Dataset Information

A prospective cause of death classification system for maternal deaths in low and middle-income countries: results from the Global Network Maternal Newborn Health Registry.

ABSTRACT: OBJECTIVE:To describe the causes of maternal death in a population-based cohort in six low- and middle-income countries using a standardised, hierarchical, algorithmic cause of death (COD) methodology. DESIGN:A population-based, prospective observational study. SETTING:Seven sites in six low- to middle-income countries including the Democratic Republic of the Congo (DRC), Guatemala, India (two sites), Kenya, Pakistan and Zambia. POPULATION:All deaths among pregnant women resident in the study sites from 2014 to December 2016. METHODS:For women who died, we used a standardised questionnaire to collect clinical data regarding maternal conditions present during pregnancy and delivery. These data were analysed using a computer-based algorithm to assign cause of maternal death based on the International Classification of Disease-Maternal Mortality system (trauma, termination of pregnancy-related, eclampsia, haemorrhage, pregnancy-related infection and medical conditions). We also compared the COD results to healthcare-provider-assigned maternal COD. MAIN OUTCOME MEASURES:Assigned causes of maternal mortality. RESULTS:Among 158 205 women, there were 221 maternal deaths. The most common algorithm-assigned maternal COD were obstetric haemorrhage (38.6%), pregnancy-related infection (26.4%) and pre-eclampsia/eclampsia (18.2%). Agreement between algorithm-assigned COD and COD assigned by healthcare providers ranged from 75% for haemorrhage to 25% for medical causes coincident to pregnancy. CONCLUSIONS:The major maternal COD in the Global Network sites were haemorrhage, pregnancy-related infection and pre-eclampsia/eclampsia. This system could allow public health programmes in low- and middle-income countries to generate transparent and comparable data for maternal COD across time or regions. TWEETABLE ABSTRACT:An algorithmic system for determining maternal cause of death in low-resource settings is described.

SUBMITTER: Pasha O

PROVIDER: S-EPMC6298604 | biostudies-literature | 2018 Aug

REPOSITORIES: biostudies-literature

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A prospective cause of death classification system for maternal deaths in low and middle-income countries: results from the Global Network Maternal Newborn Health Registry.

Pasha O O McClure E M EM Saleem S S Tikmani S S SS Lokangaka A A Tshefu A A Bose C L CL Bauserman M M Mwenechanya M M Chomba E E Carlo W A WA Garces A L AL Figueroa L L Hambidge K M KM Krebs N F NF Goudar S S Kodkany B S BS Dhaded S S Derman R J RJ Patel A A Hibberd P L PL Esamai F F Tenge C C Liechty E A EA Moore J L JL Wallace D D DD Koso-Thomas M M Miodovnik M M Goldenberg R L RL

BJOG : an international journal of obstetrics and gynaecology 20180521 9

<h4>Objective</h4>To describe the causes of maternal death in a population-based cohort in six low- and middle-income countries using a standardised, hierarchical, algorithmic cause of death (COD) methodology.<h4>Design</h4>A population-based, prospective observational study.<h4>Setting</h4>Seven sites in six low- to middle-income countries including the Democratic Republic of the Congo (DRC), Guatemala, India (two sites), Kenya, Pakistan and Zambia.<h4>Population</h4>All deaths among pregnant w ...[more]

PMID: 29094456

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Project description:BackgroundDespite global improvements in maternal and newborn health (MNH), maternal, fetal and newborn mortality rates in Pakistan remain stagnant. Using data from the Global Network's Maternal Newborn Health Registry (MNHR) the objective of this study is to compare the rates of maternal mortality, stillbirth and newborn mortality and levels of putative risk factors between the Pakistani site and those in other countries.MethodsUsing data collected through a multi-site, prospective, ongoing, active surveillance system to track pregnancies and births in communities in discrete geographical areas in seven sites across six countries including Pakistan, India, Kenya, Zambia, Guatemala and Argentina from 2010 to 2013, the study compared MNH outcomes and risk factors. The MNHR captures more than 60,000 deliveries annually across all sites with over 10,000 of them in Thatta, Pakistan.ResultsThe Pakistan site had a maternal mortality ratio almost three times that of the other sites (313/100,000 vs 116/100,000). Stillbirth (56.5 vs 22.9/1000 births), neonatal mortality (50.0 vs 20.7/1000 livebirths) and perinatal mortality rates (95.2/1000 vs 39.0/1000 births) in Thatta, Pakistan were more than twice those of the other sites. The Pakistani site is the only one in the Global Network where maternal mortality increased (from 231/100,000 to 353/100,000) over the study period and fetal and neonatal outcomes remained stagnant. The Pakistan site lags behind other sites in maternal education, high parity, and appropriate antenatal and postnatal care. However, facility delivery and skilled birth attendance rates were less prominently different between the Pakistani site and other sites, with the exception of India. The difference in the fetal and neonatal outcomes between the Pakistani site and the other sites was most pronounced amongst normal birth weight babies.ConclusionsThe increase in maternal mortality and the stagnation of fetal and neonatal outcomes from 2010 to 2013 indicates that current levels of antenatal and newborn care interventions in Thatta, Pakistan are insufficient to protect against poor maternal and neonatal outcomes. Delivery care in the Pakistani site, while appearing quantitatively equivalent to the care in sites in Africa, is less effective in saving the lives of women and their newborns. By the metrics available from this study, the quality of obstetric and neonatal care in the site in Pakistan is poor.Trial registrationThe study is registered at clinicaltrials.gov [NCT01073475].

