Malaria and Fetal Growth Alterations in the 3rd Trimester of Pregnancy: A Longitudinal Ultrasound Study

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Study Justification:
This study aimed to investigate the impact of malaria infection on fetal growth during the 3rd trimester of pregnancy using trans-abdominal ultrasound. The study is important because although pregnancy-associated malaria is known to be associated with decreased birth weight, there is limited research on in-utero evaluation of fetal growth alterations. Understanding the effects of malaria on fetal growth can help inform strategies for protecting pregnant women against malaria and improving birth outcomes.
Highlights:
– The study included 876 pregnant women in Tanzania and monitored fetal growth using ultrasound.
– Malaria infection only affected birth weight and fetal growth among primi- and secundigravid women.
– Among primi- and secundigravidae, 58% had malaria in the first half of pregnancy, but the effect on fetal growth was observed in the 3rd trimester.
– Different patterns of fetal growth alterations were observed, with some women experiencing immediate or persistent effects on growth.
– The study highlights the need for protection against malaria throughout pregnancy and suggests that observed changes in fetal growth may be a consequence of an infection much earlier in pregnancy.
Recommendations:
– Pregnant women should be protected against malaria throughout pregnancy to minimize the risk of fetal growth alterations.
– Regular screening for malaria should be conducted during pregnancy to detect and treat infections promptly.
– Further research is needed to understand the mechanisms by which malaria infection affects fetal growth and to develop targeted interventions.
Key Role Players:
– Researchers and scientists in the field of maternal and child health
– Obstetricians and gynecologists
– Public health officials and policymakers
– Healthcare providers and midwives
– Community health workers and educators
Cost Items for Planning Recommendations:
– Malaria screening tests and diagnostic tools
– Antimalarial medications for treatment and prevention
– Ultrasound equipment and trained personnel for fetal growth monitoring
– Training and capacity building for healthcare providers
– Health education and awareness campaigns for pregnant women and communities
– Transportation and logistics for accessing healthcare facilities
– Data management and analysis tools and resources

The strength of evidence for this abstract is 8 out of 10.
The evidence in the abstract is strong because it is based on an observational study of 876 pregnant women and includes multiple statistical analyses. However, to improve the evidence, the study could have included a control group of pregnant women without malaria to compare the effects on fetal growth. Additionally, the abstract could have provided more information on the methodology and limitations of the study.

