Accuracy of the Community Maternal Danger Score Algorithm for Predicting Pregnant Women Requiring Skilled Birth Attendants and at High-risk for Mortality

Abstract

Abstract BackgroundHigh rates of maternal mortality in low-and-middle-income countries (LMICs) are associated with the lack of skilled birth attendants (SBAs) at delivery. Risk analysis tools may be useful to identify pregnant women who are at risk of mortality in LMICs. We sought to develop a low-cost maternal risk tool, the Community Maternal Danger Score (CMDS), to identify pregnant women who need an SBA at delivery.MethodsTo design the CMDS algorithm, an initial literature review was conducted to identify predictors of the need for an SBA. Medical records of women who delivered at the Federal Medical Centre in Makurdi, Nigeria (2019-2020) were examined for predictors identified from the literature review. Outcomes associated with the need for an SBA were recorded: caesarean section, postpartum hemorrhage, eclampsia, and sepsis. A maternal mortality ratio (MMR) was determined. Multivariate logistic regression analysis and area under the receiver operating curve (AUC) were used to assess the predictive ability of the CMDS algorithm.ResultsSeven factors from the literature predicted the need for an SBA: age (under 20 years of age or 35 and older), parity (nulliparity or grand-multiparity), BMI (underweight or overweight), fetal size (less than 35cm or 40cm and over), adverse obstetrical history, signs of pre-eclampsia, and co-existing medical conditions. These factors were recorded in 589 women of whom 67% required an SBA (n=396) and 1% died (n=7). The MMR was 1,189 per 100,000 (95%CI: 478-2,449). Signs of pre-eclampsia, obstetrical history, and co-existing conditions were highly associated with the need for an SBA. Age was found to interact with parity, suggesting that the CMDS requires adjustment for younger multigravida and older primigravida women. The CMDS algorithm had an AUC of 0.73 (95%CI: 0.69-0.77) for predicting whether women required an SBA, and an AUC of 0.85 (95%CI: 0.67-1.00) for in-hospital mortality.ConclusionsThe CMDS is a low-cost, evidence-based tool that uses 7 risk factors assessed on 589 women from Makurdi. Non-specialist health workers can use the CMDS to standardize patient assessment and encourage pregnant women to seek an SBA in preparation for delivery, thus improving care in countries with high rates of maternal mortality.