Maternal Mortality Risk Factors in Regional Hospital of Burkina Faso

Savadogo, Léon G. Blaise; Zombra, Aminata; Tamini, Cécile; Kinda, Moumouni; Donnen, Philipe

doi:10.4236/ojepi.2014.42010

Cited by 6 publications

(10 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…[22][23] Furthermore, patients with an obstetrical history of any of: previous hemorrhage, 24 previous stillbirth or miscarriage, 25 previous breech delivery, 26 previous twins (or more), 27 previous pregnancy within 1.5 years or greater than 5 years ago, 28 and reported reduction in fetal movements 22 were grouped as: high risk (1 of these conditions) or extremely high risk (2 or more of these conditions). Co-existing conditions (maternal sepsis, 29 fever with ruptured membranes, 30 human immunode ciency virus (HIV), 24,31 anemia, 31 tuberculosis, 31 female genital mutilation, [32][33] diabetes, 29 and malaria 23,31 ) were also recorded on 2-levels (high risk and extremely high risk) based on the number and type of conditions the woman presented with (Table 1). Pre-eclampsia is a common cause of maternal mortality 34 and is classi ed as a risk factor based on two ndings: by the mother's blood pressure and by other signs that could indicate this condition.…”

Section: Cmds Domainsmentioning

confidence: 99%

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

Bola

Ujoh

Ukah

et al. 2021

Preprint

View full text Add to dashboard Cite

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.

show abstract

Section: Cmds Domainsmentioning

confidence: 99%

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

Bola

Ujoh

Ukah

et al. 2021

Preprint

View full text Add to dashboard Cite

show abstract

“…Women from this retrospectively assessed cohort with up to 1 matching risk factor were considered low risk, women with 2 matching factors were considered high risk, and women with 3 factors were considered extremely high risk. [27][28][29][30] The absolute proportion of women at risk was also assessed. All PHC data was categorized using de nitions incorporated by the CMDS.…”

Section: Data Sourcesmentioning

confidence: 99%

“…26 These risk factors include age, 27 parity, 28 and co-existing medical conditions (human immunode ciency virus (HIV) and diabetes). [29][30]…”

Section: Introductionmentioning

confidence: 99%

Identification and Mitigation of High-Risk Pregnancy with the Community Maternal Danger Score Mobile Application in Gboko, Nigeria

Bola

Ujoh

Lett

2021

Preprint

View full text Add to dashboard Cite

Introduction Nigeria constitutes 1% of the world’s population yet accounts for 10% of global maternal mortality. Risk analyses within rural regions of Nigeria are not routinely conducted, yet could help inform access to skilled birth care. The objectives of this study were to assess the proportion of women at risk for mortality or morbidity in Benue State, Nigeria by analysing data collected during routine antenatal visits and through the Community Maternal Danger Score (CMDS), a validated risk-analysis tool. Methods Two cohorts, comprised of pregnant women presenting to primary healthcare centres within Gboko, Benue State between 2015-2017 and 2020-2021, were included in this study. The 2015-2017 cohort had their risk assessed retrospectively through analysis of routinely collected data. Identification of risk was based on their age, parity, and disease status (HIV and diabetes). The 2020-2021 cohort had their risk assessed prospectively using the CMDS. Results Routinely collected data from 2015-2017 demonstrated that up to 14.9% of women in Gboko were at risk for mortality or morbidity. The CMDS reported that up to 21.5% of women were at a similar level of risk; a significant difference of 6.6% (p=0.006). The CMDS was more efficient in obtaining and assessing this data, and the identification was available in real-time for midwives and pregnant women. Conclusion Routine data collected in Gboko identifies a high proportion of pregnant women at risk for mortality or morbidity. The CMDS is an evidence-based risk analysis tool that expands on this assessment by also estimating individual and community-level risk, which allows for more efficient mitigation and prevention strategies of maternal mortality.

show abstract

“…Adapun faktor pelayanan kesehatan disebabkan oleh belum mantapnya jangkauan pelayanan KIA dan penanganan kelompok berisiko, masih rendahnya cakupan Ante Natal Care dan pertolongan persalinan oleh tenaga kesehatan, keterlambatan penanganan adekuat, akses pelayanan kesehatan (jarak, biaya, waktu dan transportasi) yang tidak terjangkau. 3 4,5 Penelitian ini juga menunjukkan bahwa ibu yang mengalami komplikasi persalinan memiliki risiko mengalami kematian maternal 9,533 kali lebih besar dibandingkan dengan ibu yang tidak mengalami komplikasi persalinan, dengan nilai p 0,001<0,05 (OR = 9,533; 95% CI : 2,397 -37,909) ini sesuai dengan penelitian yang dilakukan oleh Astuti bahwa komplikasi persalinan memiliki risiko 5,083 kali terhadap kematian maternal, Muthoharoh tingkat risiko komplikasi dengan kematian maternal sebesar 4,233 kali. 4,6 Demikian juga dengan komplikasi nifas,penelitian ini menunjukkan bahwa ibu yang mengalami komplikasi nifas memiliki pengaruh bermakna terhadap kematian maternal dengan nilai p0,000 <0,05.…”

Section: Pendahuluanunclassified

Analisis Faktor Determinan Kematian Ibu di Kabupaten Sukoharjo Jawa Tengah Indonesia

Respati¹,

Sulistyowati²,

Nababan³

2019

Jurnal Kespro

View full text Add to dashboard Cite

LatarBelakang: Kematian ibu di kabupaten Sukoharjo masih cukup tinggi. Hal ini disebabkan oleh beberapa faktor seperti 4 “terlalu” ,komplikasi kehamilan, persalinan dan nifas,terlambat mengambil keputusan, merujuk dan mendapat pelayanan kesehatanserta sosioal ekonomi yang rendah.Metode: Observasional analitik dengan case control study. Jumlah sampel 16 kasus dan 32 kontrol dengan teknik simple random sampling. Analisis dilakukan secara univariat, bivariat dengan chi square test, multivariat dengan metode regresi logistik.Hasil: Terdapat hubungan yang bermakna antara komplikasi kehamilan (p<0.034) (OR=4,200; 95% CI : 1,064 – 16,584), komplikasi persalinan (p<0.001) (OR=9,533; 95% CI : 2,397 – 37,909), komplikasi nifas (p<0.000), keterlambatan penanganan petugas (p=0,011),paritas (OR=0,035; 95% CI : 0,004 – 0,300; p=0,000) dan ibu bekerja (p=0,017)(OR=4.592; 95% CI : 1.257 – 16.771) terhadap kematian maternal. Dengan faktor risiko di atas kemungkinan kematian maternal meningkat sebanayak 88,9 %.Kesimpulan: Komplikasi kehamilan, persalinan, nifas ,keterlambatan penanganan petugas, paritas dan ibu bekerja meningkatkan risiko kematian maternal

show abstract

Maternal Mortality Risk Factors in Regional Hospital of Burkina Faso

Cited by 6 publications

References 15 publications

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

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

Identification and Mitigation of High-Risk Pregnancy with the Community Maternal Danger Score Mobile Application in Gboko, Nigeria

Analisis Faktor Determinan Kematian Ibu di Kabupaten Sukoharjo Jawa Tengah Indonesia

Contact Info

Product

Resources

About