Immunologic, Virologic, and Clinical Consequences of Episodes of Transient Viremia During Suppressive Combination Antiretroviral Therapy
Bibliographic record
Abstract
OBJECTIVE: To investigate immunologic, virologic, and clinical consequences of episodes of transient viremia in patients with sustained virologic suppression. METHODS: From the AIDS Therapy Evaluation Project, Netherlands cohort, 4447 previously therapy-naive patients were selected who were on continuous combination antiretroviral therapy and had initial success (2 consecutive HIV RNA measurements <50 copies/mL). During episodes of viral suppression (RNA <50 copies/mL), low-level viremia (RNA 50 to 1000 copies/mL), or high-level viremia (RNA >1000 copies/mL) after initial success, the occurrence of therapy changes, drug resistance, and clinical events was assessed. RESULTS: During 11,187 person-years of follow-up, 1281 (28.8%) patients had at least 1 RNA measurement >50 copies/mL. Among 8069 episodes, there were 5989 (74.2%) episodes of suppression, 1711 (21.2%) episodes of low-level viremia, and 369 (4.6%) episodes of high-level viremia. Most episodes of low-level viremia consisted of < or =2 RNA measurements (93.7%), were without clinical events or therapy changes (79.6%), and were without changes in CD4 cell counts. Therapy changes (52.3% of episodes) and resistance (23.3%) were frequently observed during high-level viremia. CONCLUSIONS: Episodes of low-level viremia are frequent and short lasting, and the low proportion of episodes with clinical events suggests that leaving therapy unchanged is a clinically acceptable strategy. In contrast, high-level viremia is associated with resistance and is often followed by therapy changes.
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 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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".