- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT05048472
East Africa Point of Care Viral Load Study (EAPoC-VL)
Implementation of Point of Care HIV Viral Load Monitoring to Improve Viral Load Suppression Among Children, Adolescents and Young People Living With HIV in East Africa
Study Overview
Status
Conditions
Intervention / Treatment
Detailed Description
Main Study Aims:
i) To determine the effectiveness of PoC VL monitoring in improving viral suppression among children, adolescents and young people living with HIV in East Africa.
ii) To evaluate feasibility and acceptability of using PoC VL monitoring among children, adolescents and young people living with HIV in East Africa.
iii) To understand the psychosocial life of children, adolescents and young people living with HIV in East Africa and how they predict adherence and viral load suppression
Objectives of Aim 1:
Primary objective i. To estimate the effect of PoC VL monitoring on viral load suppression among children, adolescents and young people living with HIV in East Africa at 6 and 12 months of follow-up.
Secondary objectives i. To describe the effect of PoC VL monitoring on the proportion of children, adolescents and young people living with HIV that experiences virological rebound after initial suppression within 6 and 12 months of follow-up.
ii. To describe the effect of PoC VL monitoring on time to initiation of intensive adherence counselling following virological failure among children, adolescents and young people living with HIV.
iii. To estimate the effect of PoC VL monitoring on the proportion of children, adolescents and young people living with HIV that experiences change of ART regimen within 6 and 12 months of follow-up.
iv. To determine the effect of PoC VL monitoring on the proportion of children, adolescents and young people living with HIV that is retained in care at 6 and 12 months.
Objectives of Aim 2 i. To assess the acceptability of the implementation and scale-up of PoC VL testing and monitoring from the perspective of children, adolescents, young people and their caregivers.
ii. To assess the critical determinants that may affect the implementation of PoC VL testing and monitoring from the perspective of healthcare workers and policy makers.
iii. To assess potential barriers and facilitators to implementation and scale-up of PoC VL testing and monitoring among children, adolescents and young people living with HIV.
iv. To assess the incremental cost-effectiveness of PoC VL from a modified societal perspective using established models, with data collected alongside the implementation of the intervention combined with data estimated based on existing studies.
Objectives of Aim 3 i. To psychometrically validate 'psychosocial life' questionnaires. ii. To iteratively develop and psychometrically validate a novel user-friendly tablet-based 'Psychosocial Life' game that predicts adherence and viral load.
iii. To develop and test a set of clinical micro-interventions for psychosocial support based on existing best practice.
iv. To measure how 'psychosocial life' mediates the PoC effect on adherence and viral load.
v. To test proof-of-concept of the use of the novel 'psychosocial life' game and associated micro-interventions in a clinical setting.
Design: A cluster randomized controlled trial with 14 intervention clusters and 14 control clusters.
Study Sites: Twenty (28) health facilities spread across 4 countries as follows: Uganda (8), Kenya (4), Tanzania (12), and Rwanda (4).
Population: The study will be conducted among three population sub-groups
- Study population 1: children, adolescents and young people (≤24 years) living with HIV in participating countries in East Africa.
- Study population 2: Care givers/ guardians and treatment supporters of children, adolescents and young people living with HIV in participating countries in East Africa
- Study population 3: Health care workers attending to children, adolescents and young people living with HIV, and policy makers.
Study Intervention: PoC VL monitoring using Cepheid Gene Xpert machine Control: Standard-of-care / centralized HIV VL monitoring
Duration: The whole project will take 48 months including 24 months of data collection. Each participant will be followed up for approximately 12 months.
Sample size The study will enroll 956 children, adolescents and young people (6months - 24years); with 476 in 14 intervention clusters and 476 in 14 control clusters (34 participants per cluster). The effect of the intervention and 95% CIs will be estimated using cluster-level summary methods and a power of 80%.
Study outcomes of Aim 1 Primary outcomes i. The proportion of children, adolescents and young people living with HIV that achieves viral suppression at 6 and 12 months of follow-up.
ii. The time between enrolment into the study and viral suppression.
