Impact of malaria during pregnancy on pregnancy outcomes in a Ugandan prospective cohort with intensive malaria screening and prompt treatment

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Study Justification:
– Malaria in pregnancy (MiP) is a major public health problem in sub-Saharan Africa.
– Additional evidence is needed to understand how best to control malaria and its impact on pregnancy outcomes.
– This study aimed to identify factors associated with increased risk of MiP and analyze how various characteristics of MiP affect delivery outcomes.
Study Highlights:
– The study followed a prospective cohort of 1,218 pregnant women in Uganda.
– Intensive malaria screening and prompt treatment were provided to the participants.
– The study found that the timing, parasitaemia level, and number of malaria infections were associated with adverse birth outcomes.
– Prompt malaria detection and treatment should be offered to pregnant women regardless of symptoms or other preventive measures used during pregnancy.
– Increased focus on mothers living in remote areas is recommended.
Study Recommendations for Lay Reader:
– Pregnant women should be screened for malaria regularly and receive prompt treatment.
– Malaria infections during pregnancy can lead to adverse birth outcomes, such as low birth weight and preterm delivery.
– Pregnant women living in remote areas should receive extra attention and support to prevent and treat malaria.
Study Recommendations for Policy Maker:
– Implement and strengthen malaria screening and treatment programs for pregnant women.
– Provide resources and support to ensure regular and accessible malaria screening and treatment services in remote areas.
– Promote awareness and education about the importance of malaria prevention and treatment during pregnancy.
Key Role Players:
– Healthcare providers: to conduct regular malaria screening and provide prompt treatment.
– Community health workers: to educate and raise awareness about malaria prevention and treatment.
– Government health departments: to allocate resources and support for malaria control programs.
– Non-governmental organizations: to provide funding and support for malaria prevention and treatment initiatives.
Cost Items for Planning Recommendations:
– Training and capacity building for healthcare providers and community health workers.
– Procurement and distribution of malaria testing kits and antimalarial drugs.
– Awareness campaigns and educational materials.
– Monitoring and evaluation of malaria control programs.
– Infrastructure and logistics for delivering malaria screening and treatment services in remote areas.

The strength of evidence for this abstract is 8 out of 10.
The evidence in the abstract is strong because it is based on a prospective cohort study with a large sample size. The study followed pregnant women who had access to intensive malaria screening and prompt treatment, and analyzed various characteristics of malaria in pregnancy and their effects on delivery outcomes. The study also conducted multivariate analyses to assess the association between mothers’ characteristics and malaria risk, as well as between malaria in pregnancy and birth outcomes. The study provides important insights into the risk factors and consequences of malaria in pregnancy. To improve the evidence, it would be helpful to provide more details on the methods used for malaria screening and treatment, as well as the statistical analyses performed. Additionally, including information on the representativeness of the study population and any potential limitations of the study would further strengthen the evidence.

Background: Malaria in pregnancy (MiP) is a major public health problem in endemic areas of sub-Saharan Africa and has important consequences on birth outcome. Because MiP is a complex phenomenon and malaria epidemiology is rapidly changing, additional evidence is still required to understand how best to control malaria. This study followed a prospective cohort of pregnant women who had access to intensive malaria screening and prompt treatment to identify factors associated with increased risk of MiP and to analyse how various characteristics of MiP affect delivery outcomes. Methods. Between October 2006 and May 2009, 1,218 pregnant women were enrolled in a prospective cohort. After an initial assessment, they were screened weekly for malaria. At delivery, blood smears were obtained from the mother, placenta, cord and newborn. Multivariate analyses were performed to analyse the association between mothers’ characteristics and malaria risk, as well as between MiP and birth outcome, length and weight at birth. This study is a secondary analysis of a trial registered with ClinicalTrials.gov, number NCT00495508. Results: Overall, 288/1,069 (27%) mothers had 345 peripheral malaria infections. The risk of peripheral malaria was higher in mothers who were younger, infected with HIV, had less education, lived in rural areas or reported no bed net use, whereas the risk of placental infection was associated with more frequent malaria infections and with infection during late pregnancy. The risk of pre-term delivery and of miscarriage was increased in mothers infected with HIV, living in rural areas and with MiP occurring within two weeks of delivery.In adjusted analysis, birth weight but not length was reduced in babies of mothers exposed to MiP (-60g, 95%CI: -120 to 0 for at least one infection and -150 g, 95%CI: -280 to -20 for >1 infections). Conclusions: In this study, the timing, parasitaemia level and number of peripherally-detected malaria infections, but not the presence of fever, were associated with adverse birth outcomes. Hence, prompt malaria detection and treatment should be offered to pregnant women regardless of symptoms or other preventive measures used during pregnancy, and with increased focus on mothers living in remote areas. © 2013 De Beaudrap et al.; licensee BioMed Central Ltd.

