15 research outputs found
Cohort Profile: The international epidemiological databases to evaluate AIDS (IeDEA) in sub-Saharan Africa
Growth and CD4 patterns of adolescents living with perinatally acquired HIV worldwide, a CIPHER cohort collaboration analysis.
INTRODUCTION
Adolescents living with HIV are subject to multiple co-morbidities, including growth retardation and immunodeficiency. We describe growth and CD4 evolution during adolescence using data from the Collaborative Initiative for Paediatric HIV Education and Research (CIPHER) global project.
METHODS
Data were collected between 1994 and 2015 from 11 CIPHER networks worldwide. Adolescents with perinatally acquired HIV infection (APH) who initiated antiretroviral therapy (ART) before age 10 years, with at least one height or CD4 count measurement while aged 10-17 years, were included. Growth was measured using height-for-age Z-scores (HAZ, stunting if <-2 SD, WHO growth charts). Linear mixed-effects models were used to study the evolution of each outcome between ages 10 and 17. For growth, sex-specific models with fractional polynomials were used to model non-linear relationships for age at ART initiation, HAZ at age 10 and time, defined as current age from 10 to 17 years of age.
RESULTS
A total of 20,939 and 19,557 APH were included for the growth and CD4 analyses, respectively. Half were females, two-thirds lived in East and Southern Africa, and median age at ART initiation ranged from 7 years in sub-Saharan African regions. At age 10, stunting ranged from 6% in North America and Europe to 39% in the Asia-Pacific; 19% overall had CD4 counts <500 cells/mm3 . Across adolescence, higher HAZ was observed in females and among those in high-income countries. APH with stunting at age 10 and those with late ART initiation (after age 5) had the largest HAZ gains during adolescence, but these gains were insufficient to catch-up with non-stunted, early ART-treated adolescents. From age 10 to 16 years, mean CD4 counts declined from 768 to 607 cells/mm3 . This decline was observed across all regions, in males and females.
CONCLUSIONS
Growth patterns during adolescence differed substantially by sex and region, while CD4 patterns were similar, with an observed CD4 decline that needs further investigation. Early diagnosis and timely initiation of treatment in early childhood to prevent growth retardation and immunodeficiency are critical to improving APH growth and CD4 outcomes by the time they reach adulthood
Examining oral pre-exposure prophylaxis (PrEP) literacy among participants in an HIV vaccine trial preparedness cohort study
Background: PrEP literacy is influenced by many factors including the types of information available and how it is interpreted. The level of PrEP literacy may influence acceptability and uptake.
Methods: We conducted 25 in-depth interviews in a HIV vaccine trial preparedness cohort study. We explored what participants knew about PrEP, sources of PrEP knowledge and how much they know about PrEP. We used the framework approach to generate themes for analysis guided by the Social Ecological Model and examined levels of PrEP literacy using the individual and interpersonal constructs of the SEM.
Results: We found that PrEP awareness is strongly influenced by external factors such as social media and how much participants know about HIV treatment and prevention in the local community. However, while participants highlighted the importance of the internet/social media as a source of information about PrEP they talked of low PrEP literacy in their communities. Participants indicated that their own knowledge came as a result of joining the HIV vaccine trial preparedness study. However, some expressed doubts about the effectiveness of the drug and worried about side effects. Participants commented that at the community level PrEP was associated with being sexually active, because it was used to prevent the sexual transmission of HIV. As a result, some participants commented that one could feel judged by the health workers for asking for PrEP at health facilities in the community.
Conclusion: The information collected in this study provided an understanding of the different layers of influence around individuals that are important to address to improve PrEP acceptability and uptake. Our findings can inform strategies to address the barriers to PrEP uptake, particularly at structural and community levels.
Trial registration: https://clinicaltrials.gov/ct2/show/NCT0406688
Cohort Profile: the international epidemiological databases to evaluate AIDS (IeDEA) in sub-Saharan Africa
Age-specific and sex-specific weight gain norms to monitor antiretroviral therapy in children in low-income and middle-income countries.
BACKGROUND
Viral load and CD4% are often not available in resource-limited settings for monitoring children's responses to antiretroviral therapy (ART). We aimed to construct normative curves for weight gain at 6, 12, 18, and 24 months following initiation of ART in children, and to assess the association between poor weight gain and subsequent responses to ART.
DESIGN
Analysis of data from HIV-infected children younger than 10 years old from African and Asian clinics participating in the International epidemiologic Databases to Evaluate AIDS.
METHODS
The generalized additive model for location, scale, and shape was used to construct normative percentile curves for weight gain at 6, 12, 18, and 24 months following ART initiation. Cox proportional models were used to assess the association between lower percentiles (<â50th) of weight gain distribution at the different time points and subsequent death, virological suppression, and virological failure.
