Multiple concurrent illnesses associated with anemia in HIV-infected and HIV-exposed uninfected children aged 6-59 months, hospitalized in Mozambique

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Study Justification:
– Anemia is a growing concern in sub-Saharan Africa, including Mozambique.
– The study aimed to determine the prevalence, severity, and factors associated with anemia in hospitalized children aged 6-59 months, specifically HIV-infected and HIV-exposed uninfected children.
– Understanding the causes and impact of anemia in this population is crucial for developing effective management strategies.
Study Highlights:
– Out of 413 children enrolled, 88% were found to be anemic.
– The most common diagnoses associated with hospital admission were acute respiratory illness, malnutrition, gastroenteritis/diarrhea, malaria, and bacteremia.
– Malaria and bacteremia were found to significantly decrease hemoglobin levels.
– Bacteremia was associated with a higher risk of death during hospitalization.
Recommendations for Lay Reader and Policy Maker:
– Physicians and nonphysician clinicians in Mozambique should adopt integrated and non-disease specific approaches to pediatric anemia management.
– Improved access to blood culture should be included in algorithms used for diagnosing and managing anemia.
– Strategies should be developed to address the high burden of malaria, HIV, tuberculosis, and poor nutrition, which contribute to anemia in Mozambique.
Key Role Players Needed to Address Recommendations:
– Healthcare providers (physicians and nonphysician clinicians)
– Laboratory technicians for blood culture
– Policy makers and government officials
– Public health organizations and NGOs
Cost Items to Include in Planning Recommendations:
– Training and capacity building for healthcare providers on integrated anemia management approaches
– Equipment and supplies for blood culture
– Development and implementation of algorithms for anemia diagnosis and management
– Public health campaigns and interventions targeting malaria, HIV, tuberculosis, and malnutrition
– Monitoring and evaluation of anemia management programs

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is moderately strong. The study conducted a prospective observational study with a relatively large sample size (N = 413) and provided detailed information on the magnitude, severity, and associated factors of anemia among hospitalized children aged 6-59 months in Mozambique. The study also analyzed the impact of various diagnoses on hemoglobin levels and explored the association between bacteremia and in-hospital death. However, the abstract lacks information on the study design, data collection methods, and statistical analysis techniques used. To improve the evidence, the abstract should include a brief description of the study design (e.g., prospective observational study), provide more details on the data collection methods (e.g., how anemia was diagnosed, how diagnoses were determined), and mention the statistical analysis techniques used (e.g., regression analysis).

Anemia is an increasingly recognized problem in sub-Saharan Africa. To determine the magnitude, severity, and associated factors of anemia among hospitalized children aged 6-59 months, HIV-infected and HIV-exposed uninfected children (a child born to a known HIV-infected mother) with a documented fever or history of fever within the prior 24 hours of hospital admission (N = 413) were included in this analysis. Of 413 children enrolled, 364 (88%) were anemic, with 53% classified as mild anemia (hemoglobin [Hb] 7-9.9 g/dL). The most common diagnoses associated with hospital admission included acute respiratory illness (51%), malnutrition (47%), gastroenteritis/diarrhea (25%), malaria (17%), and bacteremia (13%). A diagnosis of malaria was associated with a decrease in Hb by 1.54 g/dL (P < 0.001). In HIV-infected patients, malaria was associated with a similar decrease in Hb (1.47 g/dL), whereas a dual diagnosis of bacteremia and malaria was associated with a decrease in Hb of 4.12 g/dL (P < 0.001). No difference was seen in Hb for patients on antiretroviral therapy versus those who were not. A diagnosis of bacteremia had a roughly 4-fold increased relative odds of death during hospitalization (adjusted odds ratio = 3.97; 95% CI: 1.61, 9.78; P = 0.003). The etiology of anemia in high-burden malaria, HIV, tuberculosis, and poor nutrition countries is multifactorial, and multiple etiologies may be contributing to one's anemia at any given time. Algorithms used by physician and nonphysician clinicians in Mozambique should incorporate integrated and non-disease specific approaches to pediatric anemia management and should include improved access to blood culture.

