Determinants of adherence to highly active antiretroviral therapy among HIV-1-infected patients in Côte d'Ivoire
Bibliographic record
Abstract
OBJECTIVE: To assess adherence to HAART and to determine factors associated with poor adherence among HIV-1-infected patients in Abidjan, Côte d'Ivoire. METHODS: A prospective observational study of 614 consecutive patients attending an HIV/AIDS outpatient clinic. Adherence was measured twice at 3-month intervals by self-report of missing doses over 4 days. An adherence level of less than 95% was defined as poor adherence. We used generalized estimating equation models for binomial distribution with repeated measures for data analysis. RESULTS: Of the 591 subjects who completed the study, 74.3% reported adherence levels of 95% or greater. Six factors were independently related to poor adherence: age less than 35 years [relative risk (RR) 1.45; 95% confidence interval (CI) 1.17-1.79], absence of social support (RR 1.66; 95% CI 1.24-2.24), number of daily pills 10 or more (RR 1.47; 95% CI 1.14-1.91), time of adherence assessment (first versus second time assessment RR 1.36; 95% CI 1.12-1.66), CD4 cell count of 250 cells/mul or greater (RR 1.43; 95% CI 1.10-1.88), and not being less worried about HIV infection now that treatments have improved (RR 1.26; 95% CI 1.01-1.58). Drug supply interruptions in the pharmacies were reported by 10.0% of the non-adherent patients as the reason for missing pills. CONCLUSION: Psychosocial factors were found to impact adherence and should be analysed in more detail by further studies. Scaling up antiretroviral therapy in sub-Saharan Africa should be preceded by reliable drug supply and distribution systems.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".