Secondary outcomes i. The proportion of children, adolescents and young people living with HIV that experiences virological rebound after initial suppression within 6 and 12 months of follow-up ii. The time between enrolment into the study and initiation of intensive adherence counselling following virological failure.
iii. The proportion of children, adolescents and young people living with HIV that experiences change of ART regimen within 6 and 12 months of follow-up iv. The proportion of children, adolescents and young people living with HIV that is retained in care at 6 and 12 months.
Study outcomes of Aim 2 i. Assessed acceptability of the implementation and scale-up of PoC VL testing and monitoring from the perspective of children, adolescents and young people, and their caregivers.
ii. Identified critical determinants that may affect the implementation of PoC VL testing and monitoring from the perspective of healthcare workers and policy makers.
iii. Identified potential barriers and facilitators to implementation and scale-up of PoC VL testing and monitoring among children, adolescents and young people living with HIV.
iv. An assessment of the incremental cost-effectiveness of PoC VL from a modified societal perspective
Study outcomes of Aim 3 i. Quantified and psychometrically validated measurement of the psychosocial life of children, adolescents and young people living with HIV in East Africa ii. A novel psychometrically validated user-friendly tablet-based 'Psychosocial Life' game that predicts viral load based on psychosocial life.
iii. A list of proposed clinical micro-interventions for psychosocial support based on existing best practice.
iv. A model explaining how psychosocial life indicators mediate the PoC effect on adherence and viral load suppression.
v. A proof-of-concept of the use of the novel 'psychosocial life' game and associated micro-interventions in clinical settings.
Statistical Analysis Aim 1
To investigate the effect of the intervention on viral suppression our analysis will be carried out at the cluster level as follows:
- Reduce clusters to independent observations and provide summary statistics by comparing those in the intervention arm to those in the non-intervention arm.
- Use fixed effects regression to take into account unobserved time-invariant heterogeneity and the treatment effects across the clusters
- Analyse the main outcome (viral suppression) using time to event comparison of the two arms from enrolment to failure or completion of the follow-up time (2 years).
Mixed method Analysis Aim 2 Acceptability and feasibility will be investigated using a combined qualitative and quantitative approach, consisting of thematic content analyses of observations, in-depth interviews and focus group discussions, triangulated and generalized with descriptive statistics of survey data. As part of the feasibility study, the impact of a range of values in sensitivity analyses using each of the respective sites' 2020 per capita GDP as a benchmark cost-effectiveness threshold will be evaluated to be able to estimate the incremental cost-effectiveness of the PoC HIV VL compared to the standard of care. Quality adjusted life years (QALYS) will be calculated based on weights derived from the Global Burden of Disease.
Analysis for Aims 3 Step 1: Determining which psychosocial indicators will be used in the structure equation model on baseline data Pearson correlation analyses will be conducted to examine the strength of associations between all psychosocial life indicator variables and medication adherence. For that, a correlation table will be obtained for looking for multicollinearity. If any two explanatory variables have a Pearson's coefficient of 0.80 or greater one of the variables will be excluded from further analysis as they may measure the same underlying factor.
To determine statistically which psychosocial life indicators have the most predictive power and ascertain the extent to which selected indicators can predict adherence or viral load, a stepwise hierarchical multiple regression will be carried out. Potential predictors will be automatically added into the regression model in steps based on statistical algorithms. Only indicators that significantly improve the overall model fit (R square change) will be retained for the final model of children's psychosocial life.
Step 2: Building a structural equation model and testing how psychosocial life mediates the effect of PoC on adherence and viral load.
Following the RCT design, the goal of this analysis is to measure how psychosocial life indicators mediate the PoC effect on adherence and viral load. An initial hypothetical psychosocial life model will be developed based on variables proved to have the most predictive power obtained from phase one and a synthesis of the empirical literature. The outcome variable will be the change in adherence and viral load separately (difference between baseline and endline data). From the main study (WP1) we assume that PoC improves the medical adherence of children with HIV. We also hypothesize that PoC will improve psychosocial life indicators and that better psychosocial life improves medical adherence and viral load.
