Relationships between infection with Plasmodium falciparum during pregnancy, measures of placental malaria, and adverse birth outcomes NCT02163447 NCT

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Study Justification:
This study aimed to investigate the relationships between infection with Plasmodium falciparum during pregnancy, measures of placental malaria, and adverse birth outcomes. The justification for this study is that while malaria in pregnancy has been associated with maternal morbidity, placental malaria, and adverse birth outcomes, there is limited data on the relationships between longitudinal measures of malaria during pregnancy, measures of placental malaria, and birth outcomes. This study aimed to fill this knowledge gap and provide valuable information for the prevention and management of malaria in pregnant women.
Study Highlights:
– The study included 282 HIV-uninfected pregnant women enrolled at 12-20 weeks of gestation.
– Malaria burden during pregnancy was categorized into three groups: no malaria exposure, low malaria burden, and high malaria burden.
– Women with high malaria burden had increased risks of placental malaria and adverse birth outcomes compared to the other two groups.
– Detection of placental parasites was significantly associated with preterm birth and showed a trend towards increased risk for low birth weight and small for gestational age infants.
– The study highlights the importance of preventing and managing malaria during pregnancy to reduce the risk of adverse birth outcomes.
Study Recommendations:
Based on the findings of this study, the following recommendations can be made:
1. Implement strategies to prevent and control malaria in pregnant women, including the use of insecticide-treated bed nets and intermittent preventive therapy.
2. Strengthen antenatal care services to ensure early detection and treatment of malaria in pregnant women.
3. Improve access to diagnostic tools for the detection of placental malaria.
4. Enhance awareness and education among healthcare providers and pregnant women about the risks of malaria during pregnancy and the importance of preventive measures.
5. Conduct further research to explore interventions that can reduce the burden of placental malaria and improve birth outcomes.
Key Role Players:
1. Healthcare providers: Obstetricians, gynecologists, midwives, and nurses who provide antenatal care and manage pregnant women with malaria.
2. Public health officials: Responsible for developing and implementing policies and programs to prevent and control malaria in pregnant women.
3. Researchers: Conduct further studies to explore interventions and strategies to improve the prevention and management of malaria during pregnancy.
4. Policy makers: Develop and implement policies based on the study findings to improve the prevention and management of malaria in pregnant women.
Cost Items for Planning Recommendations:
1. Training and capacity building for healthcare providers: This includes workshops, seminars, and training programs to enhance their knowledge and skills in managing malaria in pregnant women.
2. Diagnostic tools: Procurement and maintenance of diagnostic tools for the detection of placental malaria, such as microscopy and loop-mediated isothermal amplification (LAMP) kits.
3. Antenatal care services: Investment in infrastructure, equipment, and staffing to strengthen antenatal care services and ensure early detection and treatment of malaria in pregnant women.
4. Education and awareness campaigns: Development and implementation of educational materials, campaigns, and outreach programs to raise awareness among healthcare providers and pregnant women about the risks of malaria during pregnancy and the importance of preventive measures.
5. Research funding: Allocation of funds for further research to explore interventions and strategies to improve the prevention and management of malaria during pregnancy.
Please note that the cost items provided are general categories and not actual cost estimates. The actual cost will depend on various factors such as the location, scale of implementation, and specific requirements of each recommendation.

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is relatively strong, but there are some areas for improvement. The study design is a nested observational study utilizing data from a randomized controlled trial, which provides a good level of evidence. The sample size of 282 participants is also adequate. The study measures various aspects of malaria during pregnancy, including symptomatic and asymptomatic malaria, placental malaria, and birth outcomes. The results show significant associations between higher malaria burden during pregnancy and placental malaria, as well as adverse birth outcomes. However, there are some limitations to consider. The abstract does not provide information on the statistical methods used for data analysis, which makes it difficult to assess the robustness of the findings. Additionally, the abstract does not mention any potential confounding factors that were controlled for in the analysis. To improve the evidence, it would be helpful to include more details on the statistical methods used and the control of confounding factors in the abstract.

