Evidence map›Paper›PMID 35148791›Full record

ArticleGlobal health research and policy2022

Assessment and validation of the Community Maternal Danger Score algorithm.

Rajan Bola, Fanan Ujoh, Ugochinyere Vivian Ukah, Ronald Lett

Abstract read
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Article in Global health research and policy, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Rajan BolaCanadian Network for International Surgery, #212-1650 Duranleau St, Vancouver, BC, V6H 3S4, Canada. rbola98@gmail.com.ORCID 0000-0002-7854-3967
Fanan UjohCanadian Network for International Surgery, #212-1650 Duranleau St, Vancouver, BC, V6H 3S4, Canada.
Ugochinyere Vivian UkahCanadian Network for International Surgery, #212-1650 Duranleau St, Vancouver, BC, V6H 3S4, Canada.
Ronald LettCanadian Network for International Surgery, #212-1650 Duranleau St, Vancouver, BC, V6H 3S4, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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 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.

methodsTo 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.

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), 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.

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 assessment and encourage pregnant women to seek an SBA in preparation for delivery, thus improving care in countries with high rates of maternal mortality.

Indexed as

MidwiferyPre-EclampsiaAdultAlgorithmsCesarean SectionFemaleHumansMaternal MortalityPregnancyYoung AdultAntenatal careLMICMaternal mortalityNigeriaRisk analysisSkilled birth attendants

Identifiers

PMID35148791
PMCPMC8832636

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.