Three different types of mediational model will be verified to test the potential mediating role of psychosocial life on the relationship between PoC and medication adherence: (a) a single mediator model, (b) multiple parallel mediator model, and (c) SEM model considering psychosocial life as a latent variable indicated by selected indicators.
Study Type
Enrollment (Actual)
Phase
- Not Applicable
Contacts and Locations
Study Locations
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Kisumu, Kenya
- Kenya Medical Research Institute
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Kigali, Rwanda
- University of Rwanda
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Dar es Salaam, Tanzania
- Management and Development for Health
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Dar es Salaam, Tanzania
- National Institute of Medical Research
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Moshi, Tanzania
- Kilimanjaro Clinical Research Institute
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Entebbe, Uganda
- MRC/UVRI and LSHTM
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Entebbe, Uganda
- Unhro/ Uvri
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Participation Criteria
Eligibility Criteria
Ages Eligible for Study
Accepts Healthy Volunteers
Description
Inclusion Criteria:
- Age 6 months - 24 years
- Documented evidence of HIV infection
- Receiving ART for treatment of HIV infection for at least 6 months.
- Has had a detectable VL of >1000 copies/ml in the last 6 months.
- Guardian, parent or legal representative able and willing to give voluntary consent and sign/mark an informed consent document.
- Willing and able to comply with protocol requirements/study procedures.
Exclusion Criteria:
- Any medical conditions that require pausing of ART for more than three months.
- Potential participant already enrolled in another study which may interfere with the study outcome or participation as per investigator's judgement.
- Child, adolescent or young person already enrolled and completed follow up in the current study.
- Any medical or other condition in the potential participant or their parent/ guardian that precludes provision of informed consent/ assent or that may hinder achieving study objectives as per investigator's judgement.
Study Plan
How is the study designed?
Design Details
- Primary Purpose: Diagnostic
- Allocation: Randomized
- Interventional Model: Parallel Assignment
- Masking: None (Open Label)
Arms and Interventions
Participant Group / Arm |
Intervention / Treatment |
|---|---|
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No Intervention: Control
Use of the standard of care viral load monitoring (centralized viral load monitoring)
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Experimental: Intervention
Use of point of care viral load monitoring (initially Abbott PoC devices, then changed to Cepheid Gene Xpert)
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Point of care viral load monitoring
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What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
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The time between enrolment into the study and viral suppression.
Time Frame: 36 months
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The time between enrolment into the study and viral suppression.
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36 months
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The proportion of children, adolescents and young people living with HIV that achieves viral suppression at 6 and 12 months of follow-up.
Time Frame: 36 months
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The proportion of children, adolescents and young people living with HIV that achieves viral suppression at 6 and 12 months of follow-up
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36 months
|
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
The time between enrolment into the study and initiation of intensive adherence counselling following virological failure.
Time Frame: 36 months
|
The time between enrolment into the study and initiation of intensive adherence counselling following virological failure.
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36 months
|
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The proportion of children, adolescents and young people living with HIV that experiences virological rebound after initial suppression within 6 and 12 months of follow-up
Time Frame: 36 months
|
The proportion of children, adolescents and young people living with HIV that experiences virological rebound after initial suppression within 6 and 12 months of follow-up
|
36 months
|
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The proportion of children, adolescents and young people living with HIV that experiences change of ART regimen within 6 and 12 months of follow-up
Time Frame: 36 months
|
The proportion of children, adolescents and young people living with HIV that experiences change of ART regimen within 6 and 12 months of follow-up
|
36 months
|
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The proportion of children, adolescents and young people living with HIV that is retained in care at 6 and 12 months.
Time Frame: 36 months
|
The proportion of children, adolescents and young people living with HIV that is retained in care at 6 and 12 months.
