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.

Aim: To develop clinical algorithms for the assessment and management of slow progress of labour. Population: Low-risk singleton, term, pregnant women in labour. Setting: Institutional births in low- and middle-income countries. Search Strategy: We systematically reviewed the literature on normal labour progression, and guidance on clinical management of abnormally slow progression from 1 December 2015 to 1 December 2020. Case scenarios: We developed two clinical algorithms: one for abnormally slow labour progression and arrest during first and one for second stage. Conclusions: Identifying abnormal progress of labour is often challenging. These algorithms may help to reduce misdiagnosis.