Simplification with abacavir-based triple nucleoside therapy versus continued protease inhibitor-based highly active antiretroviral therapy in HIV-1-infected patients with undetectable plasma HIV-1 RNA
Bibliographic record
Abstract
OBJECTIVE: To assess the antiviral efficacy, safety and adherence in patients switched to an abacavir-containing nucleoside reverse transcriptase inhibitor (NRTI) regimen after long-term HIV-1 RNA suppression with a dual NRTI/protease inhibitor (PI) combination. METHODS: In an open-label, multicentre study, patients receiving 2NRTI plus PI for at least 6 months, with a history of undetectable plasma HIV-1 RNA since the initiation of therapy and plasma HIV-1 RNA < 50 copies/ml at screening, were randomly assigned to replace the PI with abacavir (n = 105) or continue the same treatment (n = 106). Clinical assessments included plasma HIV-1 RNA, chemistry, haematology, lymphocyte counts, and adverse event reports. Adherence to treatment was assessed by patient self-report. RESULTS: A significantly longer time to treatment failure was demonstrated in the abacavir arm compared with the PI arm (P = 0.03) while treatment failure was experienced by significantly more patients in the PI arm: 24 (23%) versus 12 (12%) (P = 0.03). Therapy-limiting toxicity led to treatment failure in eight versus 14 cases in the abacavir and PI arms, respectively, whereas virological rebound was the cause in four versus two cases. Significant reductions in cholesterol and non-fasting triglyceride plasma levels at 48 weeks were observed in the abacavir arm (P < 0.001 andP = 0.035, respectively). The number of patients reporting no difficulty in taking their therapy showed a marked increase from baseline in the abacavir arm. CONCLUSION: The replacement of PI by abacavir in a triple combination regimen following prolonged suppression of plasma HIV-1 RNA provides continued virological suppression, significant improvements in lipid abnormalities and enhanced ease of dosing.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 |
| 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".