HIV viral load assays when used with whole blood perform well as a diagnostic assay for infants

listen audio

Study Justification:
– Only approximately 50% of HIV-exposed infants receive an early infant diagnosis test within the first two months of life.
– Fragmented and challenging laboratory systems are a barrier to identifying HIV-infected infants early and putting them on life-saving treatment.
– The study aimed to determine the accuracy of using HIV viral load assays for infant diagnosis of HIV.
Study Highlights:
– Enrolled 866 Ugandan infants for the study.
– Testing was done using Roche and Abbott molecular technologies at the Central Public Health Laboratory.
– Dried blood spot samples were prepared and tested using both qualitative and quantitative assays.
– Roche SPEX and Abbott technologies had high sensitivity (>95%) and specificity (>98%).
– Roche FVE had lower sensitivity (85%) and viral load values.
– HIV viral load may be used to diagnose HIV infection in infants, particularly using Roche SPEX and Abbott technologies.
Study Recommendations:
– Simplify and streamline laboratory practices by using HIV viral load assays for infant diagnosis.
– Promote the use of Roche SPEX and Abbott technologies for accurate diagnosis of HIV infection in infants.
Key Role Players:
– Laboratory technicians and scientists for sample processing and testing.
– Health care facilities and health care workers for sample collection and result management.
– Policy makers and government officials for implementing changes in laboratory practices.
Cost Items for Planning Recommendations:
– Equipment and reagents for HIV viral load assays.
– Training and capacity building for laboratory technicians.
– Quality control measures for accurate testing.
– Information systems for result management and reporting.
– Monitoring and evaluation to assess the impact of the recommendations.

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is based on a blinded, cross-sectional, prospective study with a large sample size. The study used laboratory-based viral load quantitative assays to determine HIV infection compared to laboratory-based, qualitative infant diagnosis assays. The study was conducted at the Central Public Health Laboratory in Kampala, Uganda using remnant samples from routinely collected dried blood spot samples. The study found that using HIV viral load assays, particularly the Roche SPEX and Abbott technologies, can simplify and streamline laboratory practices for diagnosing HIV infection in infants. However, to improve the evidence, the study could have included a control group for comparison, provided more details on the methodology, and discussed potential limitations of the study.

Objective Over the past several years, only approximately 50% of HIV-exposed infants received an early infant diagnosis test within the first two months of life. While high attrition and mortality account for some of the shortcomings in identifying HIV-infected infants early and putting them on life-saving treatment, fragmented and challenging laboratory systems are an added barrier. We sought to determine the accuracy of using HIV viral load assays for infant diagnosis of HIV. Methods We enrolled 866 Ugandan infants between March–April 2018 for this study after initial laboratory diagnosis. The median age was seven months, while 33% of infants were less than three months of age. Study testing was done using either the Roche or Abbott molecular technologies at the Central Public Health Laboratory. Dried blood spot samples were prepared according to manufacturer-recommended protocols for both the qualitative and quantitative assays. Viral load test samples for the Roche assay were processed using two different buffers: phosphate-buffered saline (PBS: free virus elution viral load protocol [FVE]) and Sample Pre-Extraction Reagent (SPEX: qualitative buffer). Dried blood spot samples were processed for both assays on the Abbott using the manufacturer’s standard infant diagnosis protocol. All infants received a qualitative test for clinical management and additional paired quantitative tests. Results 858 infants were included in the analysis, of which 50% were female. Over 75% of mothers received antiretroviral therapy, while approximately 65% of infants received infant prophylaxis. The Roche SPEX and Abbott technologies had high sensitivity (>95%) and specificity (>98%). The Roche FVE had lower sensitivity (85%) and viral load values. Conclusions To simplify and streamline laboratory practices, HIV viral load may be used to diagnose HIV infection in infants, particularly using the Roche SPEX and Abbott technologies.