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36 months
|
Other Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
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The number of factors which may affect the implementation of PoC VL testing and monitoring from the perspective of healthcare workers and policy makers.
Time Frame: 24 months
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The number of factors which may affect the implementation of PoC VL testing and monitoring from the perspective of healthcare workers and policy makers.
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24 months
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The incremental cost-effectiveness of PoC VL from a modified societal perspective
Time Frame: 36 months
|
The incremental cost-effectiveness of PoC VL from a modified societal perspective
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36 months
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The proportion of children, adolescents and young people and their care givers who accept implementation of PoC VL testing and monitoring
Time Frame: 36 months
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The proportion of children, adolescents and young people and their care givers who accept implementation of PoC VL testing and monitoring.
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36 months
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The number of potential barriers and facilitators to implementation and scale-up of PoC VL testing and monitoring identified by children, adolescents and young people living with HIV.
Time Frame: 36 months
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The number of potential barriers and facilitators to implementation and scale-up of PoC VL testing and monitoring identified by children, adolescents and young people living with HIV.
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36 months
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A psychometrically validated measurement of the psychosocial life of children, adolescents and young people living with HIV in East Africa
Time Frame: From 12-36 months
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Validated psychosocial life questionnaire The psychosocial life questionnaire consists of eight scales measuring different psychosocial indicators (1.motivational readiness scale, 2.Social support scale, 3.Self-efficacy scale, 4.Stigma scale, 5.Patient health questionnaire-9, 6.General anxiety disorder-7, 7. Alcohol use and 8.Quality of life) and only individual scales will be validated. Validation of three scales will be prioritized (1. Stigma scale, 2. Patient health questionnaire-9 and 3. General anxiety disorder-7) measuring three psychosocial indicators (stigma, depression and anxiety) which are the most important predictors of poor medication adherence in East Africa). Each scale, it will be possible to compute the minimum and maximum scores and the higher the score the worse the psychosocial issue. The minimum - maximum score 18-54 , 9-36 and 7-28 for the Stigma scale, Patient health questionnaire-9 and General anxiety disorder-7, respectively. |
From 12-36 months
|
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A novel psychometrically validated user-friendly tablet-based 'Psychosocial Life' game that predicts viral load based on psychosocial life.
Time Frame: From 36-48 months
|
The psychosocial life game will be developed from eight scales of psychosocial life questionnaire; meaning that the psychosocial life game will consist of eight components / sessions, each measuring a specific psychosocial indicator (motivational readiness, social support, self-efficacy, stigma, depression, anxiety, alcohol use or quality of life) predictive of poor medication adherence and viral load suppression.
The psychosocial life game will be deployed to HIV clinics and will serve to diagnose a need for psychosocial support among users (adolescents and young people).
The game will also be validated against the observed psychosocial needs of the users (i.e.
adolescents and youth).
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From 36-48 months
|
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A list of proposed clinical micro-interventions for psychosocial support based on existing best practice.
Time Frame: From 36-48 months
|
The List of micro-interventions for psychosocial support services will be identified from analysis results of qualitative data collected from the four countries on 'best practices on psychosocial support services provided to children, adolescents and young people living with HIV in East Africa.'
The analysis report of qualitative data collected on feasibility and acceptability will be reviewed to identify micro-interventions.
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From 36-48 months
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A model explaining how psychosocial life indicators mediate the PoC effect on adherence and viral load suppression.
Time Frame: From 36-48 months
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Explanatory model of the effect of psychosocial life indicators on the PoC effect on adherence and viral load suppression.
In this study, psychosocial life indicators (motivational readiness, social support, stigma, depression, anxiety, alcohol use, self-efficacy, quality of life) are mediating indicators between PoC (dependent / explanatory variable) and medication adherence and viral load suppression (outcome variables).
Before conducting analysis to construct the model, there will be a need to first assess if there is PoC effect.
Due to small sample size, there will be a need to first check if there is an effect of PoC on viral load suppression.