Project description:ImportanceThe emergence of acute neurological symptoms in children necessitates immediate intervention. Although low- and middle-income countries (LMICs) bear the highest burden of neurological diseases, there is a scarcity of diagnostic and therapeutic resources. Therefore, current understanding of the etiology of neurological emergencies in LMICs relies mainly on clinical diagnoses and verbal autopsies.ObjectiveTo characterize the association of premortem neurological symptoms and their management with postmortem-confirmed cause of death among children aged younger than 5 years in LMICs and to identify current gaps and improve strategies to enhance child survival.Design, setting, and participantsThis cross-sectional study was conducted between December 3, 2016, and July 22, 2022, at the 7 participating sites in the Child Health and Mortality Prevention Surveillance (CHAMPS) network (Bangladesh, Ethiopia, Kenya, Mali, Mozambique, Sierra Leone, and South Africa). Minimally invasive tissue sampling was performed at the CHAMPS sites with specimens from deceased children aged younger than 5 years. This study included deceased children who underwent a premortem neurological evaluation and had a postmortem-confirmed cause of death. Data analysis was performed between July 22, 2022, and January 15, 2023.Main outcomes and measuresDescriptive analysis was performed using neurological evaluations from premortem clinical records and from postmortem determination of cause of death (based on histopathology, microbiological testing, clinical records, and verbal autopsies).ResultsOf the 2127 deaths of children codified during the study period, 1330 (62.5%) had neurological evaluations recorded and were included in this analysis. The 1330 children had a median age of 11 (IQR, 2-324) days; 745 (56.0%) were male and 727 (54.7%) presented with neurological symptoms during illness before death. The most common postmortem-confirmed neurological diagnoses related to death were hypoxic events (308 [23.2%]), meningoencephalitis (135 [10.2%]), and cerebral malaria (68 [5.1%]). There were 12 neonates with overlapping hypoxic events and meningoencephalitis, but there were no patients with overlapping meningoencephalitis and cerebral malaria. Neurological symptoms were similar among diagnoses, and no combination of symptoms was accurate in differentiating them without complementary tools. However, only 25 children (18.5%) with meningitis had a lumbar puncture performed before death. Nearly 90% of deaths (442 of 511 [86.5%]) with neurological diagnoses in the chain of events leading to death were considered preventable.Conclusions and relevanceIn this cross-sectional study of children aged younger than 5 years, neurological symptoms were frequent before death. However, clinical phenotypes were insufficient to differentiate the most common underlying neurological diagnoses. The low rate of lumbar punctures performed was especially worrying, suggesting a challenge in quality of care of children presenting with neurological symptoms. Improved diagnostic management of neurological emergencies is necessary to ultimately reduce mortality in this vulnerable population.

Project description:BackgroundPhysician-coded verbal autopsy (PCVA) is the most widely used method to determine causes of death (CODs) in countries where medical certification of death is uncommon. Computer-coded verbal autopsy (CCVA) methods have been proposed as a faster and cheaper alternative to PCVA, though they have not been widely compared to PCVA or to each other.MethodsWe compared the performance of open-source random forest, open-source tariff method, InterVA-4, and the King-Lu method to PCVA on five datasets comprising over 24,000 verbal autopsies from low- and middle-income countries. Metrics to assess performance were positive predictive value and partial chance-corrected concordance at the individual level, and cause-specific mortality fraction accuracy and cause-specific mortality fraction error at the population level.ResultsThe positive predictive value for the most probable COD predicted by the four CCVA methods averaged about 43% to 44% across the datasets. The average positive predictive value improved for the top three most probable CODs, with greater improvements for open-source random forest (69%) and open-source tariff method (68%) than for InterVA-4 (62%). The average partial chance-corrected concordance for the most probable COD predicted by the open-source random forest, open-source tariff method and InterVA-4 were 41%, 40% and 41%, respectively, with better results for the top three most probable CODs. Performance generally improved with larger datasets. At the population level, the King-Lu method had the highest average cause-specific mortality fraction accuracy across all five datasets (91%), followed by InterVA-4 (72% across three datasets), open-source random forest (71%) and open-source tariff method (54%).ConclusionsOn an individual level, no single method was able to replicate the physician assignment of COD more than about half the time. At the population level, the King-Lu method was the best method to estimate cause-specific mortality fractions, though it does not assign individual CODs. Future testing should focus on combining different computer-coded verbal autopsy tools, paired with PCVA strengths. This includes using open-source tools applied to larger and varied datasets (especially those including a random sample of deaths drawn from the population), so as to establish the performance for age- and sex-specific CODs.

