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Record W2029638236 · doi:10.2174/138920012800840392

Pharmacogenetics of Opioids for the Treatment of Acute Maternal Pain During Pregnancy and Lactation

2012· review· en· W2029638236 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueCurrent Drug Metabolism · 2012
Typereview
Languageen
FieldMedicine
TopicPharmacological Effects and Toxicity Studies
Canadian institutionsHospital for Sick Children
FundersCanadian Institutes of Health Research
KeywordsHydromorphoneOxymorphoneHydrocodoneOxycodoneMedicineTramadolOpioidPharmacogeneticsPregnancyMorphinePharmacologyAnesthesiaInternal medicineAnalgesicGenotypeBiology

Abstract

fetched live from OpenAlex

There have been an increasing number of clinical studies investigating the relationship between interindividual genetic variability and the safety and efficacy of opioid analgesics. Despite the widespread use of opioids in pregnant and lactating women for the treatment of acute pain, few studies have investigated the interplay of genetic factors and pregnancy-related physiological alterations in relation to opioid metabolism and response. Some interesting avenues of research require further pursuit- including evidence of cytochrome P450 2D6 (CYP2D6) induction during pregnancy and its effect on the generation of the active opioid metabolites morphine, oxymorphone, O-desmethyltramadol, and hydromorphone following the administration of codeine, oxycodone, tramadol, and hydrocodone respectively. Studies investigating the duration of maternal CYP2D6 induction after delivery are also needed to shed light on genotype to phenotype correlations in breastfeeding mothers using opioid analgesics in the postpartum period.

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)0.000
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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.973
Threshold uncertainty score0.605

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
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 head0.089
GPT teacher head0.408
Teacher spread0.319 · 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