Background: Malaria in pregnancy has been associated with maternal morbidity, placental malaria, and adverse birth outcomes. However, data are limited on the relationships between longitudinal measures of malaria during pregnancy, measures of placental malaria, and birth outcomes. Methods: This is a nested observational study of data from a randomized controlled trial of intermittent preventive therapy during pregnancy among 282 participants with assessment of placental malaria and delivery outcomes. HIV-uninfected pregnant women were enrolled at 12-20 weeks of gestation. Symptomatic malaria during pregnancy was measured using passive surveillance and monthly detection of asymptomatic parasitaemia using loop-mediated isothermal amplification (LAMP). Placental malaria was defined as either the presence of parasites in placental blood by microscopy, detection of parasites in placental blood by LAMP, or histopathologic evidence of parasites or pigment. Adverse birth outcomes assessed included low birth weight (LBW), preterm birth (PTB), and small for gestational age (SGA) infants. Results: The 282 women were divided into three groups representing increasing malaria burden during pregnancy. Fifty-two (18.4%) had no episodes of symptomatic malaria or asymptomatic parasitaemia during the pregnancy, 157 (55.7%) had low malaria burden (0-1 episodes of symptomatic malaria and < 50% of samples LAMP+), and 73 (25.9%) had high malaria burden during pregnancy (≥ 2 episodes of symptomatic malaria or ≥ 50% of samples LAMP+). Women with high malaria burden had increased risks of placental malaria by blood microscopy and LAMP [aRR 14.2 (1.80-111.6) and 4.06 (1.73-9.51), respectively], compared to the other two groups combined. Compared with women with no malaria exposure during pregnancy, the risk of placental malaria by histopathology was higher among low and high burden groups [aRR = 3.27 (1.32-8.12) and aRR = 7.07 (2.84-17.6), respectively]. Detection of placental parasites by any method was significantly associated with PTB [aRR 5.64 (1.46-21.8)], and with a trend towards increased risk for LBW and SGA irrespective of the level of malaria burden during pregnancy. Conclusion: Higher malaria burden during pregnancy was associated with placental malaria and together with the detection of parasites in the placenta were associated with increased risk for adverse birth outcomes. Trial Registration Current Controlled Trials Identifier NCT02163447

