Assessment and validation of the Community Maternal Danger Score algorithm.
Journal article
Bola, R., Ujoh, F., Ukah, U.V. and Lett, R. (2022). Assessment and validation of the Community Maternal Danger Score algorithm. Global health research and policy. 7 (1), p. 6. https://doi.org/10.1186/s41256-022-00240-8
| Authors | Bola, R., Ujoh, F., Ukah, U.V. and Lett, R. |
|---|---|
| Abstract | <h4>Background</h4>High 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 and validate a low-cost maternal risk tool, the Community Maternal Danger Score (CMDS), which is designed to identify pregnant women who need an SBA at delivery.<h4>Methods</h4>To design the CMDS algorithm, an initial scoping 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 curve (AUC) were used to assess the predictive ability of the CMDS algorithm.<h4>Results</h4>Seven 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), fundal height (less than 35 cm or 40 cm 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 1189 per 100,000 (95% CI 478-2449). Signs of pre-eclampsia, obstetrical history, and co-existing conditions were associated with the need for an SBA. Age was found to interact with parity, suggesting that the CMDS requires adjustment to indicate higher risk among 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.<h4>Conclusions</h4>The 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 assessment and encourage pregnant women to seek an SBA in preparation for delivery, thus improving care in countries with high rates of maternal mortality. |
| Keywords | Risk analysis; Maternal mortality; Nigeria; Antenatal Care; Skilled Birth Attendants; Lmic |
| Year | 2022 |
| Journal | Global health research and policy |
| Journal citation | 7 (1), p. 6 |
| Publisher | BMC |
| ISSN | 2397-0642 |
| Digital Object Identifier (DOI) | https://doi.org/10.1186/s41256-022-00240-8 |
| Publication dates | |
| Online | 11 Feb 2022 |
| Publication process dates | |
| Accepted | 03 Nov 2022 |
| Deposited | 18 Mar 2022 |
| Publisher's version | License File Access Level Open |
| License | CC BY |
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