This was a blinded, cross-sectional, prospective study to investigate the diagnostic accuracy of laboratory-based viral load quantitative assays to determine HIV infection compared to laboratory-based, qualitative infant diagnosis assays. All testing occurred at the Central Public Health Laboratory in Kampala, Uganda using remnant samples from routinely collected dried blood spot samples. Samples were received in the laboratory through the national infant diagnosis system from any health care facility in the country submitting a clinical sample from an HIV-exposed infant less than 18 months of age for routine diagnosis. Sample receipt, processing, and testing occurred between March and August 2018. All clinical samples were tested using the Roche COBAS AmpliPrep/COBAS TaqMan HIV-1 Qualitative Test, v2.0 (total nucleic acid detected)–these results were provided to the health care facility, health care workers, and caregivers to manage the infant’s care. Samples were purposefully selected in that all consecutively collected positive samples and an equal number of randomly selected negative samples were included and blindly tested each week until the target sample size was met. Most (179) of the negative samples were used for both the Roche COBAS AmpliPrep/COBAS TaqMan HIV-1 Test, v2.0 and Abbott RealTime HIV-1 viral load assays (RNA only detected); however, 70 additional consecutive negative samples were collected for testing using the Abbott viral load assay, as the original samples were insufficient for testing with both assays. Separate sets of consecutively collected positive samples were used for the two technologies (Roche COBAS AmpliPrep/COBAS TaqMan HIV-1 Test, v2.0 and Abbott RealTime HIV-1 viral load), because the majority of positive samples did not have sufficient remaining spots available as all positive samples in routine clinical care are repeat tested in the laboratory prior to result dispatch. Demographic and clinical data were collected from each patient using routine national requisition forms, including age, sex, maternal treatment, infant prophylaxis, and breastfeeding status. The cycle threshold of both qualitative and quantitative assays were captured as well as the qualitative result (detected or not detected) and viral load result from the quantitative assay. Dried blood spot preparation and testing for the qualitative assays were conducted as previously described for the Roche COBAS AmpliPrep/COBAS TaqMan HIV-1 Qualitative Test, v2.0 [18]. Dried blood spots were prepared in two ways for the Roche COBAS AmpliPrep/COBAS TaqMan HIV-1 Test v2.0, using SPEX and PBS (free virus elution: FVE protocol) buffers [18, 19]. In brief, one spot was cut out using a pair of scissors or 12mm circular punch, transferred with forceps to an S-tube and 1100 ul of Sample Pre-Extraction Reagent (SPEX) was added; the tubes were incubated in a thermomixer at 56°C and shaken at 1000 rpm for ten minutes before being loaded on to the sample rack for testing. For the COBAS AmpliPrep/COBAS TaqMan HIV-1 Qualitative Test, v2.0 using the FVE protocol, one spot was cut out using a pair of scissors or 12 mm circular punch, transferred with forceps to an S-tube and 1000 ul of calcium- and magnesium-free Phosphate buffered saline (PBS) buffer added; the tubes were incubated at room temperature for at least 30 minutes or overnight. The tubes were gently tapped at the bottom to homogenize the solution before being loaded on to the sample rack for testing. Dried blood spots for the Abbott RealTime HIV-1 Viral Load assay were prepared similarly to those prepared for the Abbott RealTime HIV-1 Qualitative assay [20]. In brief, one spot was punched from the card using a sterile pipet tip, placed in a tube, and 1300 ul of mSample Preparation System buffer added; the tubes were manually swirled to ensure the spot was fully submerged, and incubated in a thermomixer at 55°C for 30 minutes. Tubes were then manually swirled again before being transferred directly to the sample rack for testing. Alternatively, as a sub-analysis to determine if a different sample preparation might improve performance, we also processed a separate set of samples using a modified dried blood spot sample preparation protocol, in which two spots were submerged in 1500 ul of mDBS buffer (all other steps remaining consistent). The sensitivity and specificity of using the viral load assays to accurately diagnose HIV infection were calculated using the Roche COBAS AmpliPrep/COBAS TaqMan HIV-1 Qualitative Test, v2.0 assay as this assay is currently the standard test used for clinical management in Uganda. The score-based Wilson method [21] was used to construct confidence intervals for sensitivity and specificity. Confidence intervals for Cohen’s Kappa were estimated [22]. McNemar’s chi-squared test for symmetry of rows and columns in a two-dimensional contingency table was estimated [23]. Further, a sub-analysis was conducted comparing the performance of the quantitative assay with the qualitative assay in infants exposed to antiretroviral drugs–either through infant prophylaxis or maternal treatment. All statistical analyses were performed in the R statistical computing environment. This study was approved by the Uganda National Council for Science and Technology; the Higher Degrees, Research and Ethics Committee from Makerere University, Uganda; Chesapeake International Review Board in the United States; and the Ethics Review Committee from the World Health Organization, Geneva, Switzerland. Informed consent was waived by each ethical review committee because of the use of routine, leftover clinical samples. The data were fully anonymized prior to access and analysis. Viral load test results were not provided to patients. The routine clinical qualitative infant diagnosis test results were returned to the health care facility and caregiver per national guidelines.

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

1. Mobile Health (mHealth) Solutions: Develop mobile applications or SMS-based systems to provide information and reminders to pregnant women about antenatal care visits, medication adherence, and postnatal care.

2. Telemedicine: Implement telemedicine services to enable remote consultations between healthcare providers and pregnant women, especially in rural or underserved areas where access to healthcare facilities is limited.

3. Community Health Workers: Train and deploy community health workers to provide basic maternal health services, education, and support to pregnant women in their communities.