This was a cohort study that utilized data from a randomized controlled trial of IPTp in Tororo, Uganda. Tororo is a rural district in southeastern Uganda with an entomologic inoculation rate estimated at 310 infectious bites per person year in 2012 [11]. From June 2014 to October 2014, 300 pregnant women were enrolled into a three-arm, double-blinded, placebo-controlled trial of sulfadoxine-pyrimethamine (SP) given every 8 weeks versus dihydroartemisinin-piperaquine (DP) given every 8 weeks versus DP given every 4 weeks for IPTp. Details of the parent study have been described elsewhere [12]. Briefly, participants were HIV-negative pregnant women of at least 16 years of age, with an estimated gestational age of 12–20 weeks confirmed by ultrasound. For the present study, all 282 women from this cohort with placental histopathology and known birth outcomes were included. At enrollment, pregnant women underwent a standardized history and physical exam including assessment of wealth status, gravidity, gestational age by ultrasound, and age. Each participant received a long-lasting insecticide-treated bed net (LLIN). Women received all their medical care at a designated study clinic that was open daily. Routine visits were conducted every 4 weeks, including collection of dried blood spots (DBS) for LAMP. Participants with positive LAMP results were not treated for malaria. Women were also encouraged to present to the clinic with any illness. Patients who presented with a documented fever (tympanic temperature ≥ 38.0 °C) or a history of fever in the prior 24 h had peripheral blood collected for a thick blood smear. If the blood smear was positive, the patient was diagnosed with symptomatic malaria and treated with artemether–lumefantrine. At delivery, a standardized assessment was completed including evaluation of infant birth weight and gestational age, and collection of specimens within 1 h of delivery, including placental tissue, placental blood smears, and DBS of placental blood. All women were encouraged to deliver at the hospital adjacent to the study clinic. Women delivering at home were visited by study staff as close to the time of delivery as possible for assessment and sample collection. DBS were tested for the presence of malaria parasites using LAMP as previously described [13, 14]. Formalin-fixed paraffin-embedded placental biopsies were processed in duplicate for histological evidence of placental malaria using a standardized case record form by two independent readers as previously described [12]. A third reader resolved any discrepant results. Blood smears were stained with 2% Giemsa and read by two trained laboratory technicians. Smears were considered negative if no asexual parasites were detected in 100 high-powered fields. A third reviewer settled any discrepant readings. The following demographic data was collected: maternal age, possession of bed net at enrollment, wealth status, gravidity, gestational age, and IPTp treatment arm. Wealth status was categorized into lowest, middle, and highest tertiles designed as a composite variable using ownership of several household items and land. Gravidity was grouped as primigravidas (1st pregnancy) and multigravidas (≥ 2 pregnancies). Gestational age at enrollment was confirmed by ultrasound measurements by fetal biometry at less than 20 weeks’ gestation. IPTp treatment arm was categorized as SP given every 8 weeks, DP given every 8 weeks and DP given every 4 weeks. Malaria in pregnancy was defined as both symptomatic malaria and asymptomatic parasitaemia. Symptomatic malaria was measured using passive surveillance and defined as fever with positive blood smear. Asymptomatic parasitaemia was measured using active surveillance every 4 weeks and defined as molecular detection of malaria parasites from a DBS by LAMP. Measures of placental malaria at the time of delivery included: the detection of malaria parasites in placental blood by both microscopy and LAMP, and histopathologic evidence of placental malaria (parasites and/or pigment) from placental biopsies. Birth outcomes assessed included: LBW (< 2500 g), PTB (< 37 weeks gestational age), and SGA (birth weight < 10th percentile for gestational age according to East African fetal weight standards) [15]. In this study, an East African fetal weight standard was used because international growth standards (such as the Intergrowth-21st and the WHO growth curves) have shown greater variance of estimated fetal weight between countries, especially later in gestation [16, 17]. Utilizing the composite international standards above would have under- (Intergrowth-21st) or over-estimated (WHO) the incidence of SGA compared to the East African standards. There were eight cases of twin gestation; four were monochorionic–diamniotic and four were dichorionic–diamniotic. In these cases, outcomes were considered positive if present in at least one placenta and/or child. Data were double entered into a Microsoft Access database. Data analysis was done using Stata 14 (Stata Corp, College Station TX). For baseline characteristics, comparison of proportions was done using the χ2 test and the one way anova test for normally-distributed continuous variables. Generalized linear Poisson regression models with robust standard errors were used to investigate associations between a categorical measure of malaria burden during pregnancy and measures of placental malaria as well as associations between a composite measure of malaria in pregnancy and adverse birth outcomes. Associations were expressed as relative risks. Multivariate analyses included adjustment for which drug was given for IPTp and gravidity. All p values were two-sided and values of < 0.05 were considered statistically significant. Informed consent was obtained from all study participants. Ethical approval was obtained from the Uganda National Council of Science and Technology, the Makerere University School of Medicine Research and Ethics Committee, the Makerere University School of Biomedical Sciences Research and Ethics Committee, and the University of California, San Francisco, Committee on Human Research.

Based on the information provided, it seems that the study focused on the relationship between malaria during pregnancy, placental malaria, and adverse birth outcomes. To improve access to maternal health, here are some potential innovations that could be considered:

1. Mobile health (mHealth) interventions: Develop mobile applications or SMS-based systems to provide pregnant women with information about malaria prevention, symptoms, and treatment. This can help increase awareness and improve access to timely and accurate information.

2. Telemedicine services: Implement telemedicine services to enable pregnant women in remote or underserved areas to consult with healthcare providers remotely. This can help overcome geographical barriers and ensure access to prenatal care and malaria treatment.

3. Community health workers: Train and deploy community health workers to provide education, counseling, and basic healthcare services to pregnant women in their communities. These workers can play a crucial role in raising awareness about malaria prevention, conducting screenings, and referring women for appropriate care.

4. Integrated antenatal care: Integrate malaria prevention and treatment services into routine antenatal care visits. This can ensure that pregnant women receive comprehensive care and reduce the burden of accessing multiple healthcare services.

5. Point-of-care diagnostics: Develop and deploy rapid diagnostic tests for malaria that can be used at the point of care, such as in community clinics or at home. This can enable early detection and prompt treatment of malaria during pregnancy.

6. Supply chain management: Strengthen supply chain management systems to ensure the availability of essential antimalarial drugs, insecticide-treated bed nets, and other necessary commodities for malaria prevention and treatment during pregnancy.

7. Health education campaigns: Conduct targeted health education campaigns to raise awareness about the importance of malaria prevention during pregnancy. This can include community outreach programs, radio broadcasts, and educational materials in local languages.

8. Collaboration and partnerships: Foster collaboration and partnerships between government agencies, healthcare providers, researchers, and community organizations to collectively address the challenges of malaria in pregnancy and improve access to maternal health services.

