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Record W2121928714 · doi:10.1128/aac.00449-09

Differential Effects of Tipranavir plus Ritonavir on Atorvastatin or Rosuvastatin Pharmacokinetics in Healthy Volunteers

2009· article· en· W2121928714 on OpenAlexaff
Paul A. Pham, C. J. L. la Porte, Lawrence Lee, Rolf van Heeswijk, John P. Sabo, M. Elgadi, Peter J. Piliero, Patricia Barditch‐Crovo, Edward J. Fuchs, Charles Flexner, D. William Cameron

Bibliographic record

VenueAntimicrobial Agents and Chemotherapy · 2009
Typearticle
Languageen
FieldMedicine
TopicHepatitis C virus research
Canadian institutionsBoehringer Ingelheim (Canada)Ottawa HospitalUniversity of Ottawa
FundersNational Center for Research Resources
KeywordsRitonavirRosuvastatinAtorvastatinPharmacokineticsPharmacologyMedicineMetabolic clearance rateVirologyHuman immunodeficiency virus (HIV)Viral loadAntiretroviral therapy

Abstract

fetched live from OpenAlex

To identify pharmacokinetic (PK) drug-drug interactions between tipranavir-ritonavir (TPV/r) and rosuvastatin and atorvastatin, we conducted two prospective, open-label, single-arm, two-period studies. The geometric mean (GM) ratio was 1.37 (90% confidence interval [CI], 1.15 to 1.62) for the area under the concentration-time curve (AUC) for rosuvastatin and 2.23 (90% CI, 1.83 to 2.72) for the maximum concentration of drug in serum (Cmax) for rosuvastatin with TPV/r at steady state versus alone. The GM ratio was 9.36 (90% CI, 8.02 to 10.94) for the AUC of atorvastatin and 8.61 (90% CI, 7.25 to 10.21) for the Cmax of atorvastatin with TPV/r at steady state versus alone. Tipranavir PK parameters were not affected by single-dose rosuvastatin or atorvastatin. Mild gastrointestinal intolerance, headache, and mild reversible liver enzyme elevations (grade 1 and 2) were the most commonly reported adverse drug reactions. Based on these interactions, we recommend low initial doses of rosuvastatin (5 mg) and atorvastatin (10 mg), with careful clinical monitoring of rosuvastatin- or atorvastatin-related adverse events when combined with TPV/r.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.550
Threshold uncertainty score0.736

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.022
GPT teacher head0.343
Teacher spread0.321 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations66
Published2009
Admission routes1
Has abstractyes

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