Different factors associated with loss to follow-up of infants born to HIV-infected or uninfected mothers: Observations from the ANRS 12140-PEDIACAM study in Cameroon

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Study Justification:
The study aimed to investigate the factors associated with loss to follow-up (LTFU) of mother-child pairs in the ANRS 12140-PEDIACAM study in Cameroon. LTFU can introduce bias in clinical studies and impact the validity and generalizability of results. Understanding the reasons for LTFU can help improve follow-up in clinical studies and contribute to achieving prevention, treatment, and research goals.
Highlights:
– LTFU among HIV-unexposed infants was four times higher than among HIV-exposed infants.
– Factors associated with LTFU among HIV-exposed infants included emergency caesarean section, young maternal age, and absence of antiretroviral treatment for prophylaxis.
– Factors associated with LTFU among HIV-unexposed infants included young maternal age, low maternal education level, and housewife/unemployed mothers.
– Enhanced counseling in antenatal and intrapartum services is required for mothers at high risk of failure to return for follow-up visits.
Recommendations:
– Implement enhanced counseling services in antenatal and intrapartum care to improve follow-up rates for infants included in studies involving HIV-exposed infants.
– Provide targeted support and interventions for mothers at high risk of failure to return for follow-up visits, such as young mothers, those with low education levels, and housewife/unemployed mothers.
Key Role Players:
– Healthcare providers: Responsible for providing enhanced counseling services and support to mothers during antenatal and intrapartum care.
– Researchers: Conduct further studies to explore additional factors associated with LTFU and develop strategies to improve follow-up rates.
– Policy makers: Implement policies and guidelines to support enhanced counseling services and interventions for mothers at high risk of LTFU.
Cost Items for Planning Recommendations:
– Training and capacity building for healthcare providers on enhanced counseling techniques: Includes costs for workshops, materials, and trainers.
– Development and dissemination of educational materials for mothers: Includes costs for designing, printing, and distributing materials.
– Monitoring and evaluation of counseling services: Includes costs for data collection, analysis, and reporting.
– Support for targeted interventions: Includes costs for implementing interventions, such as financial assistance for transportation or incentives for attending follow-up visits.

The strength of evidence for this abstract is 8 out of 10.
The evidence in the abstract is strong, but there are some areas for improvement. The study design is robust, with a large sample size and both uni- and multivariable logistic regression analysis. The results show a significant difference in loss to follow-up (LTFU) between HIV-exposed and HIV-unexposed infants, and identify several factors associated with LTFU in both groups. The study provides actionable steps to improve follow-up, such as enhanced counseling in antenatal and intrapartum services for mothers at high risk of LTFU. However, the abstract could be improved by providing more specific details about the study population, methods, and results. Additionally, it would be helpful to include information about the limitations of the study and potential implications of the findings.

Background: Loss to follow-up (LTFU) is a cause of potential bias in clinical studies. Differing LTFU between study groups may affect internal validity and generalizability of the results. Understanding reasons for LTFU could help improve follow-up in clinical studies and thereby contribute to goals for prevention, treatment, or research being achieved. We explored factors associated with LTFU of mother-child pairs after inclusion in the ANRS 12140-Pediacam study. Methods: From November 2007 to October 2010, 4104 infants including 2053 born to HIV-infected mothers and 2051 born to HIV-uninfected mothers matched individually on gender and study site were enrolled during the first week of life in three referral hospitals in Cameroon and scheduled for visits at 6, 10 and 14 weeks of age. Visits were designated 1, 2 and 3, in chronological order, irrespective of the child’s age at the time of the visit. Mother-child pairs were considered lost to follow-up if they never returned for a clinical visit within the first six months after inclusion. Uni- and multivariable logistic regression were adjusted on matching variables to identify factors associated with LTFU according to maternal HIV status. Results: LTFU among HIV-unexposed infants was four times higher than among HIV-exposed infants (36.7% vs 9.8%, p∈<∈0.001). Emergency caesarean section (adjusted Odds Ratio (aOR)∈=∈2.46 95% Confidence Interval (CI) [1.47-4.13]), young maternal age (aOR∈=∈2.29, 95% CI [1.18-4.46]), and absence of antiretroviral treatment for prophylaxis (aOR∈=∈3.45, 95% CI [2.30-5.19]) were independently associated with LTFU among HIV-exposed infants. Factors associated with LTFU among HIV-unexposed infants included young maternal age (aOR∈=∈1.96, 95% CI [1.36-2.81]), low maternal education level (aOR∈=∈2.77, 95% CI [1.95-3.95]) and housewife/unemployed mothers (aOR∈=∈1.56, 95% CI [1.16-2.11]). Conclusion: Failure to return for at least one scheduled clinical visit is a problem especially among HIV-unexposed infants included in studies involving HIV-exposed infants. Factors associated with this type of LTFU included maternal characteristics, socio-economic status, quality of antenatal care and obstetrical context of delivery. Enhanced counselling in antenatal and intrapartum services is required for mothers at high risk of failure to return for follow-up visits.