Background: Pregnancy associated malaria is associated with decreased birth weight, but in-utero evaluation of fetal growth alterations is rarely performed. The objective of this study was to investigate malaria induced changes in fetal growth during the 3rd trimester using trans-abdominal ultrasound. Methods: An observational study of 876 pregnant women (398 primi- and secundigravidae and 478 multigravidae) was conducted in Tanzania. Fetal growth was monitored with ultrasound and screening for malaria was performed regularly. Birth weight and fetal weight were converted to z-scores, and fetal growth evaluated as fetal weight gain from the 26th week of pregnancy. Results: Malaria infection only affected birth weight and fetal growth among primi- and secundigravid women. Forty-eight of the 398 primi- and secundigravid women had malaria during pregnancy causing a reduction in the newborns z-score of -0.50 (95% CI: -0.86, -0.13, P = 0.008, multiple linear regression). Fifty-eight percent (28/48) of the primi- and secundigravidae had malaria in the first half of pregnancy, but an effect on fetal growth was observed in the 3rd trimester with an OR of 4.89 for the fetal growth rate belonging to the lowest 25% in the population (95%CI: 2.03-11.79, P6 months, and willing to give birth at KDH. Women with preeclampsia and/or twins in the current pregnancy, and fetuses/newborns with severe malformations were excluded from the analysis, since these conditions can severely affect fetal growth [32], [33]. In analyses including BW, stillbirths were omitted. Sensitization campaigns were performed in the villages to reduce selection bias. After inclusion, women were booked for three antenatal visits (ANV) at a GA of 26 (ANV2), 30 (ANV3), and 36 (ANV4) weeks. If needed due to illness women attended extra clinic visits. Maternal age, anthropometric measures, obstetric history, educational level (≤primary school; ≥secondary school), HIV status, and hemoglobin level (Sysmex hematological analyzer®, Kobe, Japan) were documented. The project team performed all investigations except screening for maternal HIV infection which governmental nurses performed only three days a week. Women not completing follow-up were therefore less likely to have their HIV status determined. Transport was offered at the time of delivery and 77.2%, 5.3%, and 17.6% delivered at KDH, another health facility, and at home, respectively. Home visits were performed within one week of the bookings or the estimated date of delivery, if women failed to report at KDH. At all visits venous blood was collected and at delivery both venous and placental blood. Malaria was diagnosed using rapid diagnostic test (RDT) (Parascreen™ Zephyr Biomedicals, Goa, India, Paracheck Pf® Orchid Biomedical Systems, Goa, India or ParaHIT® Span diagnostics Ltd, Surat, India) [34]. Thick and thin blood smears were prepared and evaluated at the end of the study. Women were therefore treated based on the RDT results with Artemether-Lumefantrine (Coartem® Dispersible, Norvatis Corporation Suffern, New York, USA) or Quinine (Quinine sulfate coated tablets, ELYS chemical Industries Ltd, Nairobi, Kenya) (infections occurring in 1st trimester). Women with symptoms or sign of malaria had an immediate blood smear investigation in addition to the RDT. Infections requiring hospital admission were treated with Quinine (Quinine Dihydrochloride Injection BP, Healthcare PVT Ltd, Mumbai India). RDT positive women, who had been RDT positive within two weeks before the ANV, also had an immediate blood smear examination. Parasite HRP-2 antigen can circulate in the blood stream after clearance of the malaria parasites, and only women who were consistently blood smear positive were treated [35]. Blood smears were stained with Giemsa, and asexual parasites counted against 200 (500 if parasite count was <10) leucocytes. One hundred thick film fields were read before a slide was declared negative. The malaria infection was considered symptomatic if the axillary temperature was above 37.5C. Intermittent preventive treatment for malaria (IPTp) with sulfadoxine-pyrimethamine (1500 mg/75 mg) (SULPHADAR®, Shelys Pharmaceutical Ltd., Dar es Salaam, Tanzania) was given as directly observed treatment; 1st dose in the 2nd trimester after a GA of 20 weeks and 2nd dose in the 3rd trimester, at least four weeks apart. If included early in pregnancy the 1st dose was given at an extra clinic visit at a GA of 20. If having received a 1st dose of IPTp before inclusion, but earlier than recommended by WHO (2nd trimester when quickening is felt [36]), the woman received a 2nd dose at week 20 and a 3rd dose in the 3rd trimester. According to the national program, voucher for procuring a bednet was provided and bednet use inquired. Trans-abdominal ultrasound examination was performed at inclusion, ANV2, ANV3, and ANV4 (Sonosite TITAN®, US High resolution ultrasound system, 5–2 MHz C60 abdominal probe, Bothell, Washington state, USA). At inclusion GA was estimated using crown-rump length (crown-rump length<75 mm) [37]) or head circumference of the fetus [38]. If the GA was 0 represents excess fetal weight gain and a Δz<0 insufficient weight gain. Evaluation of changes in z-scores can be affected by the fetal pulsatile growth pattern [42] and to limit false-positives the 25th centile for Δz was used as a cut-off to define insufficient weight gain. The effect of malaria was categorized in four groups: 1) Normal growth as Δz ≥25th centile in all growth intervals following a malaria infection, 2) Immediate effect as Δz <25th centile in the growth interval when the infection occurred or in the first growth interval after a malaria infection, followed by growth intervals where Δz ≥25th centile, 3) Late effect as a Δz<25th centile in a growth interval not immediately following the infection, and 4) Persistent effect as a Δz <25th centile immediately after a malaria infection and until the end of pregnancy. For analysis, women were considered to be malaria negative if they never had malaria based on RDT and microscopy results from the time they were enrolled. Women, who contracted malaria (RDT and/or microscopy positive), were considered to belong to the malaria group from when they were diagnosed until delivery. In growth intervals preceding the time of detection of the malaria infection they were excluded from the analysis. Hence, women contracting malaria between ANV2 and ANV3 were not included in analyses of the growth interval ANV2-ANV3, but considered malaria positive in all other growth intervals. All data were documented and validated using Microsoft Office Access 2003. Statistical analyses were performed in Stata 10 (Stata Corporation) using, when appropriate, Chi2 test, Fisher’s exact test, Mann Whitney ranksum, and Student t-test, and all with two-sided P-values. The effect of malaria on BW (as z-score) was investigated using multiple linear regression and on relative weight gain (dichotomized as lowest 25% and highest 75%) using multiple logistic regression. Crude and adjusted coefficients/odds ratios were calculated. Factors with a P<0.20 in univariate analysis were entered into the multivariate models. Using a step-wise backward elimination approach final models were obtained including variables with a P<0.10. A P<0.05 was considered significant. Final models only included women without missing values.