The study was conducted in Mbarara district, southwestern Uganda. This predominantly rural area lies at an altitude of about 1,500 m above sea level and has moderate levels of malaria transmission [32]. Between October 2006 and May 2009, 1,218 pregnant women with an estimated gestational age ≥13 weeks were enrolled in a prospective observational cohort. The first 1197 women in this cohort screened for malaria with a positive rapid diagnostic test (RDT) confirmed by a positive blood smear were invited to participate in an additional study comparing the efficacy and tolerance of artemether–lumefantrine with oral quinine for the treatment of uncomplicated falciparum malaria published elsewhere [33]. At baseline, a comprehensive assessment of the pregnant women’s socio-demographic characteristics and health status was performed, including a medical and obstetrical history, clinical and obstetric examination, ultrasound evaluation, blood smear and hemoglobin measurement. Estimated gestational age by was determined by ultrasound in all women enrolled in the study between week 16–20 of pregnancy (72% of the cohort). For the remaining mothers, i.e., those recruited after the 20th week of gestation, we turned to a published model that predicts gestational age from symphysis-fundal height (SFH) measurements and calibrated it using the data from the 16–20 week group [34], and then used these results to predict gestational age at delivery in the subset of mothers without ultrasound (Additional file 1). After this initial assessment, the mothers returned to the clinic weekly for a clinical examination and malaria RDT. In case of positive RDT, malarial infection was confirmed with a blood smear. Treatment of uncomplicated falciparum malaria included a random allocation of artemether-lumefantrine for three days or quinine for seven days. Infections with only Plasmodium vivax were treated with chloroquine. All women in the cohort received standard supervised IPT with two doses of SP given at intervals of one month or more during the second and third trimesters, as well as iron and folate supplementation, antihelmintic treatment and insecticide-treated bed nets (ITN). All treatments were provided free-of-charge. At delivery, blood smears were obtained from the mother, placenta, cord and newborn to test for the presence of Plasmodium and malaria pigment. Placental histology was available only for a subset of the cohort (n=260). Placental malaria cases were classified according to the presence of parasitized erythrocytes, intervillous inflammation and haemozoin deposition [18,35]. Newborns were given an initial standardized physical examination by a medical officer, weighed to the nearest 10g using a SECA mechanical type scale, and measured for length to the nearest centimeter using a portable stadiometer (Shorr productions, US). Infants delivered outside of a health facility were examined within 24 hours of birth by a study medical officer. Paracheck® RDTs were performed using a finger-prick blood sample and interpreted according to the manufacturer’s instructions. Thick and thin blood smears were prepared and stained with Giemsa. Parasitaemia was calculated by counting parasites against 200 white blood cells (or 500, if nine parasites or fewer were counted against 200 white blood cells). Placental smears were taken by incising a fresh placenta on the maternal surface halfway between the cord and the periphery, and were then examined for the presence of parasites and pigment [35]. HIV testing and treatment was proposed to all participants and performed according to national guidelines [36], which include cotrimoxazole prophylaxis for people infected with HIV. Haemoglobin was measured from a fingerprick sample by the Haemocue B-Haemoglobin analyzer (Ängelholm, Sweden). Low birth weight was defined as <2,500 g measured within 24 hours of birth; preterm as newborn gestational age <37 weeks at delivery; stillbirth as the delivery of a non-living foetus ≥28 weeks gestation; and miscarriage as the delivery of a non-viable foetus either at <28 weeks gestation or weighing <500 g. Various parameters of malaria exposure during pregnancy were described and analysed for their temporal change and for their association with maternal characteristics or study interventions that may have affected MiP characteristics. Peripheral malaria was defined as the occurrence of a positive peripheral blood smear. After a treated malaria episode, a subsequent episode was considered a recurrence only after a minimum of 14 days, with at least one negative blood smear during this period [10]. Placental malaria was defined as the detection by microscopy of any parasite in a placental or cord blood smear. The risk of peripheral malaria infection was analysed with a mixed-effects Poisson model [37,38]. Since the occurrence of malaria before enrolment in the study could not be observed (left censoring), the at-risk time period was defined as the interval from study enrolment to delivery. Lead time bias was (partially) accounted for by including the gestational age at enrolment as a covariate. Each individual follow-up (from enrollment to delivery) was split into intervals elapsing from one visit to another, and the log duration of these intervals was included as an offset. Baseline risk was modeled using a spline function. The level of parasitaemia (log transformed) was analysed using a linear model. When more than one malaria episode was observed in a pregnancy, the maximal parasitaemia level recorded per episode was used as a dependent variable. The presence of fever and the occurrence of placental malaria infection were analysed with logistic models. In each model, maternal age, gravidity, HIV status, education level, residency area (rural versus urban), and gestational age at inclusion were considered as potential risk factors. The number of IPT doses was introduced as a time-dependent covariate in the model for peripheral malaria risk. However, IPT was interrupted after the treatment of a malaria infection, making the number of IPT doses an endogenous variable [39]. Since data were censored at the first malaria episode, only the relationship between the number of IPT doses received up to the beginning of a time interval and the risk of the first malaria episode during this time interval was assessed (using a log-linear model). The adverse outcomes evaluated in this study were stillbirth, preterm delivery, low birth weight and IUGR. IUGR was defined as a birth weight below the 10th percentile of the birth weight-for-gestational age. Type I (symmetric) IUGR and type II (asymmetric) IUGR were distinguished according to whether the Rohrer index was above the 10th percentile of Rohrer index for gestational age or not. United States population-based references were used as standard [40,41]. The association of each outcome with the various parameters of malaria exposure and with maternal characteristics were analysed separately for the full cohort, the subset of mother–newborn pairs with no or only one peripheral malaria infection, and the subset of mother–newborn pairs with ultrasound assessment of gestational age at baseline. Maternal age, education level (no education, primary level or ≥secondary level), residence area (rural versus urban), HIV status, number of clinic follow-up visits before birth outcome (<4 versus ≥4), and the newborn’s gender and gestational age at birth were included in all models. Stillbirth was analysed as a binary variable using a logistic model. Preterm delivery was analysed with gestational age at birth included as a continuous or binary variable (gestational age 6 log parasites/μL). Late malaria infection was defined as a peripheral malaria infection occurring in the last two weeks before delivery. To better understand the effect of malaria infection timing independently of the enrolment timing, the association between birth weight and gestational age at infection (<15, 15-<20, 20-<24, ≥24 weeks) was analysed with a linear model restricted to the subset of mothers with no or only one malaria infection and with a gestational age <15 weeks at enrolment. All analyses were performed using the open source statistical software R [42]. Written informed consent for study participation was obtained from all participants to the study. The study was approved by the institutional review boards of Mbarara University of Science and Technology, Uganda National Council for Science and Technology, and France’s “Comité de Protection des Personnes – Ile-de-France XI”. This study was registered with ClinicalTrials.gov, number {"type":"clinical-trial","attrs":{"text":"NCT00495508","term_id":"NCT00495508"}}NCT00495508.