Data used in this analysis were obtained from the ANRS-Pediacam cohort based in three referral hospitals in Cameroon (The Maternity of the Central hospital/Mother and Child Center of the Chantal Biya Foundation (MCH/MCC-CBF), Essos Hospital Center in Yaoundé (EHC) and the Laquintinie Hospital in Douala (LH)) and coordinated by the Centre Pasteur of Cameroon. The ANRS 12140-Pediacam study was designed to assess the feasibility of early diagnosis of HIV and early antiretroviral multitherapy in HIV-infected infants, and to evaluate the humoral response of these children to vaccines of the Expanded Program on Immunization (EPI). The ANRS 12140-Pediacam is an ongoing prospective cohort study involving two consecutive phases. The first phase of the study included all infants born live to HIV-infected mothers with documented serostatus (group 1) identified before the 8th day of life from November 2007 to October 2010 and an equivalent number of infants born to HIV-uninfected mothers matched individually on gender and recruitment site. All newborns were expected to attend a clinical visit, according to the Cameroon National EPI calendar, at ages 6, 10 and 14 weeks for routine vaccination. Infant follow-up in the first phase was scheduled to coincide with this EPI timetable to minimise the number of visits to the hospital required. However, visits (follow-up visits) are designated hereafter as the first, second and third, independent of the age of the child. Samples for HIV virological testing were collected from HIV-exposed infants at the first follow-up visit (scheduled for 6 weeks), as previously described [13,14]. HIV test results were provided at the second visit (scheduled for 10 weeks). During the second visit, all parents/caregivers who received a negative result for their infants were counselled about how to avoid practises favouring HIV transmission to their infant. For breastfed infants whose first HIV test was negative were retested if they became symptomatic or six weeks after weaning if asymptomatic. For infants with a positive or indeterminate result from the first test, a blood sample was collected at the second visit for confirmatory testing. The results were announced at the third clinical visit (scheduled for 14 weeks). Incentives, including free medical support for consultation, biological analysis, additional vaccines and reimbursement of transport costs, were provided to parents/caregivers by the project during follow-up visits. All HIV-infected children and control groups of HIV-uninfected infants followed since birth, born to either HIV-infected or non-infected mothers were eligible for the second phase of the Pediacam project planned from 14 weeks to 5 years. This phase is not described here as it is not relevant to this study. Socioeconomic and demographic characteristics of the families and obstetrical characteristics were collected at enrolment by questionnaire-based interview with mothers and examination of their hospital booklets. Questionnaires were also used subsequently to collect data on infant vital status, pathologies, vaccinations and HIV testing process as appropriate. Reminder phone calls were made to families who did not return for a follow-up visit within one week of the planned date. The ANRS 12140- Pediacam study has received ethical approval in Cameroon from the National Ethic Committee and in France from the Biomedical Research Committee of the Pasteur Institute of Paris. An administrative authorization was also delivered by the Cameroonian Ministry of Public Health. Written informed consent was obtained from parents or guardians prior to inclusion of infants into the research project. All infants born live to HIV-infected mothers and infants born to HIV-uninfected mothers matched on gender and recruitment site, enrolled from November 2007 to October 2010 into the first phase of the ANRS-Pediacam study planned from the first to 14th week of life were eligible for this analysis. The main outcome was loss to follow-up (LTFU) or “failed to return for at least one scheduled clinical visit” defined as mother-child pairs who never returned for a clinical visit during the first 6 months of age after inclusion in the ANRS-Pediacam study. Those who attended clinical visits, even if only once, were not considered to be lost to follow-up. The threshold of six months was chosen because several studies indicate that knowing the HIV status of the child before age 6 months favours early initiation of HAART [15,16]. Returning for a clinical visit at least once within six months was perceived as having the willingness to comply with the study schedule; failure to attend subsequently may indicate loss of motivation due to constraints associated with the health system. The covariables considered included variables pertaining to infant’s characteristics at birth (gender, prematurity, birth weight, APGAR, hospitalization at birth), maternal characteristics and socio-economic status (HIV serological status, marital status, level of education, socio-professional activity, monthly income, presence of a functional fridge at home, access to electricity, access to tap water), quality of antenatal care and obstetrical context of delivery (primigravid, mode of delivery, place of birth, number of antenatal visits, ART prophylaxis for PMTCT and disclosure of HIV status) and paternal characteristics (age, level of education and socio-professional activity). Maternal and infant characteristics are described using frequencies for categorical variables, medians and interquartile ranges for continuous variables. Their relation to LTFU was evaluated in each group defined by maternal HIV serostatus because of the differences observed between the two groups. For multiple births, only the first infant was included in the analysis. To examine covariables associated with LTFU, logistic regression models were adjusted on site and gender (matching variables) as appropriate for the matched study design [17]. The initial multivariable logistic regression model included those non collinear covariables found by univariable analysis to be associated with LTFU (as the dependent variable) with a p-value ≤ 0.25. The final model was obtained by successively removing variables not associated at a p-value <0.05 only if the odds ratios for the remaining variables were unchanged and taking interactions into account. The following known risk factors were maintained in the final model: low birth weight, prematurity and maternal educational level and socio-professional activity (as a surrogate for economic status). We performed a sensitivity analysis where we imputed missing data as a category for each variable. All statistical analyses were performed using R 2.15 software.

