Adherence to Antiretroviral Therapy in Sub-Saharan Africa and North America
Bibliographic record
Abstract
CONTEXT: Adherence to antiretroviral therapy is a powerful predictor of survival for individuals living with human immunodeficiency virus (HIV) and AIDS. Concerns about incomplete adherence among patients living in poverty have been an important consideration in expanding the access to antiretroviral therapy in sub-Saharan Africa. OBJECTIVE: To evaluate estimates of antiretroviral therapy adherence in sub-Saharan Africa and North America. DATA SOURCES: Eleven electronic databases were searched along with major conference abstract databases (inclusion dates: inception of database up until April 18, 2006) for all English-language articles and abstracts; and researchers and treatment advocacy groups were contacted. Study Selection and Data Abstraction To best reflect the general population, studies of mixed populations in both North America and Africa were selected. Studies evaluating specific populations such as men only, homeless individuals, or drug users, were excluded. The data were abstracted in duplicate on study adherence outcomes, thresholds used to determine adherence, and characteristics of the populations. A random-effects meta-analysis was performed in which heterogeneity was examined using multivariable random-effects logistic regression. A sensitivity analysis was performed using Bayesian methods. DATA SYNTHESIS: Thirty-one studies from North America (28 full-text articles and 3 abstracts) and 27 studies (9 full-text articles and 18 abstracts) from sub-Saharan Africa were included. African studies represented 12 sub-Saharan countries. Of the North American studies, 71% used patient self-report to assess adherence; this was true of 66% of the African assessments. Studies reported similar thresholds for adherence monitoring (eg, 100%, >95%, >90%, >80%). A pooled analysis of the North American studies (17,573 patients total) indicated a pooled estimate of 55% (95% confidence interval, 49%-62%; I2, 98.6%) of the populations achieving adequate levels of adherence. Our pooled analysis of African studies (12,116 patients total) indicated a pooled estimate of 77% (95% confidence interval, 68%-85%; I2, 98.4%). Study continent, adherence thresholds, and study quality were significant predictors of heterogeneity. Bayesian analysis was used as an alternative statistical method for combining adherence rates and provided similar findings. CONCLUSION: Our findings indicate that favorable levels of adherence, much of which was assessed via patient self-report, can be achieved in sub-Saharan African settings and that adherence remains a concern in North America.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.011 | 0.016 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".