Project description:OBJECTIVES:The maternal near-miss case review (NMCR) has been promoted by WHO as an approach to improve quality of care (QoC) at facility level. This systematic review synthesises evidence on the effectiveness of the NMCR on QoC and maternal and perinatal health outcomes in low-income and middle-income countries (LMICs). METHODS:Studies were searched for in six electronic databases (MEDLINE, Index Medicus, Web of Science, the Cochrane library, Embase, LILACS), with no language restrictions. Two authors independently screened papers and selected them for inclusion and independently extracted data. Maternal mortality was the primary outcome. Secondary outcomes included any outcome informing on any of the six dimensions of QoC: efficacy, safety, efficiency, equity, accessibility and timely care, acceptability and patient-centred care. RESULTS:Out of 24?822 papers retrieved, 17 studies from 11 countries were included. Maternal mortality measured before and after the implementation of the NMCR cycle significantly decreased (OR 0.77, 95%?CI 0.61 to 0.98, eight studies, 55 573 043 women; I2=39%). A statistically significant reduction in the incidence of uterine rupture, postpartum haemorrhage and maternal sepsis was observed in three out of six studies. Ten studies reporting on maternal care process all showed some significant improvement when measured against predefined standards. All studies reported that the NMCR resulted in some amelioration of the facility structure (physical structure, staffing, equipment, training, organisation of care). Newborn outcomes were overall poorly reported; four studies showed no significant difference in perinatal mortality. Patient satisfaction and equity were also poorly reported. CONCLUSIONS:Policy makers may consider implementing the maternal NMCR cycle approach among strategies aiming at improving QoC and reducing maternal mortality and morbidity in LMIC. Future studies should better document the effectiveness of the NMCR cycle particularly on outcomes reflecting patient-centred care and cost-effectiveness.

Project description:IntroductionImproving reproductive, maternal, newborn, and child health (RMNCH) care services is imperative for reducing maternal and child mortality. Many low- and middle-income countries (LMICs) are striving to achieve RMNCH-related Sustainable Development Goals (SDGs). We monitored progress, made projections, and calculated the average annual rate of change needed to achieve universal (100%) access of RMNCH service indicators by 2030.MethodsWe extracted Demographic and Health Survey (DHS) data of 75 LMICs to estimate the coverage of RMNCH indicators and composite coverage index (CCI) to measure health system strengths. Bayesian linear regression models were fitted to predict the coverage of indicators and the probability of achieving targets.ResultsThe projection analysis included 64 countries with available information for at least 2 DHS rounds. No countries are projected to reach universal CCI by 2030; only Brazil, Cambodia, Colombia, Honduras, Morocco, and Sierra Leone will have more than 90% CCI. None of the LMICs will achieve universal coverage of all RMNCH indicators by 2030, although some may achieve universal coverage for specific services. To meet targets for universal service access by 2030, most LMICs must attain a 2-fold increase in the coverage of indicators from 2019 to 2030. Coverage of RMNCH indicators, the probability of target attainments, and the required rate of increase vary significantly across the spectrum of sociodemographic disadvantages. Most countries with poor historical and current trends for RMNCH coverage are likely to experience a similar scenario in 2030. Countries with lower coverage had higher disparities across the subgroups of wealth, place of residence, and women's/mother's education and age; these disparities are projected to persist in 2030.ConclusionNone of the LMICs will meet the SDG RMNCH 2030 targets without scaling up essential RMNCH interventions, reducing gaps in coverage, and reaching marginalized and disadvantaged populations.

Project description:As community engagement (CE) is implemented for sustainable maternal and newborn health (MNH) programming, it is important to determine how these approaches work. Low- and middle-income countries (LMICs) have become a particular focus for MNH CE activities due to their high burden of maternal and neonatal deaths. MNH messaging and communication to engage communities are likely to differ by context, but how these approaches are actually developed and implemented within CE is not well understood. Understanding how communications in CE actually work is vital in the translation of learnings across programmes and to inform future projects. The purpose of this realist review is to describe how, why, to what extent and for whom communications in CE contribute to MNH programming in LMICs. After searching academic databases, grey literature and literature suggested by the expert advisory committee, documents were included if they described the CE communication processes/activities used for MNH programming in an LMIC. Relevant documents were assessed for richness (depth of insight) and rigor (trustworthiness and coherence of data/theories). Data were extracted as context-mechanism-outcome configurations (CMOCs) and synthesized into demi-regularities to contribute to theory refinement. After screening 416 records, 45 CMOCs were extracted from 11 documents. This informed five programme theories explaining that communications in CE for an MNH programme work when: communities are actively involved throughout the programme, the messaging and programme are acceptable, communication sources are trusted, the community has a reciprocal relationship with the programme and the community sees value in the programme. While these findings reflect what is often anecdotally known in CE or acknowledged in communications theory, they have implications for policy, practice and research by highlighting the importance of centring the community's needs and priorities throughout the stages of developing and implementing communications for CE in MNH.

Dataset Information

A prospective cause of death classification system for maternal deaths in low and middle-income countries: results from the Global Network Maternal Newborn Health Registry.

Publications

A prospective cause of death classification system for maternal deaths in low and middle-income countries: results from the Global Network Maternal Newborn Health Registry.

Similar Datasets

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