RESULTS
Among 7173 children from five regions of the world, 45% were underweight at baseline. Weight gain below the 50th percentile at 6, 12, 18, and 24 months of ART was associated with increased risk of death, independent of baseline characteristics. Poor weight gain was not associated with increased hazards of virological suppression or virological failure.
CONCLUSION
Monitoring weight gain on ART using age-specific and sex-specific normative curves specifically developed for HIV-infected children on ART is a simple, rapid, sustainable tool that can aid in the identification of children who are at increased risk of death in the first year of ART
Retention in Care and Patient-Reported Reasons for Undocumented Transfer or Stopping Care Among HIV-Infected Patients on Antiretroviral Therapy in Eastern Africa: Application of a Sampling-Based Approach.
BackgroundImproving the implementation of the global response to human immunodeficiency virus requires understanding retention after starting antiretroviral therapy (ART), but loss to follow-up undermines assessment of the magnitude of and reasons for stopping care.MethodsWe evaluated adults starting ART over 2.5 years in 14 clinics in Uganda, Tanzania, and Kenya. We traced a random sample of patients lost to follow-up and incorporated updated information in weighted competing risks estimates of retention. Reasons for nonreturn were surveyed.ResultsAmong 18 081 patients, 3150 (18%) were lost to follow-up and 579 (18%) were traced. Of 497 (86%) with ascertained vital status, 340 (69%) were alive and, in 278 (82%) cases, updated care status was obtained. Among all patients initiating ART, weighted estimates incorporating tracing outcomes found that 2 years after ART, 69% were in care at their original clinic, 14% transferred (4% official and 10% unofficial), 6% were alive but out of care, 6% died in care (<60 days after last visit), and 6% died out of care (â„ 60 days after last visit). Among lost patients found in care elsewhere, structural barriers (eg, transportation) were most prevalent (65%), followed by clinic-based (eg, waiting times) (33%) and psychosocial (eg, stigma) (27%). Among patients not in care elsewhere, psychosocial barriers were most prevalent (76%), followed by structural (51%) and clinic based (15%).ConclusionsAccounting for outcomes among those lost to follow-up yields a more informative assessment of retention. Structural barriers contribute most to silent transfers, whereas psychological and social barriers tend to result in longer-term care discontinuation
Retention in Care and Patient-Reported Reasons for Undocumented Transfer or Stopping Care Among HIV-Infected Patients on Antiretroviral Therapy in Eastern Africa: Application of a Sampling-Based Approach
Background.âImproving the implementation of the global response to human immunodeficiency virus requires understanding retention after starting antiretroviral therapy (ART), but loss to follow-up undermines assessment of the magnitude of and reasons for stopping care. Methods.âWe evaluated adults starting ART over 2.5 years in 14 clinics in Uganda, Tanzania, and Kenya. We traced a random sample of patients lost to follow-up and incorporated updated information in weighted competing risks estimates of retention. Reasons for nonreturn were surveyed. Results.âAmong 18 081 patients, 3150 (18%) were lost to follow-up and 579 (18%) were traced. Of 497 (86%) with ascertained vital status, 340 (69%) were alive and, in 278 (82%) cases, updated care status was obtained. Among all patients initiating ART, weighted estimates incorporating tracing outcomes found that 2 years after ART, 69% were in care at their original clinic, 14% transferred (4% official and 10% unofficial), 6% were alive but out of care, 6% died in care (<60 days after last visit), and 6% died out of care (â„60 days after last visit). Among lost patients found in care elsewhere, structural barriers (eg, transportation) were most prevalent (65%), followed by clinic-based (eg, waiting times) (33%) and psychosocial (eg, stigma) (27%). Among patients not in care elsewhere, psychosocial barriers were most prevalent (76%), followed by structural (51%) and clinic based (15%). Conclusions.âAccounting for outcomes among those lost to follow-up yields a more informative assessment of retention. Structural barriers contribute most to silent transfers, whereas psychological and social barriers tend to result in longer-term care discontinuation
Estimation of mortality among HIV-infected people on antiretroviral treatment in east Africa: a sampling based approach in an observational, multisite, cohort study
BackgroundMortality in HIV-infected people after initiation of antiretroviral treatment (ART) in resource-limited settings is an important measure of the effectiveness and comparative effectiveness of the global public health response. Substantial loss to follow-up precludes accurate accounting of deaths and limits our understanding of effectiveness. We aimed to provide a better understanding of mortality at scale and, by extension, the effectiveness and comparative effectiveness of public health ART treatment in east Africa.MethodsIn 14 clinics in five settings in Kenya, Uganda, and Tanzania, we intensively traced a sample of patients randomly selected using a random number generator, who were infected with HIV and on ART and who were lost to follow-up (>90 days late for last scheduled visit). We incorporated the vital status outcomes for these patients into analyses of the entire clinic population through probability-weighted survival analyses.FindingsWe followed 34â277 adults on ART from Mbarara and Kampala in Uganda, Eldoret, and Kisumu in Kenya, and Morogoro in Tanzania. The median age was 35 years (IQR 30-42), 11â628 (34%) were men, and median CD4 count count before therapy was 154 cells per ÎŒL (IQR 70-234). 