These innovations can help improve access to maternal health by addressing barriers such as lack of information, limited healthcare infrastructure, and geographical constraints. It is important to adapt these recommendations to the specific context and needs of the target population.
AI Innovations Description
Based on the information provided, the recommendation to improve access to maternal health would be to implement a comprehensive malaria prevention and treatment program for pregnant women. This program should include the following components:

1. Intermittent Preventive Treatment in Pregnancy (IPTp): Provide regular doses of antimalarial medication, such as sulfadoxine-pyrimethamine (SP) or dihydroartemisinin-piperaquine (DP), to pregnant women to prevent malaria infection during pregnancy.

2. Long-lasting insecticide-treated bed nets (LLINs): Distribute LLINs to pregnant women to protect them from mosquito bites and reduce the risk of malaria transmission.

3. Active surveillance and early detection: Implement regular screening for malaria using loop-mediated isothermal amplification (LAMP) to detect asymptomatic parasitaemia. Treat positive cases promptly to prevent the progression of malaria infection.

4. Access to quality healthcare: Ensure that pregnant women have access to healthcare facilities that can provide comprehensive prenatal care, including regular check-ups, monitoring of malaria infection, and prompt treatment of complications.

5. Health education and awareness: Conduct community-based health education programs to raise awareness about the importance of malaria prevention during pregnancy and encourage pregnant women to seek early and regular prenatal care.

6. Collaboration and coordination: Foster collaboration between healthcare providers, researchers, and policymakers to ensure the effective implementation of the malaria prevention and treatment program. This includes sharing data, conducting research to evaluate the program’s impact, and making evidence-based policy decisions.

By implementing these recommendations, it is expected that access to maternal health will be improved, leading to a reduction in the incidence of placental malaria and adverse birth outcomes such as low birth weight, preterm birth, and small for gestational age infants.
AI Innovations Methodology
Based on the provided information, here are some potential recommendations for improving access to maternal health:

1. Increase availability and distribution of long-lasting insecticide-treated bed nets (LLINs) to pregnant women in high malaria burden areas. LLINs have been shown to be effective in reducing the risk of malaria infection during pregnancy.

2. Implement regular and systematic screening for malaria during pregnancy using loop-mediated isothermal amplification (LAMP) or other molecular detection methods. This can help identify asymptomatic parasitaemia and allow for timely treatment and management.

3. Strengthen antenatal care services by providing comprehensive and integrated care for pregnant women, including regular monitoring of maternal health, early detection and management of complications, and provision of appropriate interventions such as intermittent preventive therapy (IPTp) for malaria.

4. Improve access to skilled birth attendants and emergency obstetric care services to ensure safe deliveries and timely management of complications.

5. Enhance community engagement and awareness programs to educate pregnant women and their families about the importance of seeking antenatal care, adhering to recommended interventions, and recognizing danger signs during pregnancy.

To simulate the impact of these recommendations on improving access to maternal health, a methodology could be developed as follows:

1. Define the target population: Determine the specific population group or geographical area that will be the focus of the simulation.

2. Collect baseline data: Gather relevant data on the current status of maternal health access in the target population, including indicators such as antenatal care coverage, malaria prevalence, birth outcomes, and access to healthcare facilities.

3. Develop a simulation model: Create a mathematical or computational model that represents the target population and simulates the impact of the recommended interventions. The model should incorporate factors such as population demographics, healthcare infrastructure, disease transmission dynamics, and intervention coverage.

4. Define intervention scenarios: Specify different scenarios that represent the implementation of the recommended interventions. This could include variations in intervention coverage, timing, and intensity.

5. Run simulations: Use the simulation model to simulate the impact of each intervention scenario on access to maternal health. This could involve running multiple iterations of the model to capture the variability and uncertainty in the system.

6. Analyze results: Analyze the simulation results to assess the potential impact of the interventions on key outcomes such as antenatal care utilization, malaria prevalence, and birth outcomes. Compare the results of different intervention scenarios to identify the most effective strategies.

7. Validate and refine the model: Validate the simulation model by comparing the simulated results with real-world data, if available. Refine the model based on feedback and insights gained from the analysis.

8. Communicate findings: Present the findings of the simulation study in a clear and concise manner, highlighting the potential benefits of the recommended interventions in improving access to maternal health. This information can be used to inform policy decisions and guide the implementation of interventions in real-world settings.

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