Atorvastatin reduces <scp>T</scp>‐cell activation and exhaustion among <scp>HIV</scp>‐infected c<scp>ART</scp>‐treated suboptimal immune responders in <scp>U</scp>ganda: a randomised crossover placebo‐controlled trial
Bibliographic record
Abstract
OBJECTIVE: T-cell activation independently predicts mortality, poor immune recovery and non-AIDS illnesses during combination antiretroviral therapy (cART). Atorvastatin showed anti-immune activation effects among HIV-infected cART-naïve individuals. We investigated whether adjunct atorvastatin therapy reduces T-cell activation among cART-treated adults with suboptimal immune recovery. METHODS: A randomised double-blind placebo-controlled crossover trial, of atorvastatin 80 mg daily vs. placebo for 12 weeks, was conducted among individuals with CD4 increase <295 cells/μl after seven years of suppressive cART. Change in T-cell activation (CD3 + CD4 + /CD8 + CD38 + HLADR+) and in T-cell exhaustion (CD3 + CD4 + /CD8 + PD1 + ) was measured using flow cytometry. RESULTS: Thirty patients were randomised, 15 to each arm. Atorvastatin resulted in a 28% greater reduction in CD4 T-cell activation (60% reduction) than placebo (32% reduction); P = 0.001. Atorvastatin also resulted in a 35% greater reduction in CD8-T-cell activation than placebo (49% vs. 14%, P = 0.0009), CD4 T-cell exhaustion (27% vs. 17% in placebo), P = 0.001 and CD8 T-cell exhaustion (27% vs. 16%), P = 0.004. There was no carry-over/period effect. Expected adverse events were comparable in both groups, and no serious adverse events were reported. CONCLUSION: Atorvastatin reduced T-cell immune activation and exhaustion among cART-treated adults in a Ugandan cohort. Atorvastatin adjunct therapy should be explored as a strategy to improve HIV treatment outcomes among people living with HIV in sub-Saharan Africa.
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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 | 0.002 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".