Based on the information provided, here are some potential innovations that can be used to improve access to maternal health:

1. Intensive Malaria Screening and Prompt Treatment: Implementing a comprehensive malaria screening program for pregnant women, including regular testing and prompt treatment, can help reduce the risk of malaria during pregnancy and improve birth outcomes.

2. Education and Awareness Campaigns: Conducting educational campaigns to raise awareness about the importance of prenatal care, including malaria prevention and treatment, can help improve access to maternal health services.

3. Mobile Health (mHealth) Solutions: Utilizing mobile technology to provide information, reminders, and support to pregnant women, such as sending SMS messages with health tips, appointment reminders, and medication reminders, can help improve access to maternal health services, especially in remote areas.

4. Community Health Workers: Training and deploying community health workers to provide prenatal care, including malaria prevention and treatment, in rural and remote areas can help improve access to maternal health services for women who may have limited access to healthcare facilities.

5. Integration of Services: Integrating maternal health services with other existing healthcare programs, such as HIV/AIDS prevention and treatment programs, can help improve access to comprehensive care for pregnant women, addressing multiple health needs simultaneously.

6. Telemedicine: Implementing telemedicine services, such as remote consultations and monitoring, can help improve access to maternal health services for women who may have limited access to healthcare facilities or live in areas with a shortage of healthcare providers.

