Clinical algorithms for the management of intrapartum maternal urine abnormalities

Abstract

Aim: To develop evidence-based clinical algorithms for management of common intrapartum urinary abnormalities. Population: Women with singleton, term pregnancies in active labour and immediate postnatal period, at low risk of complications. Setting: Healthcare facilities in low- and middle-income countries. Search strategy: A systematic search and review were conducted on the current guidelines from WHO, NICE, ACOG and RCOG. Additional search was done on PubMed and The Cochrane Database of Systematic Reviews up to May 2020. Case scenarios: Four common intrapartum urinary abnormalities were selected: proteinuria, ketonuria, glycosuria and oliguria. Using reagent strip testing, glycosuria was defined as ≥2+ on one occasion or of ≥1+ on two or more occasions. Proteinuria was defined as ≥2+ and presence of ketone indicated ketonuria. Oliguria was defined as hourly urine output ≤30 ml. Thorough initial assessment using history, physical examination and basic investigations helped differentiate most of the underlying causes, which include diabetes mellitus, dehydration, sepsis, pre-eclampsia, shock, anaemia, obstructed labour, underlying cardiac or renal problems. A clinical algorithm was developed for each urinary abnormality to facilitate intrapartum management and referral of complicated cases for specialised care. Conclusions: Four simple, user-friendly and evidence-based clinical algorithms were developed to enhance intrapartum care of commonly encountered maternal urine abnormalities. These algorithms may be used to support healthcare professionals in clinical decision-making when handling normal and potentially complicated labour, especially in low resource countries. Tweetable abstract: Evidence-based clinical algorithms developed to guide intrapartum management of commonly encountered urinary abnormalities.