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From 36-48 months
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A proof-of-concept of the use of the novel 'psychosocial life' game and associated micro-interventions in clinical settings.
Time Frame: From 36-48 months
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Proof-of-concept of the use of the novel 'psychosocial life' game.
The proof-of-concept will be produced in form of report a mixed methods study that will be conducted to assess feasibility and acceptability of the use of psychosocial life game considering the perspective of end users
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From 36-48 months
|
Collaborators and Investigators
Collaborators
Investigators
- Principal Investigator: Pontiano Kaleebu, London School of Hygiene and Tropical Medicine
Publications and helpful links
General Publications
- Bowen DJ, Kreuter M, Spring B, Cofta-Woerpel L, Linnan L, Weiner D, Bakken S, Kaplan CP, Squiers L, Fabrizio C, Fernandez M. How we design feasibility studies. Am J Prev Med. 2009 May;36(5):452-7. doi: 10.1016/j.amepre.2009.02.002.
- Sekhon M, Cartwright M, Francis JJ. Acceptability of health care interventions: A theoretical framework and proposed research agenda. Br J Health Psychol. 2018 Sep;23(3):519-531. doi: 10.1111/bjhp.12295. Epub 2018 Feb 16. No abstract available.
- Joint United Nations Programme on, H.A. and H.I.V.A. Joint United Nations Programme on, 90-90-90: an ambitious treatment target to help end the AIDS epidemic. Geneva: UNAIDS
- UNAIDS UNAIDS data 2020. Annual Report, 2020.
- Joint United Nations Programme on, H.A., Fast-track: ending the AIDS epidemic by 2030. Geneva: UNAIDS.
- Agolory S, de Klerk M, Baughman AL, Sawadogo S, Mutenda N, Pentikainen N, Shoopala N, Wolkon A, Taffa N, Mutandi G, Jonas A, Mengistu AT, Dzinotyiweyi E, Prybylski D, Hamunime N, Medley A. Low Case Finding Among Men and Poor Viral Load Suppression Among Adolescents Are Impeding Namibia's Ability to Achieve UNAIDS 90-90-90 Targets. Open Forum Infect Dis. 2018 Aug 11;5(9):ofy200. doi: 10.1093/ofid/ofy200. eCollection 2018 Sep.
- Gill MM, Hoffman HJ, Bobrow EA, Mugwaneza P, Ndatimana D, Ndayisaba GF, Baribwira C, Guay L, Asiimwe A. Detectable Viral Load in Late Pregnancy among Women in the Rwanda Option B+ PMTCT Program: Enrollment Results from the Kabeho Study. PLoS One. 2016 Dec 22;11(12):e0168671. doi: 10.1371/journal.pone.0168671. eCollection 2016.
- Ntlantsana V, Hift RJ, Mphatswe WP. HIV viraemia during pregnancy in women receiving preconception antiretroviral therapy in KwaDukuza, KwaZulu-Natal. South Afr J HIV Med. 2019 Apr 10;20(1):847. doi: 10.4102/sajhivmed.v20i1.847. eCollection 2019.
- Bulage L, Ssewanyana I, Nankabirwa V, Nsubuga F, Kihembo C, Pande G, Ario AR, Matovu JK, Wanyenze RK, Kiyaga C. Factors Associated with Virological Non-suppression among HIV-Positive Patients on Antiretroviral Therapy in Uganda, August 2014-July 2015. BMC Infect Dis. 2017 May 3;17(1):326. doi: 10.1186/s12879-017-2428-3.
- Nabukeera S, Kagaayi J, Makumbi FE, Mugerwa H, Matovu JKB. Factors associated with virological non-suppression among HIV-positive children receiving antiretroviral therapy at the Joint Clinical Research Centre in Lubowa, Kampala Uganda. PLoS One. 2021 Jan 27;16(1):e0246140. doi: 10.1371/journal.pone.0246140. eCollection 2021.