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

1. Mobile Health (mHealth) Solutions: Develop mobile applications or text messaging services that provide pregnant women with information about prenatal care, reminders for appointments, and educational resources. These tools can help overcome barriers to accessing healthcare by providing information directly to women’s smartphones.

2. Community Health Workers: Train and deploy community health workers to provide education, support, and follow-up care to pregnant women in their communities. These workers can help bridge the gap between healthcare facilities and remote or underserved areas, ensuring that women receive the necessary care and support throughout their pregnancy.

3. Telemedicine: Implement telemedicine programs that allow pregnant women to consult with healthcare providers remotely. This can be particularly beneficial for women in rural or remote areas who may have limited access to healthcare facilities. Telemedicine can provide prenatal consultations, monitoring, and support, reducing the need for women to travel long distances for routine check-ups.

4. Financial Incentives: Explore the use of financial incentives to encourage pregnant women to attend prenatal visits and follow-up appointments. This could include providing transportation vouchers or small cash incentives to cover the costs associated with accessing healthcare services.

5. Collaborative Care Models: Establish partnerships between healthcare facilities, community organizations, and local authorities to create integrated care models. This approach can ensure that pregnant women receive comprehensive care that addresses their physical, emotional, and social needs. By working together, different stakeholders can improve coordination and streamline the delivery of maternal health services.

6. Health Education Programs: Develop and implement targeted health education programs that focus on raising awareness about the importance of prenatal care and the potential risks associated with not seeking care. These programs can be delivered through community workshops, radio broadcasts, or social media campaigns to reach a wide audience.

7. Improving Antenatal Care Services: Enhance the quality and accessibility of antenatal care services by ensuring that healthcare facilities have well-trained staff, adequate resources, and appropriate equipment. This can help build trust and confidence among pregnant women, encouraging them to seek care and follow through with their appointments.