We conducted a prospective observational study of HIV-infected and HIV-exposed uninfected children in the cities of Maputo and Quelimane, Mozambique, who were prospectively followed up during their hospital stay. This “parent” study was designed to determine the incidence, etiology, antibiotic sensitivity patterns, and molecular characterizations of culture-confirmed bacteremia in representative rural and urban hospitals in Mozambique. All HIV-infected and HIV-exposed uninfected children aged 0–59 months with a documented axillary temperature of ≥ 37.5°C or rectal temperature ≥ 38.0°C, or a history of fever within the 24 hours before hospitalization between April 1, 2016 and December 31, 2018 were enrolled. Patients were recruited from the pediatric urgent care clinics of three hospitals in Maputo: Central Hospital Maputo, Hospital Jose Macamo, and General Hospital Mavalane; and two hospitals in Quelimane: Central Hospital Quelimane and General Hospital Quelimane. All are tertiary referral hospitals supported by the National Health System (Figure 1). Map of Mozambique with study hospitals identified for Maputo and Quelimane. This figure appears in color at www.ajtmh.org. Using data collected during the course of the parent study, we conducted this anemia analysis on our patient population aged between 6 and 59 months. Children were considered HIV positive if they had a documented proof of HIV infection by polymerase chain reaction (PCR) or HIV rapid antibody tests (if ≥ 9 months at time of test), or if they were taking ART in the absence of documented HIV test results. Children admitted with a fever, or a history of fever, and no documented history of HIV, but with documented maternal HIV exposure by self-report, were offered a PCR (if < 9 months old) or an HIV rapid antibody test (if ≥ 9 months old). Those with negative test results were then considered HIV-exposed uninfected. Children admitted with a fever, or a history of fever, and no documented history of HIV and no documented maternal HIV exposure by self-report, although with high clinical suspicion of HIV, were enrolled and offered HIV testing based on the aforementioned. Those with negative test results were considered HIV negative, and there were 18 subjects who were excluded from analysis because of a final designation of being HIV negative or unknown. For all eligible patients, study staff collected a single blood specimen for bacterial culture before the initiation of antibiotics. Additional diagnostic testing was performed if there was clinical suspicion based on the history or signs/symptoms. Readily available tests included complete blood count, blood chemistries, dipstick urinalysis, chest X-ray, lumbar puncture for chemistries and bacterial culture, stool culture, stool ova and parasites, HIV rapid antibody testing or DNA-PCR, and malaria antigen rapid testing. For patients with a positive malaria rapid test, thick and thin blood films were prepared for confirmation and to quantify Plasmodium falciparum parasitemia. There was no available laboratory diagnostics for TB in this age-group. Severe anemia was defined as a hemoglobin (Hb) concentration of 11 g/dL. All patients were followed up until their discharge from the hospital. Possible final disposition included discharged patients, patients who died during hospitalization, or patients who abandoned treatment, meaning they left the hospital against the wishes of the treating clinician. Data for the parent study, including this anemia analysis, were collected by study clinicians using a paper-based study instrument and then uploaded into a password protected, tablet-based, online database maintained by the Research Electronic Data Capture consortium (www.project-redcap.org). This allowed for the recording of demographic information, medical and medication history, and information on clinical course while hospitalized. Data quality control was conducted by study investigators who reviewed all completed paper-based study instruments and confirmed the accuracy of data entered into the electronic database. Descriptive statistics were used to summarize the participants’ sociodemographic characteristics using frequencies and proportions (for dichotomous or categorical variables) or medians with interquartile ranges for continuous variables. In univariate analysis, we compared factors by anemia status defined as > 11 g/dL, 10–10.9 g/dL, 7–9.9 g/dL, and < 7 g/dL using chi-squared test. In regression analysis, for our response or outcome variable that proxies anemia, we used Hb level (g/dL) without categorization. Using the continuous response of the Hb level maximizes our regression power by using all information levels. We assessed the association of prespecified diagnosed conditions of interest that included bacteremia, malaria, gastroenteritis (GE)/diarrhea, acute respiratory illness (ARI), or malnutrition, with the Hb level as a biomarker response variable using separate regression analyses. Because anemia can be secondary to one’s ART treatment, we also examined the association of ART treatment and Hb level among HIV-infected patients. We examined the interaction effect of concurrent diagnoses using separate regression and a cross-product term (bacteremia and malaria, bacteremia and malnutrition, and malaria and malnutrition) on Hb levels as an exploration analysis. Among our subset of children who were HIV infected, we examined the association of diagnosis with the outcome of in-hospitalization death (yes versus no) using multivariable logistic regression. Each multivariable regression analysis included the child’s age, gender, and health facility as covariates for adjustment. We had case-wise deletions on ∼4% of subjects because of missing data for infant age (n = 18). We performed multiple imputations (MIs) to account for missing age data in multivariable regression as sensitivity analyses.26 We present beta coefficient-associating factors with anemia from complete case analysis. Statistical significance was determined using a 2-sided, 5% significance level. Statistical analysis was performed using R version 3.4.0 software (R core team, 2015, R Foundations for Statistical Computing, Viena, Austria, http://www.r-project.org). The Mozambican National Bioethics Committee for Health (Comité Nacional de Bioética para Saúde) (404/CNBS/14) and the Institutional Review Board of Vanderbilt University Medical Center (IRB#141167) approved this analysis. Informed consent was obtained from the parent or legal guardian of all children enrolled in this study.