- RBC, Rwanda Population-based HIV Impact Assessment, R.B. Centre, Editor. 2020, RPHIA 2018-2019.
- UNAIDS, Understanding fast†track: Accelerating action to end the AIDS epidemic by 2030. 2015, UNAIDS Geneva.
- Mwau M, Syeunda CA, Adhiambo M, Bwana P, Kithinji L, Mwende J, Oyiengo L, Sirengo M, Boeke CE. Scale-up of Kenya's national HIV viral load program: Findings and lessons learned. PLoS One. 2018 Jan 11;13(1):e0190659. doi: 10.1371/journal.pone.0190659. eCollection 2018.
- El-Sadr WM, Rabkin M, Nkengasong J, Birx DL. Realizing the potential of routine viral load testing in sub-Saharan Africa. J Int AIDS Soc. 2017 Nov;20 Suppl 7(Suppl 7):e25010. doi: 10.1002/jia2.25010. No abstract available.
- Mangone E, C.C., Johns B, Mudhune V, & Avila C, Economic Evaluation of Nationally Scaled Point-of-Care Diagnostic Platforms for Viral Load Monitoring in Kenya, U. Report, Editor. 2018.
- Zhang J, Lan T, Lu Y. Translating in vitro diagnostics from centralized laboratories to point-of-care locations using commercially-available handheld meters. Trends Analyt Chem. 2020 Mar;124:115782. doi: 10.1016/j.trac.2019.115782. Epub 2019 Dec 23.
- Boeke CE, Joseph J, Atem C, Banda C, Coulibaly KD, Doi N, Gunda A, Kandulu J, Kiernan B, Kingwara L, Maokola W, Maparo T, Mbaye RN, Mtumbuka E, Mziray J, Ngugi C, Nkakulu J, Nzuobontane D, Okomo Assoumo MC, Peter T, Rioja MR, Sacks JA, Simbi R, Vojnov L, Khan SA. Evaluation of near point-of-care viral load implementation in public health facilities across seven countries in sub-Saharan Africa. J Int AIDS Soc. 2021 Jan;24(1):e25663. doi: 10.1002/jia2.25663.
- Moyo S, Mohammed T, Wirth KE, Prague M, Bennett K, Holme MP, Mupfumi L, Sebogodi P, Moraka NO, Boleo C, Maphorisa CN, Seraise B, Gaseitsiwe S, Musonda RM, van Widenfelt E, Powis KM, Gaolathe T, Tchetgen Tchetgen EJ, Makhema JM, Essex M, Lockman S, Novitsky V. Point-of-Care Cepheid Xpert HIV-1 Viral Load Test in Rural African Communities Is Feasible and Reliable. J Clin Microbiol. 2016 Dec;54(12):3050-3055. doi: 10.1128/JCM.01594-16. Epub 2016 Oct 12.
- Bwana P, Ageng'o J, Danda J, Mbugua J, Handa A, Mwau M. Performance and usability of mPIMA HIV 1/2 viral load test in point of care settings in Kenya. J Clin Virol. 2019 Dec;121:104202. doi: 10.1016/j.jcv.2019.104202. Epub 2019 Oct 23.
- Drain PK, Dorward J, Violette LR, Quame-Amaglo J, Thomas KK, Samsunder N, Ngobese H, Mlisana K, Moodley P, Donnell D, Barnabas RV, Naidoo K, Abdool Karim SS, Celum C, Garrett N. Point-of-care HIV viral load testing combined with task shifting to improve treatment outcomes (STREAM): findings from an open-label, non-inferiority, randomised controlled trial. Lancet HIV. 2020 Apr;7(4):e229-e237. doi: 10.1016/S2352-3018(19)30402-3. Epub 2020 Feb 24.
- Nicholas S, Poulet E, Wolters L, Wapling J, Rakesh A, Amoros I, Szumilin E, Gueguen M, Schramm B. Point-of-care viral load monitoring: outcomes from a decentralized HIV programme in Malawi. J Int AIDS Soc. 2019 Aug;22(8):e25387. doi: 10.1002/jia2.25387.
