Hepatotoxicity of nevirapine in virologically suppressed patients according to gender and CD4 cell counts<sup>*</sup>
Bibliographic record
Abstract
OBJECTIVES: A warning advising a higher risk of hepatotoxicity in antiretroviral-naive patients starting a nevirapine-containing combination antiretroviral therapy (NcART) has been issued by health authorities. It is unclear whether this higher risk also applies to stable virologically suppressed patients starting NcART. METHODS: We performed a meta-analysis of published randomized studies including virologically suppressed patients who switched to NcART with a follow-up >or=3 months. CD4 cell cell counts were classified as high (HCD4) (400 cells/microL for males and 250 cells/microL for females) or low (LCD4). The main endpoint was hepatotoxicity within the first 3 months. RESULTS: Four studies with a pooled total of 410 patients were included. The risk of hepatotoxicity within the first 3 months was 2% and 4% in the LCD4 and HCD4 groups, respectively, with a combined odds ratio of 1.46 [95% confidence interval (CI) 0.43-4.98; P=0.54]. The risk of hepatotoxicity at any point during the study was similar in both groups, with a combined hazard ratio of 0.8 (95% CI 0.3-2.5; P=0.80). CONCLUSIONS: In our study, virologically suppressed patients switching to nevirapine did not have a significantly higher risk of hepatotoxicity or rash when stratified by gender and CD4 cell count, although small differences may have gone undetected because of the sample size limitation.
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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 | 0.009 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.022 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".