4. Point-of-Care Testing: Introduce portable and easy-to-use diagnostic devices that can be used at the point of care to quickly and accurately diagnose conditions such as HIV, preeclampsia, and gestational diabetes.

5. Supply Chain Management: Improve supply chain management systems to ensure the availability of essential maternal health commodities, such as contraceptives, prenatal vitamins, and emergency obstetric care supplies, in healthcare facilities.

6. Health Financing Models: Develop innovative health financing models, such as microinsurance or community-based health financing schemes, to make maternal health services more affordable and accessible to low-income women.

7. Maternal Health Education: Implement comprehensive maternal health education programs that focus on promoting healthy behaviors, improving nutrition, and raising awareness about the importance of antenatal and postnatal care.

8. Public-Private Partnerships: Foster collaborations between the public and private sectors to leverage resources, expertise, and technology for improving maternal health services, including infrastructure development, training programs, and service delivery.

9. Data Analytics and Monitoring: Utilize data analytics and monitoring systems to track maternal health indicators, identify gaps in service delivery, and inform evidence-based decision-making for resource allocation and policy development.

10. Maternal Health Information Systems: Establish integrated information systems that enable the seamless sharing of maternal health data between healthcare facilities, ensuring continuity of care and reducing duplication of tests and procedures.

These innovations can help address the challenges in accessing maternal health services, improve the quality of care, and ultimately contribute to better maternal and child health outcomes.
AI Innovations Description
The recommendation to improve access to maternal health based on the provided information is to utilize HIV viral load assays as a diagnostic tool for infants. The study conducted in Uganda found that using HIV viral load assays, specifically the Roche SPEX and Abbott technologies, had high sensitivity and specificity in diagnosing HIV infection in infants. This recommendation suggests that incorporating viral load testing into routine infant diagnosis protocols can simplify and streamline laboratory practices, making it easier to identify HIV-infected infants early and provide them with life-saving treatment. By implementing this recommendation, healthcare facilities can improve access to maternal health by ensuring timely and accurate diagnosis of HIV infection in infants.
AI Innovations Methodology
Based on the provided information, here are some potential recommendations to improve access to maternal health:

1. Strengthen Laboratory Systems: Address the fragmented and challenging laboratory systems by investing in infrastructure, equipment, and training to ensure efficient and accurate testing for maternal health conditions, including HIV infection.

2. Early Infant Diagnosis: Increase efforts to ensure that HIV-exposed infants receive early infant diagnosis tests within the first two months of life. This can be achieved through targeted outreach programs, community education, and improved coordination between healthcare facilities and laboratories.

3. Streamline Laboratory Practices: Simplify and streamline laboratory practices by using HIV viral load assays for infant diagnosis of HIV infection. This can help reduce the need for multiple tests and improve efficiency in diagnosing and initiating treatment for HIV-infected infants.

4. Technology Adoption: Consider adopting innovative technologies, such as the Roche SPEX and Abbott viral load assays, which have shown high sensitivity and specificity in diagnosing HIV infection in infants. These technologies can provide accurate and timely results, enabling healthcare providers to make informed decisions regarding treatment.

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

1. Define the Key Metrics: Identify key metrics to measure the impact of the recommendations, such as the percentage of HIV-exposed infants receiving early infant diagnosis tests, turnaround time for test results, and the percentage of infants diagnosed and initiated on treatment within a specific timeframe.

2. Data Collection: Collect relevant data on the current state of access to maternal health, including the number of HIV-exposed infants, the percentage of infants receiving early infant diagnosis tests, and the time taken for test results to be available.

3. Model Development: Develop a simulation model that incorporates the recommended innovations and their potential impact on the key metrics. This model should consider factors such as the capacity of laboratory systems, the effectiveness of outreach programs, and the adoption rate of new technologies.

4. Scenario Analysis: Conduct scenario analysis using the simulation model to assess the potential impact of different combinations of innovations. This can help identify the most effective strategies for improving access to maternal health and estimate the expected improvements in key metrics.

5. Validation and Sensitivity Analysis: Validate the simulation model by comparing its outputs with real-world data. Conduct sensitivity analysis to assess the robustness of the model and identify the key factors that influence the outcomes.

6. Policy Recommendations: Based on the simulation results, provide policy recommendations on the implementation of the identified innovations to improve access to maternal health. These recommendations should consider the feasibility, cost-effectiveness, and scalability of the proposed interventions.

By following this methodology, policymakers and healthcare providers can make informed decisions on implementing innovations to improve access to maternal health and ensure better outcomes for mothers and infants.

Partagez ceci :
Facebook
Twitter
LinkedIn
WhatsApp
Email