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Record W2561831579 · doi:10.1002/cpt.597

Clinical pharmacogenetics implementation consortium guideline (CPIC) for <i>CYP2D6</i> and <i>CYP2C19</i> genotypes and dosing of tricyclic antidepressants: 2016 update

2016· article· en· W2561831579 on OpenAlexafffund
JK Hicks, Katrin Sangkuhl, JJ Swen, VL Ellingrod, Müller Dj, Kazutaka Shimoda, JR Bishop, E D Kharasch, TC Skaar, Andrea Gaedigk, Henry M. Dunnenberger, Teri E. Klein, KE Caudle, Julia Stingl

Bibliographic record

VenueClinical Pharmacology & Therapeutics · 2016
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicPharmacogenetics and Drug Metabolism
Canadian institutionsUniversity of TorontoCentre for Addiction and Mental Health
FundersNational Institute on Drug AbuseCanadian Institutes of Health ResearchNational Institute of General Medical SciencesNational Institute of Mental HealthAgency for Healthcare Research and QualityNational Institutes of Health
KeywordsDosingPharmacogeneticsGuidelineCYP2C19CYP2D6TricyclicMedicinePharmacologyInternal medicineGenotypeBiologyGenetics

Abstract

fetched live from OpenAlex

CYP2D6 and CYP2C19 polymorphisms affect the exposure, efficacy and safety of tricyclic antidepressants (TCAs), with some drugs being affected by CYP2D6 only (e.g., nortriptyline and desipramine) and others by both polymorphic enzymes (e.g., amitriptyline, clomipramine, doxepin, imipramine, and trimipramine). Evidence is presented for CYP2D6 and CYP2C19 genotype-directed dosing of TCAs. This document is an update to the 2012 Clinical Pharmacogenetics Implementation Consortium (CPIC) guideline for CYP2D6 and CYP2C19 Genotypes and Dosing of Tricyclic Antidepressants.

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 imitation

Not 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.

metaresearch head score (Codex)0.020
metaresearch head score (Gemma)0.060
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.028
Threshold uncertainty score0.107

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.060
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0040.004
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0050.003
Research integrity0.0090.008
Insufficient payload (model declined to judge)0.0080.006

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 head0.194
GPT teacher head0.551
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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreMethods

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

Citations678
Published2016
Admission routes2
Has abstractyes

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