Early Initiation Rather Than Prolonged Duration of Antiretroviral Therapy in HIV Infection Contributes to the Normalization of CD8 T-Cell Counts
Bibliographic record
Abstract
BACKGROUND: CD8 T-cell counts remain elevated in human immunodeficiency virus (HIV) infection even after long-term antiretroviral therapy (ART), which is associated with an increased risk of non-AIDS-related events. We assessed the impact of ART initiation in early versus chronic HIV infection on trajectories of CD8 cell counts over time. METHODS: Of 280 individuals enrolled during primary HIV infection (PHI), 251 were followed up for 24 months; 84 started ART before 6 months of infection (eART), 49 started between 6 and 24 months, and 118 remained untreated. Plasma HIV viral load (VL), CD4 and CD8 cell counts were assessed at each study visit. CD8 counts were also examined in 182 age-matched HIV-infected individuals who started ART during chronic infection and maintained undetectable plasma VL for ≥5 years. RESULTS: At PHI baseline, higher CD8 cell counts were associated with more recent infection (P = .02), higher CD4 cell counts (P < .001), and higher VL (P < .001). The CD8 count in the eART group decreased from 797 to 588 cells/µL over 24 months (P < .001), to a level lower than that in untreated PHI (834 cells/µL; P = .004) or in long-term-treated patients with chronic HIV infection (743 cells/µL; P = .047). More prominent CD4 T-cell recovery was observed in the eART group than in the delayed ART group. CONCLUSIONS: ART initiated in early HIV infection is associated with improved resolution of CD8 T-cell elevation compared with long-term ART initiated in chronic infection. Early ART may help reduce the risk of non-AIDS-related events by alleviating this elevation.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.002 | 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".