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Based on the provided description, here are some potential innovations that could improve access to maternal health:

1. Telemedicine: Implementing telemedicine services can provide remote access to healthcare professionals, allowing pregnant women to receive medical advice, consultations, and monitoring without having to travel long distances.

2. Mobile health (mHealth) applications: Developing mobile applications that provide information on prenatal care, nutrition, and maternal health can empower women with knowledge and resources to take care of themselves during pregnancy.

3. Community health workers: Training and deploying community health workers who can provide basic prenatal care, education, and support to pregnant women in rural areas can improve access to maternal health services.

4. Transportation solutions: Establishing transportation systems or partnerships to ensure that pregnant women have reliable and affordable transportation to healthcare facilities for prenatal check-ups and delivery.

5. Maternal health clinics: Setting up dedicated maternal health clinics in underserved areas can provide comprehensive prenatal care, delivery services, and postnatal care, ensuring that women have access to quality healthcare throughout their pregnancy journey.

6. Mobile clinics: Deploying mobile clinics equipped with medical professionals and necessary equipment to remote areas can bring essential maternal health services directly to communities that lack access to healthcare facilities.

7. Health education programs: Implementing targeted health education programs that focus on prenatal care, nutrition, and safe delivery practices can empower women with knowledge and help them make informed decisions about their health and the health of their babies.

8. Partnerships with local organizations: Collaborating with local organizations, such as NGOs and community-based groups, can help leverage existing resources and networks to improve access to maternal health services.

9. Financial incentives: Providing financial incentives, such as subsidies or cash transfers, to pregnant women who seek prenatal care and deliver at healthcare facilities can help overcome financial barriers and encourage utilization of maternal health services.

10. Strengthening healthcare infrastructure: Investing in the improvement and expansion of healthcare facilities, particularly in rural areas, can ensure that there are enough resources and skilled healthcare professionals to provide quality maternal health services.
AI Innovations Description
Based on the description provided, here is a recommendation that can be developed into an innovation to improve access to maternal health:

1. Implement integrated and non-disease specific approaches: Develop algorithms and guidelines for healthcare providers in Mozambique that incorporate integrated and non-disease specific approaches to pediatric anemia management. This means considering multiple factors that contribute to anemia, such as malaria, HIV, tuberculosis, and poor nutrition, and addressing them collectively rather than focusing on individual diseases.

