Effect of Baseline Characteristics on the Efficacy and Safety of Once-Daily Darunavir/ Ritonavir in HIV-1–Infected, Treatment-Naïve ARTEMIS Patients at Week 96
Bibliographic record
Abstract
OBJECTIVES: ARTEMIS demonstrated significantly greater efficacy of once-daily darunavir/ritonavir (DRV/r) 800/100 mg versus lopinavir/ritonavir 800/200 mg (total daily dose) in treatment-naïve, HIV-1-infected patients at week 96. The influence of baseline characteristics on efficacy and safety was analyzed in DRV/r patients. METHODS: Patients received once-daily DRV/r plus fixed-dose tenofovir/emtricitabine. Week 96 efficacy and safety data were analyzed by gender (males, n=239; females, n=104), age (≤30, n=115; 31-45, n=175; >45, n=53), race (Asian, n=44; Black, n=80; Caucasian/White, n=137; Hispanic, n=77), and hepatitis B and/or C virus coinfection (n=43). RESULTS: Week 96 virologic response rates (HIV-1 RNA<50 copies/mL) were as follows: gender: 79% for both males and females; age: 72% (≤30), 81% (31-45), and 89% (>45); race: 96% (Asian), 71% (Black), 77% (Caucasian/White), and 79% (Hispanic); coinfection status: 72% (coinfected) and 80% (non-coinfected). The incidence of treatment-related adverse drug reactions (ADRs) and laboratory abnormalities were comparable across gender, age, and race subgroups. Coinfected patients had a higher incidence of liver-related ADRs than non-coinfected patients. CONCLUSIONS: DRV/r 800/100 mg qd is an effective, well-tolerated treatment option for treatment-naïve patients of different gender, age, race, or coinfection status.
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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) | 0.001 | 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".