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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. Evidence‐based clinical algorithms may help support respectful, high quality intrapartum care. [Correction added on 23 August 2024, after first online publication: The Abstract has been updated to structure layout in this version.] [ABSTRACT FROM AUTHOR]

Objectives: To systematically review reasons for the willingness to participate in biomedical human subjects research in low- and middle-income countries (LMICs).Methods: Five databases were systematically searched for articles published between 2000 and 2017 containing the domain of 'human subjects research' in 'LMICs' and determinant 'reasons for (non)participation'. Reasons mentioned were extracted, ranked and results narratively described.Results: Ninety-four articles were included, 44 qualitative and 50 mixed-methods studies. Altruism, personal health benefits, access to health care, monetary benefit, knowledge, social support and trust were the most important reasons for participation. Primary reasons for non-participation were safety concerns, inconvenience, stigmatisation, lack of social support, confidentiality concerns, physical pain, efficacy concerns and distrust. Stigmatisation was a major concern in relation to HIV research. Reasons were similar across different regions, gender, non-patient or patient participants and real or hypothetical study designs.Conclusions: Addressing factors that affect (non-)participation in the planning process and during the conduct of research may enhance voluntary consent to participation and reduce barriers for potential participants. [ABSTRACT FROM AUTHOR]

Objective: To examine the association between maternal weight at <17 weeks gestation and maternal and infant outcomes of pregnancy, delivery, and the postpartum period in pregnant Ghanaian women.Methods: A prospective cohort study of 1,000 women in Accra, Ghana (2012-2014), was conducted. Women were classified as having overweight (BMI 25-30) and obesity (BMI ≥ 30), and their obstetric and infant outcomes were analyzed using multivariate logistic regression.Results: The analysis included 824 women, average 28 years (SD 5.1); 313 (31.3%) had overweight and 169 (16.9%) obesity. Women with obesity had a two-fold increased risk for cesarean sections (RR 2.20, 95% CI 1.21-4.02) and more than a six-fold higher risk for pregnancy-induced hypertension (RR 6.17, 95% CI 2.90-13.13) and chronic hypertension (RR 6.00, 95% CI 1.40-25.76). Infants of women with overweight or obesity were more likely to be macrosomic (RR 2.37, 95% CI 1.13-4.97).Conclusions: The global obesity epidemic has reached women in low- and middle-income countries (LMIC) with important adverse consequences for maternal and infant health. Antenatal care in LMIC will need to anticipate this potential expansion of complications, including the development of guidelines for optimal maternity care for pregnant women with overweight and obesity. [ABSTRACT FROM AUTHOR]

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., (© 2024 John Wiley & Sons Ltd.)