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Clinical algorithms for monitoring and management of spontaneous, uncomplicated labour and childbirth
  • +6
  • Julia Pasquale,
  • Celina Gialdini,
  • Mónica Chamillard,
  • Virginia Diaz,
  • Marcus Rijken,
  • Joyce Browne L,
  • Mimi Tin Yan Seto,
  • Ka Wang Cheung,
  • Mercedes Bonet
Julia Pasquale
Centro Rosarino de Estudios Perinatales

Corresponding Author:[email protected]

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Celina Gialdini
Centro Rosarino de Estudios Perinatales
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Mónica Chamillard
Centro Rosarino de Estudios Perinatales
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Virginia Diaz
Centro Rosarino de Estudios Perinatales
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Marcus Rijken
Universitair Medisch Centrum Utrecht
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Joyce Browne L
Universitair Medisch Centrum Utrecht
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Mimi Tin Yan Seto
The University of Hong Kong Department of Obstetrics and Gynaecology
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Ka Wang Cheung
The University of Hong Kong Department of Obstetrics and Gynaecology
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Mercedes Bonet
World Health Organization TDR
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Abstract

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 might 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.