Prospective, Randomized, Open Label Trial of Efavirenz vs Lopinavir/Ritonavir in HIV+ Treatment-Naive Subjects With CD4+<200 cell/mm3 in Mexico
Bibliographic record
Abstract
OBJECTIVE: To compare the efficacy of efavirenz (EFV) vs lopinavir/ritonavir (LPV/r) in combination with azidothymidine/lamivudine in antiretroviral therapy naive, HIV+ individuals presenting for care with CD4 counts <200/mm. METHODS: Prospective, randomized, open label, multicenter trial in Mexico. HIV-infected subjects with CD4 <200/mm were randomized to receive open label EFV or LPV/r plus azidothymidine/lamivudine (fixed-dose combination) for 48 weeks. Randomization was stratified by baseline CD4 cell count (< or =100 or >100/mm). The primary endpoint was the percentage of patients with plasma HIV-1 RNA <50 copies/mL at 48 weeks by intention-to-treat analysis. RESULTS: A total of 189 patients (85% men) were randomized to receive EFV (95) or LPV/r (94). Median baseline CD4 were 64 and 52/mm, respectively (P = not significant). At week 48, by intention-to-treat analysis, 70% of EFV and 53% of LPV/r patients achieved HIV-1 RNA <50 copies/mL [estimated difference 17% (95% confidence interval 3.5 to 31), P = 0.013]. The proportion with HIV-1 RNA <400 copies/mL was 73% with EFV and 65% with LPV/r (P = 0.25). Virologic failure occurred in 7 patients on EFV and 17 on LPV/r. Mean CD4 count increases (cells/mm) were 234 for EFV and 239 for LPV/r. Mean change in total cholesterol and triglyceride levels were 50 and 48 mg/dL in EFV and 63 and 116 mg/dL in LPV/r (P = 0.24 and P < 0.01). CONCLUSIONS: In these very advanced HIV-infected ARV-naive subjects, EFV-based highly active antiretroviral therapy had superior virologic efficacy than LPV/r-based highly active antiretroviral therapy, with a more favorable lipid profile.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".