It is important to note that these recommendations are based on the information provided and may need to be tailored to the specific context and needs of the maternal health system in Cameroon.
AI Innovations Description
The study titled “Different factors associated with loss to follow-up of infants born to HIV-infected or uninfected mothers: Observations from the ANRS 12140-PEDIACAM study in Cameroon” explores the factors associated with loss to follow-up (LTFU) of mother-child pairs after inclusion in the ANRS 12140-Pediacam study. The goal of the study is to understand the reasons for LTFU and improve follow-up in clinical studies related to maternal and child health.

The study found that LTFU among HIV-unexposed infants was four times higher than among HIV-exposed infants. Factors associated with LTFU among HIV-exposed infants included emergency caesarean section, young maternal age, and absence of antiretroviral treatment for prophylaxis. Factors associated with LTFU among HIV-unexposed infants included young maternal age, low maternal education level, and housewife/unemployed mothers.

Based on the findings of this study, a recommendation to improve access to maternal health would be to enhance counseling in antenatal and intrapartum services for mothers at high risk of failure to return for follow-up visits. This could help address the factors associated with LTFU, such as maternal characteristics, socio-economic status, quality of antenatal care, and obstetrical context of delivery. By providing targeted counseling and support, healthcare providers can encourage mothers to attend scheduled clinical visits and ensure continuity of care for both HIV-exposed and HIV-unexposed infants.
AI Innovations Methodology
Based on the provided description, here are some potential recommendations to improve access to maternal health:

1. Strengthening Antenatal Care: Enhance the quality and accessibility of antenatal care services by providing comprehensive and culturally sensitive care to pregnant women. This can include regular check-ups, education on pregnancy and childbirth, and early identification and management of potential complications.

2. Community-Based Interventions: Implement community-based interventions to increase awareness about maternal health and promote early and regular prenatal care. This can involve community health workers conducting home visits, organizing health education sessions, and facilitating referrals to healthcare facilities.

3. Mobile Health (mHealth) Solutions: Utilize mobile technology to improve access to maternal health services. This can include mobile apps for appointment reminders, health information dissemination, and teleconsultations with healthcare providers.

4. Transportation Support: Address transportation barriers by providing transportation support to pregnant women, especially those living in remote or underserved areas. This can involve establishing transportation networks or providing vouchers for public or private transportation services.

5. Financial Assistance: Provide financial assistance or health insurance coverage to pregnant women to reduce the financial burden associated with accessing maternal health services. This can include subsidies for prenatal care, childbirth, and postnatal care.

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

1. Define the indicators: Identify key indicators to measure the impact of the recommendations, such as the number of pregnant women accessing antenatal care, the percentage of women receiving timely prenatal care, or the reduction in maternal mortality rates.

2. Collect baseline data: Gather data on the current state of access to maternal health services, including the number of women accessing care, the barriers they face, and the outcomes of maternal health.

3. Develop a simulation model: Create a simulation model that incorporates the identified recommendations and their potential impact on access to maternal health. This model should consider factors such as population demographics, healthcare infrastructure, and resource availability.

4. Input data and parameters: Input the collected baseline data into the simulation model, along with relevant parameters such as the coverage and effectiveness of the recommendations.

5. Run simulations: Run multiple simulations using different scenarios to assess the potential impact of the recommendations. This can involve varying parameters such as the coverage of interventions, the population size, or the availability of resources.

6. Analyze results: Analyze the simulation results to determine the projected impact of the recommendations on improving access to maternal health. This can include quantifying changes in key indicators and identifying any potential trade-offs or unintended consequences.

7. Refine and validate the model: Refine the simulation model based on the analysis of results and validate it using real-world data or expert input. This will help ensure the accuracy and reliability of the simulation.

8. Communicate findings: Present the findings of the simulation study to relevant stakeholders, such as policymakers, healthcare providers, and community members. This can help inform decision-making and prioritize interventions to improve access to maternal health.

It is important to note that the methodology for simulating the impact of recommendations may vary depending on the specific context and available data.

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