The effect of baseline CD4 cell count and HIV-1 viral load on the efficacy and safety of nevirapine or efavirenz-based first-line HAART
Bibliographic record
Abstract
BACKGROUND: A substantial number of patients start their first-line antiretroviral therapy at an advanced stage of an HIV-1 infection. Potential differences between specific drug regimens in antiviral efficacy and safety in these patients are of major importance. METHODS: A post-hoc analysis within the randomized controlled 2NN trial comparing efficacy between regimes containing nevirapine (NVP), efavirenz (EFV), or both, in addition to stavudine and lamivudine. PRIMARY OUTCOME: risk of virologic failure in different strata of baseline CD4 T-lymphocyte counts and plasma HIV-1 RNA concentrations (pVL). Virologic failure: never reaching a pVL < 400 copies/ml, or a rebound to two consecutive values > 400 copies/ml. RESULTS: The risk of virologic failure was increased at very low CD4 counts (< 25 x 10(6) cells/l) compared to CD4 counts > 200 x 10(6) cells/l [hazard ratio (HR), 1.28; 95% confidence interval (CI), 0.93-1.77]. The same was seen for a pVL > or = 100,000 copies/ml compared to a lower pVL (HR, 1.20; CI, 0.96-1.50). There were no statistically significant differences between NVP and EFV in risk of virologic failure within any of the CD4 or pVL strata, although EFV performed slightly better in the low CD4 stratum. The incidence of rash in the NVP group was significantly higher in female patients with higher CD4 cell counts, while adverse events in the EFV group were not associated with CD4 cell count. CONCLUSIONS: Initial antiretroviral therapy including NVP or EFV is effective in patients with an advanced HIV-1 infection. A high baseline CD4 cell count is associated with the occurrence of rash in female patients using NVP.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".