5780 patients (17%) were lost to follow-up, 991 (17%) were selected for tracing between June 10, 2011, and Aug 27, 2012, and vital status was ascertained for 860 (87%). With incorporation of outcomes from the patients lost to follow-up, estimated 3 year mortality increased from 3·9% (95% CI 3·6-4·2) to 12·5% (11·8-13·3). The sample-corrected, unadjusted 3 year mortality across settings was lowest in Mbarara (7·2%) and highest in Morogoro (23·6%). After adjustment for age, sex, CD4 count before therapy, and WHO stage, the sample-corrected hazard ratio comparing the settings with highest and lowest mortalities was 2·2 (95% CI 1·5-3·4) and the risk difference for death at 3 years was 11% (95% CI 5·0-17·7).InterpretationA sampling-based approach is widely feasible and important to an understanding of mortality after initiation of ART. After adjustment for measured biological drivers, mortality differs substantially across settings despite delivery of a similar clinical package of treatment. Implementation research to understand the systems, community, and patients' behaviours driving these differences is urgently needed.FundingThe US National Institutes of Health and President's Emergency Fund for AIDS Relief
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The Causal Effect of Tracing by Peer Health Workers on Return to Clinic Among Patients Who Were Lost to Follow-up From Antiretroviral Therapy in Eastern Africa: A "Natural Experiment" Arising From Surveillance of Lost Patients.
Background.The effect of tracing human immunodeficiency virus (HIV)-infected patients who are lost to follow-up (LTFU) on reengagement has not been rigorously assessed. We carried out an ex post analysis of a surveillance study in which LTFU patients were randomly selected for tracing to identify the effect of tracing on reengagement.Methods.We evaluated HIV-infected adults on antiretroviral therapy who were LTFU (>90 days late for last visit) at 14 clinics in Uganda, Kenya, and Tanzania. A random sample of LTFU patients was selected for tracing by peer health workers. We assessed the effect of selection for tracing using Kaplan-Meier estimates of reengagement among all patients as well as the subset of LTFU patients who were alive, contacted in person by the tracer, and out of care.Results.Of 5781 eligible patients, 991 (17%) were randomly selected for tracing. One year after selection for tracing, 13.3% (95% confidence interval [CI], 11.1%-15.3%) of those selected for tracing returned compared with 10.0% (95% CI, 9.1%-10.8%) of those not randomly selected, an adjusted risk difference of 3.0% (95% CI, .7%-5.3%). Among patients found to be alive, personally contacted, and out of care, tracing increased the absolute probability of return at 1 year by 22% (95% CI, 7.1%-36.2%). The effect of tracing on rate of return to clinic decayed with a half-life of 7.0 days after tracing (95% CI, 2.6 %-12.9%).Conclusions.Tracing interventions increase reengagement, but developing methods for targeting LTFU patients most likely to benefit can make this practice more efficient
Patient-reported factors associated with reengagement among HIV-infected patients disengaged from care in East Africa
OBJECTIVE:
Engagement in care is key to successful HIV treatment in resource-limited settings; yet little is known about the magnitude and determinants of reengagement among patients out of care. We assessed patient-reported reasons for not returning to clinic, identified latent variables underlying these reasons, and examined their influence on subsequent care reengagement.
DESIGN:
We used data from the East Africa International Epidemiologic Databases to Evaluate AIDS to identify a cohort of patients disengaged from care (>3 months late for last appointment, reporting no HIV care in preceding 3 months) (nâ=â430) who were interviewed about reasons why they stopped care. Among the 399 patients for whom follow-up data were available, 104 returned to clinic within a median observation time of 273 days (interquartile range: 165-325).
METHODS:
We conducted exploratory and confirmatory factor analyses (EFA, CFA) to identify latent variables underlying patient-reported reasons, then used these factors as predictors of time to clinic return in adjusted Cox regression models.
RESULTS:
EFA and CFA findings suggested a six-factor structure that lent coherence to the range of barriers and motivations underlying care disengagement, including poverty, transport costs, and interference with work responsibilities; health system 'failures,' including poor treatment by providers; fearing disclosure of HIV status; feeling healthy; and treatment fatigue/seeking spiritual alternatives to medicine. Factors related to poverty and poor treatment predicted higher rate of return to clinic, whereas the treatment fatigue factor was suggestive of a reduced rate of return.
CONCLUSION:
Certain barriers to reengagement appear easier to overcome than factors such as treatment fatigue. Further research will be needed to identify the easiest, least expensive interventions to reengage patients lost to HIV care systems. Interpersonal interventions may continue to play an important role in addressing psychological barriers to retention