Impact of a modified directly administered antiretroviral treatment intervention on virological outcome in HIV‐infected patients treated in Burkina Faso and Mali
Bibliographic record
Abstract
OBJECTIVE: This study explores whether viral load measurements can be used in resource-limited settings to target those in need of adherence assistance. It was hypothesized that high plasma viral loads (pVLs) (>/=500 HIV-1 RNA copies/mL) were the result of poor antiretroviral therapy adherence and amenable to improvement with adherence assistance. DESIGN: A single-arm, multicentre pilot study was conducted from November 2003 to March 2004 on 606 treatment-experienced patients who had initiated an antiretroviral regimen in Mali and Burkina Faso >/=6 months before study enrolment. In these patients, those whose pVL was >/=500 copies/mL were offered 1 month of modified directly administered antiretroviral treatment (mDAART) with weekly follow-up visits from pharmacists or adherence counsellors. METHODS: An adherence questionnaire was given to all cohort patients and viral load was used to screen for patients with >/=500 copies/mL. mDAART participants included cohort patients with >/=500 copies/mL, who completed the adherence questionnaire. Genotypic analyses were conducted on samples taken prior to and after the intervention. The intervention was considered effective when there was a decrease of >/=1 log(10) in pVL. RESULTS: mDAART was effective in over one-third of the intervention participants, while in two-thirds no decrease in pVL was observed. The majority of mDAART participants had major resistance mutations. CONCLUSIONS: pVL measurement was useful to identify patients who needed adherence assistance. However, because it was performed >/=6 months after starting treatment, mDAART came too late for most participants, as they had already developed important resistance mutations that might have been avoided with better laboratory monitoring.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".