- Villa G, Abdullahi A, Owusu D, Smith C, Azumah M, Sayeed L, Austin H, Awuah D, Beloukas A, Chadwick D, Phillips R, Geretti AM. Determining virological suppression and resuppression by point-of-care viral load testing in a HIV care setting in sub-Saharan Africa. EClinicalMedicine. 2020 Jan 5;18:100231. doi: 10.1016/j.eclinm.2019.12.001. eCollection 2020 Jan.
- Fleuren MA, Paulussen TG, Van Dommelen P, Van Buuren S. Towards a measurement instrument for determinants of innovations. Int J Qual Health Care. 2014 Oct;26(5):501-10. doi: 10.1093/intqhc/mzu060. Epub 2014 Jun 20.
- Baral S, Logie CH, Grosso A, Wirtz AL, Beyrer C. Modified social ecological model: a tool to guide the assessment of the risks and risk contexts of HIV epidemics. BMC Public Health. 2013 May 17;13:482. doi: 10.1186/1471-2458-13-482.
- Fazeli PL, Turan JM, Budhwani H, Smith W, Raper JL, Mugavero MJ, Turan B. Moment-to-moment within-person associations between acts of discrimination and internalized stigma in people living with HIV: An experience sampling study. Stigma Health. 2017 Aug;2(3):216-228. doi: 10.1037/sah0000051. Epub 2016 Aug 8.
- WHO, Child and Adolescent Health and Development, in Progress Report, W.H. Organization, Editor. 2006.
- Decety J. Empathy in Medicine: What It Is, and How Much We Really Need It. Am J Med. 2020 May;133(5):561-566. doi: 10.1016/j.amjmed.2019.12.012. Epub 2020 Jan 15.
- Mariani D, de Azevedo MCVM, Vasconcellos I, Ribeiro L, Alves C, Ferreira OC Jr, Tanuri A. The performance of a new point-of-care HIV virus load technology to identify patients failing antiretroviral treatment. J Clin Virol. 2020 Jan;122:104212. doi: 10.1016/j.jcv.2019.104212. Epub 2019 Nov 9.
- Meggi B, Bollinger T, Zitha A, Mudenyanga C, Vubil A, Mutsaka D, Nhachigule C, Mabunda N, Loquiha O, Kroidl A, Jani IV. Performance of a True Point-of-Care Assay for HIV-1/2 Viral Load Measurement at Antenatal and Postpartum Services. J Acquir Immune Defic Syndr. 2021 May 1;87(1):693-699. doi: 10.1097/QAI.0000000000002621.
- Vasconcellos I, Mariani D, Azevedo MCVM, Ferreira OC Jr, Tanuri A. Development and validation of a simple and rapid way to generate low volume of plasma to be used in point-of-care HIV virus load technologies. Braz J Infect Dis. 2020 Jan-Feb;24(1):30-33. doi: 10.1016/j.bjid.2019.10.010. Epub 2019 Nov 21.
- Fretzayas A, Karpathios T, Dimitriou P, Nicolaidou P, Matsaniotis N. Grading of vesicoureteral reflux by radionuclide cystography. Pediatr Radiol. 1984;14(3):148-50. doi: 10.1007/BF01002299.
Study record dates
Study Major Dates
Study Start (Actual)
Primary Completion (Actual)
Study Completion (Actual)
Study Registration Dates
First Submitted
First Submitted That Met QC Criteria
First Posted (Actual)
Study Record Updates
Last Update Posted (Estimated)
Last Update Submitted That Met QC Criteria
Last Verified
More Information
Terms related to this study
Other Study ID Numbers
- RGPK210909
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
IPD Plan Description
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
product manufactured in and exported from the U.S.
This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.
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Kettering Health NetworkBilimetrix s.r.l.CompletedKernicterus | Point-of-Care Testing | Neonatal Screening | Newborn JaundiceUnited States