Correlates of Efavirenz Exposure in Chilean Patients Affected With Human Immunodeficiency Virus Reveals a Novel Association With a Polymorphism in the Constitutive Androstane Receptor
Bibliographic record
Abstract
OBJECTIVE: To explore the effect of demographics and single-nucleotide polymorphisms in cytochrome P450 (CYP) 2B6, 2A6, UDP-glucuronosyltransferase (UGT) 2B7, and the constitutive androstane receptor (CAR) genes on efavirenz pharmacokinetics in a Chilean cohort affected with human immunodeficiency virus. METHODS: Timed plasma samples obtained throughout the dosing interval were analyzed for efavirenz concentrations with liquid chromatography/tandem mass spectrometry. DNA from whole-blood samples was used for genetic analysis. Data were analyzed using a Mann-Whitney statistical test; furthermore, a Pearson or Spearman correlation was used. A multivariate analysis was then conducted using multiple linear regression by best subset analysis. RESULTS: Overall 219 patients were included, 208 patients had measurable efavirenz levels and available genetic samples. The overall median (interquartile range) of efavirenz concentration was 2.6 (2.1-3.7) mcg/mL. In multivariate regression analysis, CYP2B6 516G>T (P < 0.0001) and CAR rs2307424 C>T (P = 0.002) were significantly related to efavirenz plasma concentrations. CONCLUSION: This novel association between CAR rs2307424 and efavirenz plasma concentrations now requires validation in other cohorts.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| 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) | 0.002 | 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".