2. Improve access to blood culture: Enhance access to blood culture testing in healthcare facilities across Mozambique. Blood culture testing can help identify the specific causes of anemia and guide appropriate treatment. This can be achieved by ensuring that healthcare facilities have the necessary equipment, trained staff, and resources to perform blood culture tests.

3. Strengthen diagnostic capabilities: Invest in improving diagnostic capabilities in Mozambique, particularly for diseases like tuberculosis that currently lack available laboratory diagnostics for children aged 6-59 months. This can involve providing healthcare facilities with the necessary tools and technologies to accurately diagnose and treat these conditions.

4. Enhance healthcare provider training: Conduct training programs for healthcare providers in Mozambique to enhance their knowledge and skills in managing pediatric anemia. This can include training on integrated approaches, blood culture testing, and the diagnosis and treatment of specific diseases associated with anemia.

5. Increase awareness and education: Launch awareness campaigns and educational initiatives to increase knowledge and understanding of pediatric anemia among caregivers and communities in Mozambique. This can involve disseminating information about the causes, symptoms, and available treatments for anemia, as well as promoting the importance of seeking timely healthcare services.

By implementing these recommendations, Mozambique can improve access to maternal health by addressing the multifactorial nature of anemia and ensuring that healthcare providers have the necessary tools, knowledge, and resources to effectively manage and treat this condition.
AI Innovations Methodology
Based on the provided description, here are some potential recommendations for improving access to maternal health:

1. Strengthening healthcare infrastructure: Invest in improving healthcare facilities, equipment, and resources in areas with high maternal health needs. This includes ensuring access to clean water, electricity, and essential medical supplies.

2. Enhancing healthcare workforce: Increase the number of skilled healthcare professionals, such as doctors, nurses, midwives, and community health workers, to provide quality maternal health services. This can be achieved through training programs, incentives, and recruitment strategies.

3. Promoting community engagement: Implement community-based interventions to raise awareness about maternal health, promote antenatal care, and encourage women to seek skilled care during pregnancy, childbirth, and postpartum. This can involve community health education programs, support groups, and community outreach initiatives.

4. Improving transportation and logistics: Address transportation barriers by providing reliable and affordable transportation options for pregnant women, especially in remote areas. This can include ambulances, mobile clinics, or transportation vouchers.

5. Strengthening referral systems: Develop and strengthen referral networks between primary healthcare facilities and higher-level facilities to ensure timely access to emergency obstetric care. This includes improving communication channels, transportation arrangements, and coordination between healthcare providers.

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

1. Define indicators: Identify key indicators to measure the impact of the recommendations, such as the number of pregnant women receiving antenatal care, the percentage of births attended by skilled healthcare professionals, and maternal mortality rates.

2. Collect baseline data: Gather existing data on the current status of maternal health access in the target area, including indicators mentioned above. This can be obtained from health records, surveys, and other relevant sources.

3. Develop a simulation model: Create a simulation model that incorporates the identified recommendations and their potential impact on the selected indicators. This model should consider factors such as population demographics, healthcare infrastructure, workforce capacity, transportation availability, and community engagement.

4. Input data and assumptions: Input the baseline data into the simulation model and define assumptions regarding the implementation and effectiveness of the recommendations. This may include assumptions about the rate of healthcare workforce expansion, community engagement strategies, and improvements in transportation infrastructure.

5. Run simulations: Run multiple simulations using different scenarios to assess the potential impact of the recommendations on the selected indicators. This can involve adjusting the input parameters and assumptions to explore various scenarios and their outcomes.

6. Analyze results: Analyze the simulation results to determine the potential impact of the recommendations on improving access to maternal health. This can involve comparing the outcomes of different scenarios and identifying the most effective strategies.

7. Refine and validate the model: Continuously refine and validate the simulation model based on new data, feedback from stakeholders, and real-world observations. This ensures that the model accurately reflects the complex dynamics of improving access to maternal health.

By following this methodology, policymakers and healthcare stakeholders can gain insights into the potential impact of different recommendations and make informed decisions to improve access to maternal health.

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