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Clinical algorithms for identification and management of delay in the progression of first and second stage of labour.
  • +4
  • Julia Pasquale,
  • Mónica Chamillard,
  • Virginia Diaz,
  • Celina Gialdini,
  • Mercedes Bonet,
  • Olufemi Oladapo,
  • Edgardo Abalos
Julia Pasquale
Centro Rosarino de Estudios Perinatales
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Mónica Chamillard
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Virginia Diaz
Centro Rosarino de Estudios Perinatales
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Celina Gialdini
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Mercedes Bonet
World Health Organization
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Olufemi Oladapo
World Health Organization
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Edgardo Abalos
Centro Rosarino de Estudios Perinatales (CREP)
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Abstract

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.

Peer review status:ACCEPTED

12 Nov 2020Submitted to BJOG: An International Journal of Obstetrics and Gynaecology
12 Nov 2020Submission Checks Completed
12 Nov 2020Assigned to Editor
16 Nov 2020Reviewer(s) Assigned
06 Dec 2020Review(s) Completed, Editorial Evaluation Pending
15 Dec 2020Editorial Decision: Revise Minor
30 Dec 20201st Revision Received
11 Jan 2021Submission Checks Completed
11 Jan 2021Assigned to Editor
17 Jan 2021Review(s) Completed, Editorial Evaluation Pending
09 Feb 2021Editorial Decision: Accept