Transient Relapses (“Blips”) of Plasma HIV RNA Levels During HAART Are Associated With Drug Resistance
Bibliographic record
Abstract
INTRODUCTION: In a large number of patients on HAART who achieved plasma HIV RNA levels below the limit of detection (50 copies/ml), transient relapses of HIV RNA levels ("blips") are observed. OBJECTIVE: To determine whether relapses of plasma HIV RNA during HAART are associated with development of drug resistance. METHODS: Plasma samples from 15 patients with a transient viral load relapse during HAART were studied. All regimens contained lamivudine (3TC). We used an ultrasensitive sequence approach to analyze the presence of drug resistance mutations during the relapse. RESULTS: The median plasma HIV RNA load of the relapse was 76 copies/ml (range 50-1239). In 11 of 15 cases, a genotype of HIV could be obtained. Mutations in the RT and protease gene conferring resistance to one or more drugs were observed in 8 of 11 patients, 6 of whom had the M184V substitution. During a median follow-up of 27 months after the relapse, plasma HIV RNA levels remained undetectable in 13 of 15 patients. CONCLUSIONS: Plasma HIV RNA blips during HAART can be associated with selection of drug-resistant HIV. This indicates that viral replication may occur during HAART, probably caused by a temporary decrease in active drug concentrations. A blip containing only wild-type virus is not necessarily caused by viral replication. In this situation the raise of HIV RNA could also originate from release of wild-type viruses, caused by activation of the latent virus reservoir. Independent of the mechanism, blips did not preclude successful inhibition of viral replication during 2-year follow-up in the majority of these cases.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".