High exposure to nevirapine in plasma is associated with an improved virological response in HIV-1-infected individuals
Bibliographic record
Abstract
OBJECTIVE: To explore relationships between exposure to nevirapine and the virological response in HIV-1-infected individuals participating in the INCAS trial. METHODS: The elimination rate constant of plasma HIV-1 RNA (k) was calculated during the first 2 weeks of treatment with nevirapine, zidovudine and didanosine in 51 antiretroviral-naive HIV-1-infected patients. The relationships between the value of k, the time to reach an undetectable HIV-1 RNA concentration in plasma (< 20 copies/ml) and the success of therapy after 52 weeks of treatment as dependent variables and the exposure to nevirapine, baseline HIV-1 RNA and baseline CD4 cell count as independent variables, were explored using linear regression analyses, proportional hazard models and logistic analyses, respectively. RESULTS: The value of k for HIV-1 RNA in plasma was positively and significantly associated with the mean plasma nevirapine concentration during the first 2 weeks of therapy (P = 0.011) and the baseline HIV-1 RNA (P = 0.008). Patients with a higher exposure to nevirapine reached undetectable levels of HIV-1 RNA in plasma more rapidly (P = 0.03). From 12 weeks on, the median nevirapine plasma concentration was significantly correlated with success of therapy after 52 weeks (P < 0.02). CONCLUSIONS: A high exposure to nevirapine (in a twice daily regimen) is significantly associated with improved virological response in the short as well as in the long term. These findings suggest that optimization of nevirapine concentration might be used as a tool to improve virological outcome in (antiretroviral-naive) patients treated with nevirapine.
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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 | 0.003 |
| 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) | 0.001 | 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".