Organization (WHO), National Institute for Health and Care Excellence (NICE), American College of Obstetricians and Gynecologists (ACOG) and French College of Gynaecologists and Obstetricians (CNGOF). Case scenarios: Algorithms were developed for two case scenarios: uterine hypoactivity and excessive uterine contractions. Key themes in the algorithm are: diagnosis, identification of probable causes, assessment of maternal and fetal condition and labour progress, monitoring and management. Conclusion: The algorithms for uterine hypoactivity and excessive uterine contractions have been developed to facilitate safe and effective management of abnormal uterine activity during labour. Research is needed to assess the views of healthcare professionals and women accessing healthcare to explore the feasibility of implementing these algorithms, and impact on labour outcomes. Tweetable abstract: An evidence-based algorithm to support clinical management of abnormal uterine activity during labour.
KW - Abnormal uterine activity
KW - clinical algorithm
KW - labour
KW - uterine contractions
KW - uterine hypoactivity
KW - uterine tachysystole
KW - vaginal birth
UR - http://www.scopus.com/inward/record.url?scp=85133550880&partnerID=8YFLogxK
U2 - https://doi.org/10.1111/1471-0528.16727
DO - https://doi.org/10.1111/1471-0528.16727
M3 - Article
C2 - 35415963
SN - 1470-0328
JO - BJOG: An International Journal of Obstetrics and Gynaecology
JF - BJOG: An International Journal of Obstetrics and Gynaecology
ER -