The study titled “Malaria and Fetal Growth Alterations in the 3rd Trimester of Pregnancy: A Longitudinal Ultrasound Study” investigated the impact of malaria on fetal growth during the third trimester of pregnancy. The study used trans-abdominal ultrasound to monitor fetal growth in 876 pregnant women in Tanzania. The results showed that malaria infection affected birth weight and fetal growth in primi- and secundigravid women. The study highlighted the need for protection against malaria throughout pregnancy and the recognition that observed changes in fetal growth might be a consequence of an infection much earlier in pregnancy. The study was conducted in accordance with ethical guidelines and obtained informed written consent from all participants.
AI Innovations Description
The recommendation that can be developed into an innovation to improve access to maternal health based on the study “Malaria and Fetal Growth Alterations in the 3rd Trimester of Pregnancy: A Longitudinal Ultrasound Study” is to implement regular screening and treatment for malaria in pregnant women, especially during the 3rd trimester. This recommendation is based on the findings of the study, which showed that malaria infection during pregnancy had a significant impact on birth weight and fetal growth, particularly among primi- and secundigravid women.

By implementing regular screening for malaria and providing appropriate treatment, healthcare providers can identify and treat malaria infections in pregnant women, thereby reducing the negative effects on fetal growth. This can be done through the use of rapid diagnostic tests (RDTs) and antimalarial medications. Additionally, sensitization campaigns can be conducted to raise awareness among pregnant women about the importance of protecting themselves against malaria throughout pregnancy.

Furthermore, the study highlights the need for access to ultrasound examinations during pregnancy to monitor fetal growth. By incorporating regular ultrasound screenings into antenatal care, healthcare providers can identify any growth alterations and take appropriate actions to ensure the well-being of both the mother and the baby.

Overall, the recommendation is to integrate regular screening and treatment for malaria, as well as regular ultrasound examinations, into existing maternal health services to improve access to maternal health and reduce the negative impact of malaria on fetal growth.
AI Innovations Methodology
Based on the provided information, here are some potential recommendations to improve access to maternal health:

1. Increase availability and accessibility of antenatal care: Ensure that pregnant women have access to regular check-ups and screenings throughout their pregnancy. This can be achieved by expanding the number of healthcare facilities, particularly in rural areas, and providing transportation options for pregnant women to reach these facilities.

2. Strengthen malaria prevention and treatment programs: Implement comprehensive malaria prevention strategies, including the distribution of insecticide-treated bed nets and intermittent preventive treatment for pregnant women. Improve access to accurate and timely malaria diagnosis and effective treatment.

3. Enhance health education and awareness: Conduct community-based health education programs to raise awareness about the importance of antenatal care, malaria prevention, and the potential impact of malaria on fetal growth. Provide information on the signs and symptoms of malaria during pregnancy and encourage early detection and treatment.

4. Improve healthcare infrastructure and resources: Invest in improving healthcare facilities, equipment, and resources to ensure that pregnant women receive quality care. This includes adequate staffing, trained healthcare professionals, and essential medical supplies.

To simulate the impact of these recommendations on improving access to maternal health, a methodology could include the following steps:

1. Define the target population: Determine the specific population that will be affected by the recommendations, such as pregnant women in a particular region or country.

2. Collect baseline data: Gather data on the current state of access to maternal health, including the number of pregnant women receiving antenatal care, malaria prevalence rates, and birth outcomes.

3. Develop a simulation model: Create a mathematical or statistical model that simulates the impact of the recommendations on access to maternal health. This model should consider factors such as population size, healthcare infrastructure, resource availability, and the effectiveness of the interventions.

4. Input data and parameters: Input the baseline data and parameters into the simulation model. This includes information on the current levels of antenatal care utilization, malaria prevalence, and birth outcomes, as well as the expected impact of the recommendations (e.g., increase in antenatal care coverage, reduction in malaria prevalence).

5. Run simulations: Run the simulation model to project the potential impact of the recommendations over a specified time period. This can include estimating the number of additional pregnant women accessing antenatal care, the reduction in malaria cases, and the improvement in birth outcomes.

6. Analyze results: Analyze the simulation results to assess the potential impact of the recommendations on improving access to maternal health. This can include evaluating changes in key indicators such as antenatal care coverage, malaria prevalence, and birth outcomes.

7. Refine and validate the model: Continuously refine and validate the simulation model based on new data and feedback. This can help improve the accuracy and reliability of the projections.

By following this methodology, policymakers and healthcare stakeholders can gain insights into the potential impact of different recommendations on improving access to maternal health and make informed decisions on resource allocation and program implementation.

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