Valproic acid in association with highly active antiretroviral therapy for reducing systemic <scp>HIV</scp>‐1 reservoirs: results from a multicentre randomized clinical study
Bibliographic record
Abstract
OBJECTIVES: Conflicting results have been reported regarding the ability of valproic acid (VPA) to reduce the size of HIV reservoirs in patients receiving suppressive highly active antiretroviral therapy (HAART). In a randomized multicentre, cross-over study, we assessed whether adding VPA to stable HAART could potentially reduce the size of the latent viral reservoir in CD4 T cells of chronically infected patients. METHODS: A total of 56 virologically suppressed patients were randomly assigned either to receive VPA plus HAART for 16 weeks followed by HAART alone for 32 weeks (arm 1; n = 27) or to receive HAART alone for 16 weeks and then VPA plus HAART for 32 weeks (arm 2; n = 29). VPA was administered at a dose of 500 mg twice a day (bid) and was adjusted to the therapeutic range. A quantitative culture assay was used to assess HIV reservoirs in CD4 T cells at baseline and at weeks 16 and 48. RESULTS: No significant reductions in the frequency of CD4 T cells harbouring replication-competent HIV after 16 and 32 weeks of VPA therapy were observed. In arm 1, median (range) values of IU per log(10) billion (IUPB) cells were 2.55 (range 1.20-4.20), 1.80 (range 1.0-4.70) and 2.70 (range 1.0-3.90; P = 0.87) for baseline, week 16 and week 48, respectively. In arm 2, median values of IUPB were 2.55 (range 1.20-4.65), 1.64 (range 1.0-3.94) and 2.51 (range 1.0-4.48; P = 0.50) for baseline, week 16 and week 48, respectively. CONCLUSIONS: Our study demonstrates that adding VPA to stable HAART does not reduce the latent HIV reservoir in virally suppressed patients.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".