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Record W3133802300 · doi:10.1002/cpdd.926

Pharmacokinetic Interaction Among Ezetimibe, Rosuvastatin, and Telmisartan

2021· article· en· W3133802300 on OpenAlexaff
Ki Young Huh, Sang Won Lee, Kyung Tae Kim, In‐Jin Jang, Seung‐Hwan Lee

Bibliographic record

VenueClinical Pharmacology in Drug Development · 2021
Typearticle
Languageen
FieldMedicine
TopicLipoproteins and Cardiovascular Health
Canadian institutionsMicropharma (Canada)
Fundersnot available
KeywordsMedicineTelmisartanRosuvastatinEzetimibePharmacokinetic interactionPharmacologyPharmacokineticsInternal medicineDrug interactionStatinBlood pressure

Abstract

fetched live from OpenAlex

Abstract To evaluate the pharmacokinetic interactions among rosuvastatin, ezetimibe, and telmisartan, a randomized, open‐label, 3‐period, 6‐sequence crossover study was conducted in healthy subjects. Subjects received one of the following treatments once daily for 7 days in each period with a 1‐week washout: a fixed‐dose combination of ezetimibe/rosuvastatin 10/20 mg, telmisartan 80 mg, combination therapy of ezetimibe/rosuvastatin 10/20 mg, or telmisartan 80 mg. Blood samples were collected up to 24 hours postdose at steady state. Geometric mean ratios (GMRs) and their 90% confidence intervals (CIs) of the combination therapy to monotherapy for the maximum plasma concentration (C max,ss ), and the area under the time‐concentration curve within a dosing interval at steady state (AUC tau,ss ) were estimated. Among the 36 randomized subjects, 31 subjects completed the study. The GMRs and 90%CIs of C max,ss and AUC tau,ss of total ezetimibe were not significantly altered. The C max,ss of free ezetimibe was increased (GMR, 1.85; 90%CI, 1.56–2.19) but not for the AUC tau,ss (GMR, 1.16; 90%CI, 1.06–1.26). Similarly, the C max,ss of rosuvastatin was increased (GMR, 2.13; 90%CI, 1.88–2.43) without a change in the AUC tau,ss (GMR, 1.09; 90%CI, 1.03–1.15). The C max,ss (GMR, 1.16; 90%CI, 1.01–1.32) and AUC tau,ss (GMR, 1.26; 90%CI, 1.17–1.37) of telmisartan were slightly increased. Considering the therapeutic range of the components, the interaction would have limited clinical impact.

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.533
Threshold uncertainty score0.734

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.037
GPT teacher head0.394
Teacher spread0.357 · 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 designObservational
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

Citations6
Published2021
Admission routes1
Has abstractyes

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