7. Financial Support: Providing financial support, such as subsidies or conditional cash transfers, to pregnant women for accessing maternal health services, including malaria prevention and treatment, can help reduce financial barriers and improve access to care.

8. Strengthening Healthcare Infrastructure: Investing in improving healthcare infrastructure, including the availability of healthcare facilities, trained healthcare providers, and essential medical supplies, can help ensure that pregnant women have access to quality maternal health services.

9. Partnerships and Collaboration: Collaborating with local communities, non-governmental organizations, and international partners to develop and implement innovative strategies for improving access to maternal health services can help leverage resources and expertise to achieve better outcomes.

10. Research and Data Collection: Conducting further research and data collection on the impact of malaria during pregnancy and the effectiveness of different interventions can help inform evidence-based policies and programs to improve access to maternal health.
AI Innovations Description
The recommendation that can be developed into an innovation to improve access to maternal health based on the study is to implement intensive malaria screening and prompt treatment for pregnant women. This recommendation is supported by the findings of the study, which showed that the timing, parasitaemia level, and number of malaria infections during pregnancy were associated with adverse birth outcomes.

By providing pregnant women with regular malaria screening and prompt treatment, the risk of malaria infection can be reduced, leading to improved birth outcomes. This intervention should be offered to all pregnant women, regardless of symptoms or other preventive measures used during pregnancy. Additionally, there should be increased focus on providing this intervention to mothers living in remote areas, as they may have limited access to healthcare services.

Implementing this recommendation as an innovation would involve establishing systems for regular malaria screening during prenatal visits and ensuring that prompt treatment is available and accessible to pregnant women. This could be done through training healthcare providers, improving diagnostic capabilities, and ensuring the availability of appropriate antimalarial medications. It would also be important to raise awareness among pregnant women about the importance of malaria screening and treatment during pregnancy.

Overall, implementing intensive malaria screening and prompt treatment for pregnant women has the potential to significantly improve access to maternal health and reduce the negative impact of malaria on birth outcomes.
AI Innovations Methodology
Based on the provided information, here are some potential recommendations for improving access to maternal health:

1. Increase access to intensive malaria screening and prompt treatment: This study showed that intensive malaria screening and prompt treatment significantly reduced the risk of adverse birth outcomes. Therefore, implementing similar programs in other areas with high malaria transmission rates could improve access to maternal health.

2. Improve education and awareness about malaria prevention: The study found that mothers with less education and those who reported no bed net use had a higher risk of peripheral malaria infection. Therefore, implementing educational programs to raise awareness about the importance of bed net use and other preventive measures could help reduce the risk of malaria during pregnancy.

3. Focus on mothers living in remote areas: The study highlighted the need for increased focus on mothers living in remote areas. These areas often have limited access to healthcare services, including malaria screening and treatment. Implementing mobile clinics or outreach programs specifically targeting these areas could help improve access to maternal health services.

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: Identify the specific population or region where the recommendations will be implemented. This could be a rural area with high malaria transmission rates and limited access to maternal health services.

2. Collect baseline data: Gather data on the current access to maternal health services, including malaria screening and treatment, in the target population. This could involve conducting surveys, interviews, or reviewing existing data.

3. Implement the recommendations: Introduce the recommended interventions, such as intensive malaria screening and prompt treatment, education and awareness programs, and targeted outreach to remote areas. Ensure that the interventions are implemented consistently and effectively.

4. Monitor and evaluate the impact: Continuously monitor the implementation of the recommendations and collect data on key indicators, such as the number of pregnant women accessing malaria screening and treatment, changes in malaria infection rates during pregnancy, and birth outcomes. Compare these data to the baseline data collected in step 2.

5. Analyze the data: Use statistical analysis to assess the impact of the recommendations on improving access to maternal health. This could involve comparing pre- and post-intervention data, conducting regression analyses, or using other appropriate statistical methods.

6. Draw conclusions and make recommendations: Based on the analysis of the data, draw conclusions about the effectiveness of the recommendations in improving access to maternal health. Identify any challenges or limitations encountered during the implementation process. Make recommendations for further improvements or modifications to the interventions based on the findings.

7. Disseminate the findings: Share the results of the impact assessment with relevant stakeholders, such as healthcare providers, policymakers, and community members. Use the findings to advocate for continued support and investment in initiatives to improve access to maternal health.

By following this methodology, it would be possible to simulate the impact of the recommendations on improving access to maternal health and make evidence-based decisions for future interventions.

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