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Record W2008486886 · doi:10.1177/0091270009337946

Effect of Age, Weight, and CYP2C19 Genotype on Escitalopram Exposure

2009· article· en· W2008486886 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThe Journal of Clinical Pharmacology · 2009
Typearticle
Languageen
FieldMedicine
TopicTreatment of Major Depression
Canadian institutionsUniversity of TorontoCentre for Addiction and Mental Health
FundersNational Institute of Mental Health
KeywordsEscitalopramBody mass indexCYP2C19PopulationInternal medicineVolume of distributionDemographyMedicinePharmacokineticsAntidepressant

Abstract

fetched live from OpenAlex

The purpose of this study was to characterize escitalopram population pharmacokinetics (PK) in patients treated for major depression in a cross-national, US-Italian clinical trial. Data from the 2 sites participating in this trial, conducted at Pittsburgh (United States) and Pisa (Italy), were used. Patients received 5, 10, 15, or 20 mg of escitalopram daily for a minimum of 32 weeks. Nonlinear mixed effects modeling was used to model the PK characteristics of escitalopram. One- and 2-compartment models with various random effect implementations were evaluated during model development. Objective function values and goodness-of-fit plots were used as model selection criteria. CYP2C19 genotype, age, weight, body mass index, sex, race, and clinical site were evaluated as possible covariates. In total, 320 plasma concentrations from 105 Pittsburgh patients and 153 plasma concentrations from 67 Pisa patients were available for the PK model development. A 1-compartmental model with linear elimination and proportional error best described the data. Apparent clearance (CL/F) and volume of distribution (V/F) for escitalopram without including any covariates in the patient population were 23.5 L/h and 884 L, respectively. CYP2C19 genotype, weight, and age had a significant effect on CL/F, and patient body mass index affected estimated V/F. Patients from Pisa, Italy, had significantly lower clearances than patients from Pittsburgh that disappeared after controlling for patient CYP2C19 genotype, age, and weight. Postprocessed individual empirical Bayes estimates on clearance for the 172 patients show that patients without allele CYP2C19(*)2 or (*)3 (n = 82) cleared escitalopram 33.7% faster than patients with heterogeneous or homogeneous (*)2 or (*)3 ((*)17/(*)2, (*)17/(*)3, (*)1/(*)2, (*)1/(*)3, (*)2/(*)2, (*)2/(*)3, and (*)3/(*)3, n = 46). CL/F significantly decreased with increasing patient age. Patients younger than 30 years (n = 45) cleared escitalopram 20.7% and 42.7% faster than patients aged 30 to 50 years (n = 84) and older than 50 years of age (n = 43), respectively. CYP2C19 genotype, age, and weight strongly influenced the CL/F of escitalopram. These variables may affect patient tolerance of this antidepressant and may provide important information in the effort to tailor treatments to patients' individual needs.

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.

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)0.002
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 score0.683
Threshold uncertainty score0.285

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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)0.0000.000

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 head0.038
GPT teacher head0.450
Teacher spread0.412 · 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