TY - JOUR
T1 - Clinical algorithms for the monitoring and management of spontaneous, uncomplicated labour and childbirth
AU - Pasquale, Julia
AU - Gialdini, Celina
AU - Chamillard, Mónica
AU - Diaz, Virginia
AU - Rijken, Marcus J.
AU - Browne, Joyce L.
AU - Seto, Mimi Tin Yan
AU - Cheung, Ka Wang
AU - Bonet, Mercedes
AU - Ciabati, Livia
AU - De Oliveira, Lariza Laura
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 - Gülmezoglu, A. Metin
AU - Oladapo, Olufemi
N1 - Publisher Copyright:
© 2024 John Wiley & Sons Ltd.
PY - 2024/8
Y1 - 2024/8
N2 - Aim: To develop evidence-based clinical algorithms for the assessment and management of spontaneous, uncomplicated labour and vaginal birth. Population: Pregnant women at any stage of labour, with singleton, term pregnancies considered to be at low risk of developing complications. Setting: Health facilities in low- and middle-income countries. Search Strategy: We searched for relevant published algorithms, guidelines, systematic reviews and primary research studies on Cochrane Library, PubMed, and Google on terms related to spontaneous, uncomplicated labour and childbirth up to 01 June 2023. Case scenarios: Three case scenarios were developed to cover assessments and management for spontaneous, uncomplicated first, second and third stage of labour. The algorithms provide pathways for definition, assessments, diagnosis, and links to other algorithms in this series for management of complications. Conclusions: We have developed three clinical algorithms to support evidence-based decision making during spontaneous, uncomplicated labour and vaginal birth. These algorithms may help guide health care staff to institute respectful care, appropriate interventions where needed, and potentially reduce the unnecessary use of interventions during labour and childbirth.
AB - Aim: To develop evidence-based clinical algorithms for the assessment and management of spontaneous, uncomplicated labour and vaginal birth. Population: Pregnant women at any stage of labour, with singleton, term pregnancies considered to be at low risk of developing complications. Setting: Health facilities in low- and middle-income countries. Search Strategy: We searched for relevant published algorithms, guidelines, systematic reviews and primary research studies on Cochrane Library, PubMed, and Google on terms related to spontaneous, uncomplicated labour and childbirth up to 01 June 2023. Case scenarios: Three case scenarios were developed to cover assessments and management for spontaneous, uncomplicated first, second and third stage of labour. The algorithms provide pathways for definition, assessments, diagnosis, and links to other algorithms in this series for management of complications. Conclusions: We have developed three clinical algorithms to support evidence-based decision making during spontaneous, uncomplicated labour and vaginal birth. These algorithms may help guide health care staff to institute respectful care, appropriate interventions where needed, and potentially reduce the unnecessary use of interventions during labour and childbirth.
KW - childbirth
KW - labour
KW - normal
KW - spontaneous
KW - uncomplicated
UR - https://www.scopus.com/pages/publications/85198121549
U2 - 10.1111/1471-0528.17895
DO - 10.1111/1471-0528.17895
M3 - Review article
AN - SCOPUS:85198121549
SN - 1470-0328
VL - 131
SP - 17
EP - 27
JO - BJOG: An International Journal of Obstetrics and Gynaecology
JF - BJOG: An International Journal of Obstetrics and Gynaecology
IS - S2
M1 - doi.org/10.1111/1471-0528.17895
ER -